Allelopathy in canola (Brassica napus L)
Md. Asaduzzaman B.Sc. Ag., Sher-e-Bangla Agricultural University, Bangladesh MSc. (by research), Sher-e-Bangla Agricultural University, Bangladesh
A thesis presented in fulfilment of the requirements for the degree of Doctor of Philosophy
Faculty of Science
Wagga Wagga, NSW, Australia
August, 2014
TABLE OF CONTENTS
TABLE OF CONTENTS................................................................................... i CERTIFICATE OF AUTHORSHIP............................................................... iii ACKNOWLEDGEMENTS............................................................................. iv STATMMENT OF CONTRIBUTIONS TO PUBLICATIONS.................... vii ABSTRACTS.................................................................................................... x GLOSSARY AND ABBREVIATIONS........................................................ xiv
Chapter 1 General Introduction....................................................................... 1 Aims and objectives.................................................................... 14
Chapter 2 Literature Review........................................................................ 20 Allelopathy in canola: potential for weed management............. 21 Canola interference for weed control......................................... 24 Chapter 3 Phytotoxicity of canola stubble extracts...................................... 36 Chapter 4 Optimisation of Laboratory Bioassay.......................................... 50 Allelopathic effect of canola on annual ryegrass........................51 Laboratory bioassay for canola allelopathy................................. 55 Chapter 5 Canola (Brassica napus) germplasm shows variable allelopathic effects against annual ryegrass (Lolium rigidum)....................... 74
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Chapter 6 The seedling root response of annual ryegrass (Lolium rigidum) to neighbouring seedlings of a highly-allelopathic canola (Brassica napus cv. Av-opal)...................................................................... 85 Chapter 7 Canola cultivar performances in weed-infested field plots confirms allelopathy ranking from in vitro testing................................... 112 Management of Paterson’s curse (Echium plantagineum) through canola interference.................................................................... 128 Evaluation of canola (Brassica napus) allelopathy: from laboratory to field...................................................................... 132 Chapter
8 Metabolites differentiation of canola genotypes: towards an understanding of canola allelochemicals................................... 137
Chapter 9 General discussion and conclusions.......................................... 159 References................................................................................. 174
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CERTIFICATE OF AUTHORSHIP I hereby declare that this submission is my own work and to the best of my knowledge and belief, understand that it contains no materials previously published or written by another person, nor materials which to a substantial extent have been accepted for the award of any other degree or diploma at Charles Sturt University or any other educational institute, except where due acknowledgement is made in the thesis. Any contribution made to the research by colleagues with whom I have worked at Charles Sturt University or elsewhere during my candidature is fully acknowledged.
I agree that thesis be accessible for the purpose of study and research in accordance with normal conditions established by the Executive Director, Library Services, Charles Sturt University or nominee for the care, loan and reproduction of thesis, subject to confidentially as approved by the University.
Name: Md. Asaduzzaman
Signature Date 19. 12. 2014
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ACKNOWLEDGEMENTS
First and foremost, I am greatly indebted to my supervisory team Professor Jim Pratley, Dr. Min An, Professor Deirdre Lemerle and Dr. David Luckett for their continued support, scholastic guidance and encouragement. I would also like to thank them for mentoring my development as a researcher since the first day of my PhD study. My postgraduate experience at Charles Sturt University was enhanced by their collective team supervision. I would like to acknowledge the Department of Innovation, Industry, Science and Research (DIISR), government of Australia and Charles Sturt University for providing an IPRS (International Postgraduate Research Scholarship) and an APA (Australian Post-graduate Award) scholarship, respectively. Without these funding sources this project would not have been possible. Thanks to the National Brassica Germplasm Improvement Program (NBGIP), NSWDPI, Wagga Wagga for giving me permission to collect weed infestation data in their field trial at Wagga Wagga in 2012, and for helping me conduct my field trial in 2013. The Graham Centre is acknowledged for travel support to attend academic conferences. I would like to express my appreciation to other staff from the School of Agricultural and Wine Sciences including, but not limited to, Dr. John Harper, A/Prof Geoff Burrows and Dr. Sergio Moroni for their help producing annual ryegrass anatomy pictures and for training on the root scanning WinRhizo machine in the Agronomy laboratory. I also thank Dr. Neil Coombes, biometrician, NSW Department of Primary Industry, Wagga Wagga, for his help with my data analysis.
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My sincere thanks also go to David Wade, Laboratory Manager, Environmental and Analytical Laboratories, and Ms Kamala Anggamuthu for their support and help. Thanks to David Thompson, Facility Manager, School of Agricultural and Wine Sciences, for his assistance in the phytotron and Agronomy laboratory. I appreciated technical guidance from Dr Ray Cowley, David Roberts, Peter Deane, and Kerrie Graham of NSW Department of Primary Industry, Wagga Wagga during my two years’ field experiments and canola quality (NIR) laboratory analysis. I thank Michael Loughlin, technical officer, for training me to use the LC-QTOF/MS instrument, speed extractor and rotary evaporator at the National Life Sciences Hub (NaLSH), CSU. I would also like to thank the research staff of AgriBio, La Trobe University, Victoria, Australia for organising system biology training and workshop (cell to ecosystem). Thanks to Metabolomics Australia, Department of Botany, University of Melbourne, This includes Professor Ute Roessner, Dr. Berin Boughton and Dr. Alice Ng for providing training and the chance to work with them on plant metabolomics and for analysis my metabolomics data. My appreciation goes to my all fellow postgraduate students. It has been a good time working together: from constructive discussions to pointless gossiping, from supportive gestures to silly behaviour, all of which I really appreciated. A special thanks to my masters’ supervisor Professor Dr. Md. Fazlul Karim for his realistic advice and suggestions in my research career. Thanks to my wife Shamima Sultana, Dalia for her love, understanding my goal through my study, and her unconditional support and encouragement. Thanks to my v
loving daughter Arisha Zaman, who was always happy to see me – even in my darkest hours! Finally, I would like to express the upmost gratitude to my parents Md. Chan Mia and Akhlima Khanome for their emotional support, phone calls and letters, all of which were greatly appreciated.
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STATEMENT OF CONTRIBUTIONS TO PUBLICATIONS This thesis is a collection of papers resulting from the research undertaken by Mr. Md Asaduzzaman on allelopathy in canola.
The candidate, Md. Asaduzzaman
contributed to these manuscripts as follows: Journal papers Paper 1
Asaduzzaman, M., Pratley, J. E., Min, A., Luckett, D., & Lemerle, D. (2014a). Canola interference for weed control. Springer Science Reviews. DOI 10.1007/s40362-014-0022-2
Paper 2
Asaduzzaman, M., An, M., Pratley, J. E., Luckett, D., & Lemerle, D. (2014b). Laboratory bioassay for canola allelopathy. Journal of Crop Science and Biotechnology [in press]
Paper 3
Asaduzzaman, M., An, M., Pratley, J. E., Luckett, D., & Lemerle, D. (2014c). Canola (Brassica napus) germplasm shows variable allelopathic effects against annual ryegrass. Plant and Soil, 380(1), 47-56. DOI 10.1007/s11104-0142054-4.
Paper 4
Asaduzzaman, M., An, M., Pratley, J. E., Luckett, D., & Lemerle, D. (2014f). The seedling root response of annual ryegrass (Lolium rigidum) to neighbouring seedlings of canola (Brassica napus). Journal of Ecology [to be submitted]
Paper 5
Asaduzzaman, M., Luckett, D. J., Cowley, R. B., Min, A., Pratley, J. E., & Lemerle, D. (2014d). Canola cultivar performance in weed-infested field plots confirms allelopathy ranking from in vitro testing. Biocontrol Science and Technology. 24 (12): 1399-1411. DOI: http://dx.doi.org/10.1080/09583157.2014.942596
Paper 6
Asaduzzaman, M., Pratley, J. E., Min, A., Luckett, D., & Lemerle, D. (2014e). Chemical basis of canola allelopathy: understanding through metabolomics. Frontiers in Plant Science [in press].
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Conference papers Conference
Asaduzzaman. M., Pratley, J. E., Lemerle, D., Luckett, D., Svenson,
paper 1
C., & An, M. (2014). Allelopathy in canola: potential for weed management. Proceedings 17th Australian Research Assembly on Brassicas, Wagga Wagga, Australia, pp.9-11.
Conference
Asaduzzaman. M., An, M., Pratley, J. E., Luckett, D., & Lemerle, D.
paper 2
(2012). Allelopathic effect of canola on annual ryegrass. Proceedings 18th Australasian Weed Conference, Melbourne, Australia, pp.174177.
Conference
Asaduzzaman, M., Luckett, D. J., Min, A., Pratley, J. E., & Lemerle,
paper 3
D. (2014). Management of Paterson’s curse (Echium plantagineum) through canola interference. Proceedings 19th Australasian Weed Conference, Hobart, Australia (accepted).
Conference
Asaduzzaman, M., Luckett, D. J., Min, A., Pratley, J. E., & Lemerle,
paper 4
D. (2014). Evaluation of canola (Brassica napus) allelopathy: from laboratory to field. Proceedings 7th World Congress on Allelopathy, Vigo, Spain, p.162.
Paper 1 provides a review of the literature on canola interference (both allelopathy and competition); although the experimental work in this thesis was concerned with allelopathy only and has reported in the other papers. Paper 2 provides the information about the suitability of the bioassay method for canola germplasm screening under laboratory conditions. Paper 3 provides information about the allelopathic potential of 70 Brassica varieties under laboratory conditions on weed test species annual ryegrass. Paper 4 describes specific aspect of canola allelopathic and competition abilities and verifies the laboratory outcomes under natural field viii
conditions. Paper 5 provides metabolite outcome relating to canola allelopathy. Paper 6 provides additional information about how canola neighbouring plants respond to the canola allelopathy phenomenon.
The preparation and development of papers were performed by the candidate under the guidance and supervision of all members of the supervisory team. Major contributions from other than the supervisory team were acknowledged by coauthorship. The assistance of other individuals in critical reading of the manuscript is gratefully acknowledged in the manuscripts.
I as Principal Supervisor, confirm that the level of contribution by the candidate indicated above is accurate.
Professor Jim Pratley
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ABSTRACT
Canola (Brassica napus L) is Australia’s third largest winter crop. Weeds are major cost for canola production, by reducing yield and quality. Chemical herbicides are cost effective and widely used. However, to reduce the escalating problem of herbicide-resistant weeds and to address environmental concerns, non-chemical weed control tactics with new mode of action are needed for use to include in the canola cropping system. Suppression of weeds by a crop is an important tactic for weed management. Such interference can include competition for resources as well as allelopathy, the production of defensive compounds which escape into the environment through live root secretion and decomposition of plant residues. The aim of this study was to examine the potential for canola allelopathy to suppress weed growth. Canola stubble phytotoxicity was first evaluated by an aqueous extract bioassay on annual ryegrass (Lolium rigidum). In addition inter-cultivar and intracultivar canola autotoxicity was also assessed. Canola genotype residues differed significantly in their inhibition of root elongation of annual ryegrass (12% to 62%). Extract phytotoxicity significantly reduced germination as well as the root (81% to 93%) and shoot (0% to 43%) growth of receiver canola. Canola stubble toxicity on ryegrass root growth was dependent upon extract concentration (0%, 25%, 50% and 75%) for each genotype.. Cultivar Charlton was exhibited the greatest inhibitory effect followed by Sardi607, Zhonshu-ang-No4 and Ag-spectrum. Canola stubble extract also showed some differences for inter-cultivar and intra-cultivar inhibition.
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The Equal Compartment Agar Method was used to evaluate canola seedling allelopathy on annual ryegrass from a collection of 60 Brassica napus genotypes originating from five continents. In addition, 10 non-napus Brassica genotypes were tested. Significant differences were found among these canola genotypes as measured by an inhibition index which ranged from 8% to 55% inhibition of annual ryegrass root growth relative to the control. Canola genotypes originating from different countries also differed significantly in their seedling allelopathy. The screening of 70 genotypes showed that substantial differences were present, from strong (eg. cv. Av-opal) to weak (eg. cv. Barossa) genotypes. This suggested a genetic basis for differential allelopathic potential between genotypes. Canola allelopathy of 312 genotypes was investigated in the field in 2012, where significant differentiation was observed between genotypes in their ability to suppress weed growth of a natural infestation. Several genotypes showed significant weed suppressive ability against shepherd purse (Capsella bursa-pastoris), Indian hedge mustard (Sisymbrium orientale) and barley grass (Hordeum leporinum), despite short crop height. Crop height and early vigour influenced weed suppression. The combined effects of allelopathy and competition determined the weed infestation levels seen across the genotypes. A strong correlation (r = 0.77**) was found between the weed suppression by 36 genotypes in the field and their allelopathy under laboratory conditions using ECAM. A subsequent field experiment in 2013 containing extreme allelopathic and competitive genotypes was undertaken to better assess the allelopathic effects of canola genotypes, under the influence of two sowing times. Some of the variation in the field performance of genotypes was predicted by their performance in the laboratory assay. xi
Crop and weed biomass varied significantly between the genotypes in the field; high-weed-biomass was harvested in Pak85388-502, Av-opal, Av-garnet and Barossa compared with low biomass in Atr-409 and Cb-argyle. The weed biomass also significantly varied between genotypes in early and late sowing times and ranged from 21 g m-2 to 228 g m-2 and from 78 g m-2 to 297 g m-2 respectively. Avopal and Pak85388-502 plots contained significantly lower weed biomass, while Atr409, Cb-argyle and Barossa produced higher weed biomass. Weed biomass in the early sowing was lower than in the late sowing by 25%, 30% and 35% in Atr-409, Cb-argyle and Barossa, respectively. Genotypes Av-garnet and Av-opal produced the highest grain yields; which were almost 50% lower in the late sowing time. Despite its high weed suppressive ability, Pak85388-502’s yield was low compared with the other strongly competitive or allelopathic genotypes in both sowing times. This finding suggested that its lack of local adaptation for yield was independent of its expression of allelopathy and competition. This second year field study also assessed the role of canola interference ability on the aggressive weed Paterson’s curse (Echium plantagineum). Genotypes that display strong interference, such as Av-opal, Pak85388-502 and Av-garnet, significantly reduced the rosette diameter and delayed the reproductive stage of E. plantagineum, at both early and late sowing times. Canola genotypes Atr-409, Cbargyle and Barossa showed much weaker interference ability. In order to identify the responsible allelochemicals, an extensive chemical analysis was undertaken by an advanced metabolomics approach. The sensitive LCQTOF-MS technique was employed to identify the root allelochemicals produced by xii
the extreme canola genotypes identified in laboratory and field experiments. Chemical analysis of each genotype was conducted for three plant parts: shoot, root, and root exudates of 13 days-old-seedlings. A total of 2806 metabolite mass signals was identified. The total numbers of secondary metabolites were distributed differently in the root and shoot tissue and root exudates among the genotypes. Roots generally contained a higher number of allelochemicals than shoot tissue and root exudates, depending on genotype. Fourteen pure compounds were identified from root extracts of both allelopathic and non-allelopathic genotypes. Of these only 8 compounds were identified in root exudates as potential allelochemicals. Sinapyl alcohol, p-hydroxybenzoic acid, 3,5,6,7,8-pentahydroxy flavone, jasmonic acid and methyl-jasmonate were isolated from the allelopathic genotypes Av-opal and Pak85388-502. The presence of these compounds in the strongly allelopathic genotypes suggests that they may be involved in the allelopathic activity of canola seedlings. It is concluded that substantial variability exists in canola germplasm with regard to canola allelopathic activity, and the production and exudation of allelochemicals. Canola seedlings produce and exude certain compounds into the growth medium which inhibit the growth of annual ryegrass in the laboratory and other weed species in the field. Canola seedling allelopathy has great potential for weed suppression. The development of canola cultivars with enhanced allelopathic activity could be an important supplement to traditional chemical modes of action, especially when combined with other competitive traits such as early vigour. More research is needed to understand the genetic control of this allelopathic trait and also potential new modes of action for the development of new herbicide groups. xiii
Chapter 1 General Introduction This chapter provides information on the origin, distribution and the significance of canola; the problems of weed control in canola; and current chemical weed-management options and associated drawbacks. The research aims and objectives are defined here.
Key contents
Origin and distribution of canola
Significance of canola
Impacts of weeds
Chemical weed management o
Triazine-tolerant canola
o
Imidazolinone-tolerant canola
o
Genetically-modified canola
Shortcomings of current chemical weed management
Research aims and objectives
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Chapter 1 General Introduction 1.1. Canola: Origin and distribution Brassica crops are among the oldest cultivated plants known to humans with written records dating back to ca. 1500 BC (Prakash, 1980). Brassica rapa had the widest distribution historically. Brassica napus (an allotetraploid) is thought to have multiple origins and is derived from a cross between two closely related ancestral diploid species: B. rapa and B. oleracea. B. napus is believed to have originated in the Mediterranean area where the wild forms of its ancestral species were sympatric (Raymer, 2002). Production of edible oils from Brassica was started by ancient civilizations in Asia and the Mediterranean (Hedge, 1976). Rapeseed (B. napus) was first grown commercially in Canada in 1942 for fuel and lubricant; followed by Australia in 1969 (Colton & Potter, 1999). Canola (B. napus) is a member of Brassicaceae family. The term ‘canola’ is derived from Canadian oil, low acid and was originally the trademark name of a Canadian cultivar. In the 1970s very intensive breeding programs in several countries produced high-quality Brassica cultivars including Brassica napus (Figure 1). Canola has become the global generic term for all B. napus cultivars that have low glucosinolates and low erucic acid. The “canola-quality” label is now also used for B. juncea (Indian mustard) cultivars that have canola-like quality. The main difference between traditional rapeseed and canola is that rapeseed contains a high amount of erucic acid (up to 55 percent by volume) and anti-nutritional compounds known as glucosinolates (>100 µ mol/g), while canola has low erucic acid (<2%) and glucosinolates (<30 µ mol/g ) (Sovero, 1993). Canola is only a quality standard
2
and not a classification based on taxonomy. Varieties (cultivars) with canola quality are also termed as ‘double low’ or ‘double zero’.
B. nigra n=8 BB
B. juncea
B. carinata n=17
n=18
BBCC
AABB
B. oleracea
B. napus
n=9
n=19
CC
AACC
B. rapa n=10 AA
Figure 1 The triangle of U representing the genomic relationship among Brassica species (source: Raymer, 2002). n is the haploid chromosome number. The capital letters show the genome relationship between the three diploid progenitors and the three allotetraploids. 3
1.2. Significance of canola Canola is a versatile crop. The oil and meal derived from the seed have several applications and are used in a large number of end products for both human and animal consumption. Canola reaches the human consumer via at least three distinct supply chains. Firstly, canola seed is produced for oil which is directly used for human consumption (Raymer, 2002). Canola oil is very low in saturated fatty acid and is used both as cooking oil but also in the manufacture of margarine. Secondly, canola meal is produced as a by-product during the extraction of oil from canola seed; and it is widely used as a high protein feed source in animal nutrition. Whole canola seed may also be used directly as animal feed (Roth-Maier, 1999) although this use is limited in Western countries. The livestock sector and its consequent usage of feed stuff is growing rapidly, causing higher demand for feed products from the oilseed industry. Thirdly, canola products are used in applications where the supply chain links farmers to industrial processors that utilise the seed, oil or meal in cosmetics, food activities, emollients, lubricants and plastic. New uses of canola, such as the production of bio-diesel (Wu & Muir, 2008) also provide opportunities for the canola industry to expand, although the use of an edible crop to produce a fossil-fuel substitute is contentious.
1.3. Canola in Australia The first high-quality canola cultivars (cv. Maluka and
Shiralee)
became
available in Australia in 1987 (Colton & Potter, 1999). The availability of much 4
better cultivars, crop agronomic packages, and good prices through the 1990s, made the crop increasingly attractive to growers and led to rapid expansion in the acreage planted to the crop (AOF, 2013). As a result, the area sown to canola in Australia rose from 0.1 million hectares in the early 1990s to 2.4 million hectares, and production increased from 0.1 million tonnes to a peak of 3.2 million tonnes (AOF, 2013). From a minor crop in the late 1980s, canola is now Australia’s third largest broad-acre crop after wheat and barley. Australia is the world’s second largest canola exporter.
The crop is widely grown across south-eastern Australia and Western
Australia (Figure 2). A major factor in the expansion of the Australian canola industry has been the development of blackleg-resistant cultivars. Blackleg is a major disease of canola caused by the Leptosphaeria maculans fungus. Local blackleg isolates are more virulent than those in other countries and Australian canola cultivars are the most blackleg-resistant spring cultivars in the world (Howlett et al., 1999).
1.4. Impacts of weeds Weeds are one of the most important factors affecting yield in crops, including canola (Brenchley, 1917; Salisbury, 1961; Gill et al., 1984; Lemerle et al., 2001; Naylor & Lutman, 2007). Weeds interfere with crop plants, causing serious impacts in the competition for above or below ground resources (light, water and soil nutrients) (Naylor & Lutman, 2007). Canola is often exposed to severe competition from weeds which are often considered as the most limiting factor (Tomass, 1992). In Australia, since canola is usually planted from late April through to June, it germinates in cold or cooling soil. This often leads to slow early growth and so crops
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are very susceptible to competition from weeds during this vegetative phase (Sutherland, 1999). Weeds such as toad rush (Juncus bufonius) are highly
Hectares per statistical local area 1-1000 1001-5000 5001-10000 10001-25000 25001-50000 50001-80960
Figure 2 Areas of canola production in Australia (ABSA, 2008; AOF, 2013)
competitive for available nitrogen, which potentially reduces yield (Sutherland, 1999). Common grass weeds such as annual ryegrass (Lolium rigidum), vulpia (Vulpia myuros) and wild oat (Avena spp) are widespread in canola in southern Australia (Lemerle et al., 2001), and can also harbour cereal root disease (Sutherland, 1999). Weed seeds present in the harvested product reduce the quality 6
and market value of the canola seed. An Australian study demonstrated that heavy infestations of wild radish (Raphanus raphanistrum) can reduce canola yields by up to 90% (Blackshaw et al., 2002) and also greatly reduce the quality of the canola seed meal; mainly because the weed seeds have high glucosinolates and high erucic acid. Brassicaceous weed seeds are of similar size to that of canola and cannot be graded out (Mailer & Cornish, 1987; Cheam & Code, 1995). The mixture of weed seeds and other debris in harvested canola leads to direct yield and income penalties (Sutherland, 1999).
1.5. Chemical weed management strategies Canola cultivars tolerant to a range of herbicide groups are commercially available and are used as an effective weed management tactic. Genetic herbicidetolerance to triazine (Group C), imidazolinone (Group B), glyphosate (Group M)), and glufosinate ammonium (Group N) are commercialised globally, although there are restrictions on the use of genetically modified (GM) canola in some Australian jurisdictions.
1.5.1. Triazine-tolerant canola Triazine-tolerant (TT) cultivars are derived from a spontaneous mutation conferring tolerance to group C (simazine and atrazine) herbicides (Mchughen, 2011). TT cultivars have gained a significant share of the canola area in Australia. This was primarily because of the relatively low cost of the herbicides, safe postemergent control of broad-leaf weeds, the opportunity to control weeds with resistance to the herbicide group C (eg. ryegrass resistant to group A herbicides), and its close fit with farmers’ agronomic practices
(Norton & Roush, 2007). 7
Consequently, the TT system led to a rapid expansion of the canola area of Australia, particularly where wild radish was problematic and selective herbicides were limited or non-existent. However, this approach has not been widely adopted outside Australia due to a photosynthetic penalty of the trait itself, which often reduces yield by 10%, and up to 30% in some weed-free circumstances compared with conventional canola (Robertson et al., 2002). The lack of plant vigour of TT cultivars also reduces the ability to provide crop competition, so this TT technology is cost effective in areas where closely related weed species are present. Some attempt has been made to improve the inherent vigour of TT cultivars by incorporating the trait in recent F1 hybrids.
1.5.2. Imidazolinone-tolerant canola Imidazolinone-tolerant (Clearfield® Group B) canola cultivars were developed through irradiation mutagenesis and offered an alternative herbicidal option to the TT cultivars for control of Brassicaceae weeds such as wild radish, wild mustard and stink weed (Tan et al., 2005). The imidazolinone chemicals have good activity on a broad spectrum of both grass and broadleaf weeds by inhibiting the critical enzyme acetohydroxyacid synthase (AHAS) without yield penalty (Tan et al., 2005). These herbicides also have low mammalian toxicity, possess a favourable environmental profile, and are effective at low application rates. Clearfield® technology has been rapidly adopted by growers in both Canada and the USA, but is not so popular in Australia; a high level of pre-existing resistance to group B herbicides in some weeds, particularly annual ryegrass, wild radish and wild turnip (Brassica rapa), has also restricted the widespread use of these chemicals in Australia (Norton & Roush, 2007). 8
1.5.3. Genetically modified (GM) canola The application of recombinant DNA technologies to canola has produced herbicide-tolerant GM canola cultivars, including those that are tolerant of glyphosate (Roundup Ready®, RR) and glufosinate ammonium (Basta®). GM canola was first commercially introduced into Australia in 2008.
Glyphosate-resistant GM canola Canola cultivars have been genetically modified for tolerance of glyphosate
(Group M) to provide a broader non-selective herbicide for weed management. In both Canada and the USA, growers rapidly accepted this technology to control many difficult weeds and its use has resulted in decrease in the use of other herbicides (Brookes & Barfoot, 2005; Mchughen, 2011). Favourable biochemical functions, low cost, tight soil sorption, application flexibility and low minimum toxicity helped make glyphosate the most widely used herbicide in the world (Gianessi, 2005). In Australia, the availability of glyphosate-resistant GM canola provided growers with superior weed control and crop safety. This system is also very efficient for the control of annual ryegrass while a double application strategy has been shown to provide the best option to control broadleaf weeds (Robins, 2012). However, GM canola has been banned in some countries, including Japan and parts of Europe, which limits markets for Australian canola.
Glufosinate-tolerant GM canola A transgenic approach was used to achieve glufosinate (Group N herbicide)
tolerance in canola. Glufosinate-tolerant canola was launched in 1996 in open pollinated cultivars, but was less effective than glyphosate tolerance (Green, 2009). 9
Glufosinolate tolerance is now stacked with two other transgenes that control pollination for hybrid seed production (Green, 2009). This herbicide group has no soil residual activity and, as with glyphosate, glufosinate was broadly adopted throughout Canada. However, in Australia the relatively high cost of the chemical, poor efficacy and more restrictive application timing relative to weed size, has meant that adoption has been very limited (Green & Owen, 2010).
Pyramiding of herbicide-tolerance genes In 2014, the first canola cultivars will be released in Australia containing two,
‘pyramided’, herbicide-tolerance genes, in this case Roundup Ready® plus triazinetolerance. These RR-TT genotypes are being promoted as offering improved herbicidal rotation options to reduce the selection pressure on target weeds and reduce the chance of herbicide-resistant weeds evolving, thereby extending the durability of these herbicides.
1.6. Shortcomings of current chemical weed management The development of herbicide-tolerant canola has allowed farmers to simplify their chemical weed control options. However, with farming system simplicity comes less diversity and greater risk. Certainly, the frequent use of herbicide-tolerant canola in the absence of other control measures is now common. The repetitive use of the same herbicide-tolerant crops with their associated herbicides can result in overuse of the same mode-of-action, thereby allowing weeds to adapt to the system and leading to herbicide-resistant weeds (Owen and Zelaya, 2005). So, the sustainability of current weed control approaches is a major concern. For instance, in Australia, the widespread use of TT canola cultivars and triazines 10
has led to an escalation in resistant populations of weeds, particularly in wild radish (Heap, 2012). The yield and oil penalty associated with TT canola has been confirmed by Australian studies across a wide range of environments; however, this penalty is commercially acceptable or even desirable, compared with the alternative of poor weed control and reduced yield from weed competition. In contrast, IT canola has increased profit by minimising the yield penalty but there are already large numbers of imidazolinone-resistant weed populations in Australian cropping systems. The continued application of these herbicides is likely to exacerbate the development of more herbicide-resistant weed biotypes (Preston et al., 1999). The implementation of RR canola has changed the pattern of herbicide use: decreasing the use of other herbicides and giving growers an efficient and simple solution for weed control. The economics of RR canola are challenging in the Australian context, given that there are high seeding costs, restricted delivery options and additional costs with keeping GM seed segregated. RR cultivar production was subsidized by Monsanto during the 2012 season to stimulate adoption of the technology. Glyphosate-resistant annual ryegrass evolved in Australia in the 1990s (Pratley et al., 1996; Hashem et al., 2011; AGSWS, 2014). This resistance has now been reported around the world with other weeds developing resistance including goosegrass (Eleusine indica) (Lee & Ngim, 2000), horseweed (Conyza canadensis) (VanGessel, 2001), ragweed (Ambrosia artemisiifolia) (Heap, 2006), Johnson grass (Sorghum halepense) (Heap, 2006) and Italian ryegrass (Lolium multiflorum) (Perez & Kogan, 2003; Heap, 2014). Some of this breakdown in weed susceptibility can be attributed to the widespread and repeated use of glyphosate in non-crop situations
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e.g. railway lines, roadsides, fence lines, around buildings and in fallow fields (Preston, 2010). The attractive flexibility of glyphosate, often resulted in growers delaying applications of herbicides in the field, ensuring that more of the target weeds have emerged prior to post-emergent chemical application. The same approach has been used with TT and CL cultivars. Unfortunately, such delayed application means that the weeds have already begun to compete with the canola for resources. Assuming that the herbicide application methods are best-practice, it is much easier to kill small, weak, weed seedlings rather than larger plants. Because glyphosate has been so effective at controlling emerged weeds, multiple applications of herbicide have resulted in extremely high selection pressure, which has accelerated the appearance of glyphosate-resistant weeds (Heap, 2006). Recent evidence has confirmed that the overuse of glyphosate in GM canola is likely to produce even more glyphosateresistant weeds (Munier et al., 2012). In addition, the intensive and repeated use of a single herbicide has led to shifts in the weed populations from more susceptible to more tolerant species, as reported for corn and soybeans in USA (Marshall et al., 2000). The potential for gene flow via pollen movement from resistant weeds is significant in canola (Vencill et al., 2012). This is an area of importance in determining both the longevity of herbicide-tolerant canola, and the possible environmental impacts. Evidence has already been recorded in field experiments that trans-genes can move through pollen to conventional canola but also to related weed species such as wild mustard (Brassica campestris) (Simard et al., 2006). Moreover, Brassica napus can hybridize with Indian mustard (B. juncea), Ethiopian mustard (B. 12
carinata), black mustard (B. nigra), annual wall rocket (Diplotaxis muralis) and wild radish (Raphanus sp.) (Chèvre et al., 1997; Green, 2009), albeit at very low frequency in the field environment. Escaped resistance genes can create resistant canola, which become volunteer weeds in both fallow and subsequent crops. In addition, pollen-mediated canola gene flow can result in multiple herbicide-resistant weeds. This is one of the most significant challenges arising from the use of GM canola cultivars with pyramided herbicide tolerance (Senior & Dale, 1999; Beckie et al., 2003). The growing of GM canola may result in unintended sociological and economic impacts, particularly where adjacent fields are under organic crop production or where a producer wishes to grow a GM-free canola crop. Coexistence will need consideration of the presence of herbicide-tolerant canola in neighbouring fields (Légère, 2005). As an alternative to herbicide use, non-chemical approaches using physical and mechanical means have major appeal but such approaches are themselves problematic. Mechanical weed control approaches, such as tillage, do reduce annual weeds when used prior to planting (if the weeds have already germinated) but are less effective on slow-growing and broadleaf weeds. Cultivation may bury weed seeds preventing successful emergence but may also stimulate germination in other species (the so-called ‘tickle’ approach). In addition, farmers are now aware of the issues concerning soil erosion, compaction and carbon losses and therefore prefer conservation tillage, with less soil disturbance in the field. The increasing cost of fossil fuel also makes weed control by cultivation less economic. In conclusion, to maintain canola production and effectively manage weeds, an integrated weed management system is required. Tactics such as canola 13
interference could have good prospects for use in such a system. Crop interference is a combination of crop competitiveness and allelopathy (chapter 2). Allelopathy has been recognized as an untapped potential weed management tool (Purvis et al., 1985). In addition, stubble residues and green manure of several Brassica species have phytotoxic potential for weed control (Boydston & Hang, 1995; Brown & Morra, 1996; Al-Khatib et al., 1997; Vaughn & Berhow, 1999; Petersen et al., 2001; Turk & Tawaha, 2003; Haramoto & Gallandt, 2005). Any naturally-occurring compounds involved in canola allelopathy have the potential for development as natural herbicides. Aims and objectives The central aim of this study was to evaluate canola allelopathy for its potential role in achieving effective weed control. The specific planned objectives of this study were: 1. To examine canola stubble phytotoxicity (chapter 3) 2. To explore the allelopathic profile of a worldwide collection of canola accessions in live tissues under laboratory conditions (chapter 5) 3. To identify the sources of useful germplasm and to understand the genetic diversity for allelopathy in canola (chapter 5) 4. To characterise the responses of receptor weed species to canola allelochemicals (chapter 6) 5. To test the correlation between laboratory measures of allelopathy and corresponding performance in typical field conditions (chapter 7)
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6. To identify the allelopathic chemicals present in the extreme canola genotypes (chapter 8)
References Al-Khatib, K., Libbey, C., & Boydston, R. A. (1997). Weed suppression with Brassica green manure crops in green pea. Weed Science, 45(3), 439-445. Australian Glyphosate Sustainability Working Group (2014). from http://glyphosateresistance.org.au/index.html Australina Bureau of Statistics Agricultural Census (2008). Year Book Australia. Canberra: Australian Bureau of Statistics. Australian Oilseeds Fedaration (2013). Crop Report. Retrieved 25/10/2013, from http://www.australianoilseeds.com/oilseeds_industry/crop_report?year=9514 #load. Beckie, H. J., Warwick, S. I., Nair, H., & Séguin-Swartz, G. (2003). Gene flow in commercial fields of herbicide-resistant canola (Brassica napus). Ecological Applications, 13, 1276-1294. Blackshaw, R. E., Lemerle, D., Mailer, R., & Young, K. R. (2002). Influence of wild radish on yield and quality of canola. Weed Science, 50, 344-349. Boydston, R. A., & Hang, A. (1995). Rapeseed (Brassica napus) green manure crop suppresses weeds in potato (Solanum tuberosum). Weed Technology, 9, 669-675. Brenchley, W. E. (1917). The effect of weeds upon cereal crops. The New Physiologist, 16 (3 & 4), 53-76. Brookes, G., & Barfoot, P. (2005). GM crop: the global economic and environmental impact-the first nine years 1996-2004. AgBioForum, pp. 181-196. Brown, P. D., & Morra, M. J. (1996). Hydrolysis products of glucosinolates in Brassica napus tissues as inhibitors of seed germination. Plant and Soil, 181(2), 307-316. Cheam, A. H., & Code, G. R. (1995). The biology of Australian weeds Raphanus raphanistrum L. Plant Protection Quarterly, 10(1), 2-13. Chevre, A. M., Eber, F., Baranger, A., & Renard, M. (1997). Gene flow from transgenic crops. Nature, 389, 924-924. 15
Colton, B., & Potter, T. (1999). History: canola in Australia: The first 30 Years. Australian Oilseed Industries, Australia. Gianessi, L. P. (2005). Economic and herbicide use impacts of glyphosate-resistant crops. Pest Management Science, 61, 241-245. Gill, H. S., Sandhu, K. S., Mehra, S. P., & Tarlok, S. (1984). Efficacy of some herbicides for control of weeds in Indian mustard. Indian Journal Weed Science, 10, (7), 171-175. Green, J. M., & Owen, M. D. K. (2010). Herbicide-resistant crops: utilities and limitations for herbicide-resistant weed management. Journal of Agricultural and Food Chemistry, 59, 5819-5829. Green, J. M. (2009). Evolution of glyphosate-resistant crop technology. Weed Science, 57, 108-117. Haramoto, E. R., & Gallandt, E. R. (2005) Brassica cover cropping: I. Effects on weed and crop establishment. Weed Science, 53, 695-701. Hashem, A., Collins, R. M., & Bowran, D. G. (2011). Efficacy of interrow weed control techniques in wide row narrow-leaf lupin. Weed Technology, 25: 135-140. Heap, I. (2012). International survey of herbicide resistant weeds. Western Society of Weed Science, 5, 27-29. Heap, I. M. (2013). International survey of herbicide-resistant weeds. www.weedscience.org. Heap, I. M. (2006). International survey of herbicide-resistant weeds. www.weedscience.org. Hedge, I. C. (1976). A systematic and geographical survey of the world cruciferae, In: Macle-od, A. J., & Tones, B. M. G., eds. The biology and chemistry of cruciferae. Academic press, New York, pp. 1-45. Howlett, B., Ballinger, D., & Barbetti, M. (1999). Disease of canola: The first 30 Years. Australian Oilseed Industries, Australia. Lee, L. J., & Ngim, J. (2000). A first report of glyphosate-resistant goosegrass (Eleusine indica (L) Gaertn) in Malaysia. Pest Management Science, 56, 336339. Légère, A. (2005). Risks and consequences of gene flow from herbicide-resistant crops: canola (Brassica napus L) as a case study. Pest Management Science, 61, 292-300. 16
Lemerle, D., Blackshaw, R. E., Smith, A. B., Potter, T. D., & Marcroft, S. J. (2001). Comparative survey of weeds surviving in triazine-tolerant and conventional canola crops in south-eastern Australia. Plant Protection Quarterly, 16 (1), 37-40. Mailer, R. J., & Cornish, P. S. (1987). Effects of water stress on glucosinolates and oil content in the seeds of rape (Brassica napus L.) and turnip rape (Brassica rapa L). Australian Journal of Experimental Agriculture, 27, 707-711. Marshall, M. W., Al-Khatib, K., & Maddux, L. (2000). Weed community shifts associated with continuous glyphosate applications in corn and soybean rotation. Western Society of Weed Science, Kansas, pp. 22-25. Mchughen, A. (2011). Impact of herbicide tolerant crops on weed management in the Asia Pacific region. Proceedings 23rd Asian-Pacific Weed Science Society Conference, Cairns, Australia, pp.291-303. Munier, D., Brittan, K., & Lanini, W. T. (2012). Seed bank persistence of genetically modified canola in California. Environmental Science and Pollution Research, 19, 2281-2284. Naylor, R. E. L., & Lutman, P. J. (2007). What is weed? In: Naylor, R. E. L. ed. Weed management hand book. Blackwell Science, Oxford, pp. 19-40. Norton, R. M., & Roush, R. T. (2007). Canola and Australian farming systems 20032007, University of Melbourne. Owen, M. D. K., & Zelaya, I. A. (2005). Herbicide-resistant crops and weed resistance to herbicides. Pest Management Science, 61, 301-311. Perez, A., & Kogan, M. (2003). Glyphosate-resistant Lolium multiflorum in chilean orchards. Weed Research, 43, 12-19. Petersen, J., Belz, R., Walker, F., & Hurle, K. (2001). Weed suppression by release of isothiocyanates from turnip-mulch. Agronomy Journal, 93, 37-43. Prakash, S. (1980). Cruciferous oilseeds in India. Brassica crops and wild allies, Biology and breeding. Japan Scientist Society. Tokyo, pp. 151-163. Pratley, J., Eberbach, P., Incerti, M., & Broster, J. (1996). Glyphosate resistance in annual ryegrass. Procedings 11th Annual Conference of Grassland Society of NSW. p. 122. Preston, C. (2010). Managing glyphosate resistant weeds in Australia. Proceedings 16th Australian Weeds Conference. pp. 250-253.
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Preston, C., Roush, R. T., & Powles, S. B. (1999). Herbicide resistance in weeds of southern Australia: why are we the worst in the world? Proceedings 12th Australian Weeds Conference. pp. 454-459. Purvis, C., Jessop, R., & Lovett, J. (1985). Selective regulation of germination and growth of annual weeds by crop residues. Weed Research, 25, 415-421. Raymer, P. L. (2002). Canola: an emerging oilseed crop. In: Janick, J., & Whipkey, A., eds. Trends in new crops new uses. ASHS press, Alexandriapp, 122-126. Robertson, M. J., Holland, J. F., Cawley, S., Potter, T. D., Burton W., Walton G. H., . . . (2002) Growth and yield differences between triazine-tolerant and nontriazine-tolerant cultivars of canola. Australian Journal of Agricultural Research, 53, 643-651. Robins, R. (2012) The controversy over GM canola in Australia as an ontological politics. Environmental Values, 21, 185-208. Roth-Maier, D. A. (1999). Investigations on feeding full fat canola seed and canola meal to poultry. 10th International Rapeseed Congress. Canberra. Salisbury, E. J. (1961). Weed and aliens. In: Salisbury, E. J. ed. Naturalist. Collins, London. Senior, I. J., & Dale, J. E. (1999). Molecular aspects of multiple transgenes and gene flow to crops and wild relatives. Proceedings British Crop Protection Council. Pp. 1-4. Simard, M. J., Légère, A., & Warwick, S. I. (2006). Transgenic Brassica napus fields and Brassica rapa weeds in Quebec: sympatry and weed-crop in situ hybridization. Canadian Journal of Botany, 84, 1842-1851. Sovero, V. (1993). Rapseed, a new oilseed crop for the United States. In: Janick, J., & Simons, J. E. Eds. New crops. Wiley, New York, 302-307. Stuchbery, J. (2009). Better oilseeds: an adviser's view on GM canola. Australian Grain, 18(6), 16-18. Sutherland, S. (1999). Weed management. Canola in Australia: The first 30 years. Australian Oilseed Industries, Australia. Tan, S., Evans, R. R., Dahmer, M. L., Singh, B. K., & Shaner, D. L. (2005). Imidazolinone-tolerant crops: history, current status and future. Pest Management Science, 61, 246-257. Tomass, P. (1992). Canola grower manual. Canola council of Canada. Winnipeg, Canada. 18
Turk, M. A., & Tawaha, A. M. (2003). Allelopathic effect of black mustard (Brassica nigra L) on germination and growth of wild oat (Avena fatua L). Crop Protection, 22, 673-677. VanGessel, M. J. (2001). Glyphosate-resistant horseweed from Delaware. Weed Science, 49, 703-705. Vaughn, S. F., & Berhow, M. A. (1999). Allelochemicals isolated from tissues of the invasive weed garlic mustard (Alliaria petiolata). Journal of Chemical Ecology, 25(11), 2495-2504. Vencill, W. K., Nichols, R. L., Webster, T. M., Soteres, J. K., Mallory-Smith, C., Burgos, N. R., . . (2012). Herbicide resistance: toward an understanding of resistance development and the impact of herbicide- resistant crops. Weed Science, 60, 2-30. Wu, J., & Muir, A. D. (2008). Comparative structural, emulsifying, and biological properties of 2 major canola proteins, cruciferin and napin. Journal of Food Science, 73, 210-216.
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Chapter 2 Literature Review This chapter provides the majority of the literature review to the issues of canola interference (allelopathy and competition) and the difficulties of attribution in the field situation. This published review identified the research potential and gaps in the interference research area, which then formed the basis of the research in this thesis. The experimental work in this thesis focused on allelopathy rather than competition.
Key contents
Competition o
Above-ground competition
o
Below-ground competition
o
Selecting canola ideotype
Allelopathy o
Canola residues allelopathy
o
Bio-fumigation
o
Canola Allelopathy by Intact Roots of Living Plants
Canola root exudates and phyto-chemistry
Root exudates and rhizosphere communication
Conclusion
[
Conference paper 1: Asaduzzaman. M., Pratley, J. E., Lemerle, D., Luckett, D., Svenson, C., An, M. (2014). Allelopathy in canola: potential for weed management. Proceedings 17th Australian Research Assembly on Brassicas, Wagga Wagga, Australia, pp. 9-11. Paper 1 (review): Asaduzzaman. M., Pratley, J. E., An, M., Lemerle, D., Luckett, D. (2014). Canola interference for weed control. Springer Science Reviews DOI 10.1007/s40362-0140022-2. 20
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Allelopathy in canola: potential for weed management M. Asaduzzaman
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, Jim Pratley , Deirdre Lemerle , David Luckett , 1 13 Charles Svenson and Min An 1 Environmental and Analytical Laboratories, Faculty of Science, Charles Sturt University, Wagga Wagga NSW 2678 Australia 2 School of Agriculture & Wine Sciences, Charles Sturt University, Wagga Wagga NSW 2678, Australia 3 EH Graham Centre for Agricultural Innovation (an alliance between NSW Department of Primary Industries and Charles Sturt University), Wagga Wagga NSW 2678, Australia Email:
[email protected]
INTRODUCTION Canola (Brassica napus L) is a member of the family Brassicaceae, and is one of the leading crops in the world for the production of vegetable oil for human consumption, animal nutrition, and, more recently, biodiesel (Yasumoto et al. 2010). It has received great attention in Australian agriculture due to its price, substitution for other vegetable oils, increased demand due to population growth, demographic changes, economic growth, changing consumer preferences, domestic and foreign trade, and food policies. Moreover, as a cover and/or break crop it has played a significant role in agriculture due to its wide variety of benefits to the overall farming system. In Australia, canola is third-largest broad-acre crop (after wheat and barley), and according to the AOF (Australian Oilseeds Federation), production for 2011-12 is estimated at 2.44 million tones from 1.81 million ha (www.australianoilseeds.com). There are many factors responsible for low yields in canola crops, among them, inevitably, the large number of weed species that occur and the difficulty of economic control. In addition, Australian farmers have moved away from aggressive tillage practice because of the extreme risk of soil erosion, damage to soil structure, and reduction in soil carbon. Consequently, current crop rotations and seeding techniques are highly dependent on herbicides. Repetitious use of herbicides has selected for resistant weed biotypes – herbicide resistance has evolved in 25 weed species in Australia, and a number of weed species have evolved resistance to several herbicide modes of action. Foremost among them is annual ryegrass, and some of its populations have evolved resistance to all the selective-mode-of-action herbicide groups (Storrie et al. 2009). In recent years, the increasing cost of herbicides and ecological and human health concerns, have renewed interest in exploiting non-chemical alternatives including allelopathy and crop competitiveness (Holethi et al. 2008).
COMPETITIVENESS IN CANOLA AGAINST WEEDS Canola is a useful break crop in rotations, with a wide range of cultivars available including conventional, forage, and hybrid types. There is significant variation in competitiveness with weeds between cultivars (Lemerle et al. 1996; Harker et al. 2003). In Australia, data show large variation in competitiveness of local canola genotypes in the field against the most common weed (annual ryegrass), and triazine-tolerant cultivars are generally considered poorly competitive, whilst the vigorous hybrids are thought to offer an improved opportunity to suppress weeds as has been recorded in wheat (Lemerle et al. 1996). Recently, Lemerle et al. (2010) documented the competitiveness of 15 canola types against annual ryegrass where significant differences in crop yield were recorded in weedy and weed-free plots, with percentage yield reductions from weeds of 60-100%. Competitiveness was correlated with crop dry matter, with more vigorous genotypes being most competitive. Therefore, there is a tremendous opportunity to breed for highly competitive canola cultivars. Target characters may include: rapid germination, robust establishment, early seedling vigor, leaf size, leaf shape, and leaf number.
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ALLELOPATHY IN CANOLA Allelopathy is a process whereby a plant gives itself a competitive advantage by placing phytotoxins into the near adjacent environment (Pratley, 1996). Due to its potential, the science of allelopathy has attracted worldwide attention in the last two decades, and several areas of crop allelopathy have been identified (Liu et al. 2011). To date, research has indicated that under both tillage and no-till systems, canola stubbles, residues or extracts have allelopathic effects – influencing both the growth of canola itself, and the growth of a number of weeds (Uremis et al. 2009, Moyer and Huang, 1997). Biofumigation is another ‘feature’ of canola where volatiles from decomposed Brassica napus inhibit soil born pest and diseases (Gimsing and Kirkergaard 2009) and may also affect the germination and the root growth of some weed. Some effort has been placed on the isolation and identification of allelopathic compounds from canola residues and their associated soils but there are no reports of allelochemicals from root exudates or leaf leachates of living plants. Several other crops have shown such allelopathic potential including rice (Seal et al. 2004), wheat (Wu et al. 2000), sorghum (Chang et al. 1986) and black walnut (Rice, 1984). So, research is required on the isolation, identification and quantification of the allelopathic compounds in root exudates of living canola plants. Root exudates represent the largest source of allelochemical input into the rhizosphere (Jilani et al. 2008), and inputs vary with the plant species, cultivar, plant age, and stress levels (Uren, 2007). PROPOSED RESEARCH In Australia, crop allelopathy research has mainly focused on rice and wheat, however, the limited work in canola suggests that it may have strong allelopathic potential. A new PhD research study has commenced on allelopathy in canola. It will explore the allelopathic profile of a worldwide collection of 188 canola accessions, in both live tissues and crop residues; identify and quantify the responsible allelochemicals, and study the associated gene expression. It is anticipated that success may lead to reduced costs and impacts of weeds in canola cropping systems with more choice of availability of strongly-competitive cultivars. Also, the opportunity may arise to develop “natural” herbicides with new modes of action which will lead to reduced negative impacts on crop sustainability and biodiversity. ACKNOWLEDGEMENTS The senior author is very grateful to CSU for the award of an IPRS (International Post Graduate Research Scholarship), and an APA (Australian Postgraduate Award) scholarship.
REFERENCES Australian Oilseeds Federation Report (www.australianoilseeds.com). 2011. Chang, M., D. H. Netzly, L.G. Butler and D. G. Lynn, 1986: Chemical regulation of distance – st characterization of the 1 natural host germination stimulant for Striga asiatica. J. Am. Chem. Soc. 8, 7858–7860. Gimsing, A. and J. Kirkegaard, 2009: Glucosinolates and biofumigation: fate of glucosinolates and their hydrolysis products in soil. Phytochem. Reviews. 8, 299-310. Harker, K.N., G. W. Clayton, R. E. Blackshaw, J. T. O’Donovan and F.C. Stevenson, 2003: Seeding rate, herbicide timing and competitive hybrids contribute to integrated weed management in canola (Brassica napus). Can. J. Plant Sci. 83, 433-40. Holethi, P., P, Lan, D. V. Chin and H. K. Noguchi, 2008: Allelopathic potential of cucumber on barnyardgrass (Echinochloa crussgalli). Weed Bio. Man. 2, 30-39. Jilani, G., S. Mahmood, A. Chaudhry, I. Hassan, and M. Akram 2008 : Allelochemicals: sources, toxicity and microbial transformation in soil – a review. Ann. Microb. 58, 351-357. Lemerle, D., B. Verbeek, R. D. Cousens and N. Coombes, 1996: The potential for selecting wheat varities strongly competitve against weeds. Weed Res. 36, 505-513. Lemerle, D., P. Lockley, D. Luckett, and H. Wu, 2010: Canola competition for weed suppression. Seventeenth Australasian Weeds Conference, pp 60-62.
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Liu, Y., X. Chen, S. Duan, Y. Feng and M. An, 2011: Mathematical modeling of plant allelopathic hormesis based on ecological-limiting-factor models. Dose Response. 9, 117129. Moyer, J. R. and H. C. Huang, 1997: Effect of aqueous extracts of crop residues on germination and seedling growth of ten weed species. Bot. Bull. Acad. Sin. 38, 131-139. Pratley, J. B., P. Eberbach., M. Incerti, and J. Broster, 1996: Glyphosate resistance in annual th ryegrass. In: Proceedings of the 11 Annual Conference of Grassland Society of NSW, Australia. Rice, E. L.,1984: Allelopathy: Academic Press, New York. Seal, A. N., J. E. Pratley, T. Haig and M. An, 2004: Identification and quantitation of compounds in a series of sllelopathic and non-allelopathic rice root exudates. J. Chem. Ecology, 30, 1647-1662. Storrie, A., S. Sultherland and C. Preston, 2009: Canola best practice management guide for south-eastern Australia. Grain Research and Development Corporation. Canberra, Australia. Uremis, I., M. Ahmet, A. Uludag and M. Sangun, 2009: Allelopathic potentials of residues of 6 brassica species on johnsongrass (Sorghum halepense) African J. Biotech. 8, 34973501. Uren, N. C., 2007: The Rhizosphere: Biochemistry and organic substances at the soil-plant interface. CRC Press, Hoboken. Wu, H., J. Pratley, D. Lemerle and T. Haig, 2000: Laboratory screening for allelopathic potential of wheat (Triticum aestivum) accessions against annual ryegrass (Lolium rigidum). Aust. J. Agri. Res. 51, 259-266. Yasumoto, S., M. Matsuzaki, H. Hirokane and K. Okada, 2010: Glucosinolate content in rapeseed in relation to suppression of subsequent crop. Plant Prod. Sci. 13, 150-155.
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Springer Science Reviews DOI 10.1007/s40362-014-0022-2
SYSTEMATIC STUDENT REVIEW
Canola Interference for Weed Control M. Asaduzzaman • James E. Pratley • Min An • David J. Luckett • Deirdre Lemerle
Received: 23 June 2014 / Revised: 11 September 2014 / Accepted: 26 September 2014 Ó Springer International Publishing AG 2014
Abstract The increased incidence of herbicide-resistant weed species, and the related biological repercussions, poses a major threat to sustainable crop production. Integrated weed management, which involves greater reliance on non-chemical weed management tactics such as crop interference, needs to be included in canola production systems. Crop interference comprises both competition and allelopathy which favour the growth of the crop. This review examines canola plant traits associated with competitiveness and allelopathy. Competitive ability is evaluated by the ability of plant morphological traits to improve access to scarce light, nutrients and water in a limited space. Allelopathy refers to the harmful or beneficial effect of crop biochemicals on neighbouring weed species. Allelochemicals are a subset of secondary metabolites produced from intact living roots and crop residues that differ between cultivars and have specific defensive
functions in the rhizosphere. Elite allelopathic cultivars can be identified by screening canola germplasm. The identification of the allelochemicals involved and their effects in the field also need to be explored. The impact of genetic variation, the mechanisms of allelopathic action, the source and fate of allelochemicals and associated biota in the rhizosphere all need to be considered in new cultivar development. The breeding of weed-suppressive allelopathic canola cultivars needs to be in the context of good agronomic performance. Although allelopathic canola cultivars are unlikely to eliminate all weed pressures in the field, the extent to which they contribute in weed management is worthy of exploration. It remains to be known whether combined competitive and allelopathic cultivars can be developed to maximise overall interference. The integration of agronomic practises with canola interference also needs to be developed.
Endorsed by Jim Pratley.
Keywords Competition Allelopathy Root exudates Rhizosphere Metabolites
M. Asaduzzaman (&) J. E. Pratley D. Lemerle School of Agricultural and Wine Sciences, Faculty of Science, Charles Sturt University, Wagga Wagga, NSW 2650, Australia e-mail:
[email protected] M. Asaduzzaman J. E. Pratley M. An D. J. Luckett D. Lemerle Graham Centre for Agricultural Innovation (an alliance between Charles Sturt University and NSW Department of Primary Industries), Wagga Wagga, NSW 2650, Australia M. An Faculty of Science, Charles Sturt University, Wagga Wagga, NSW 2650, Australia D. J. Luckett NSW Department of Primary Industries, Wagga Wagga, NSW 2650, Australia
Introduction Canola (Brassica napus L.) is a member of Brassicaceae family with low glucosinolates and erucic acid content relative to traditional rapeseed (B. napus L.). It is a major oilseed crop, ranked as the second most important global source of vegetable oil [131]. Canola is also a potential source of specific protein and industrial raw materials including biopolymers, surfactants, adhesives and, more recently, biodiesel [170]. The annual worldwide increase in canola production has been substantial and it is predicted to exceed 15 million tonnes by 2015 [28, 29]. Australia is the world’s second largest exporter of canola seed after Canada
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and canola is Australia’s third largest broad-acre crop after wheat and barley. The Australian Oilseed Federation [5] predicts that prospects for the Australian canola industry are excellent due to good commodity prices, market demand and its value in the farming system. Canola is, therefore, an attractive alternative crop for grain growers. The rapidly growing demand for canola worldwide implies both greater yield and greater area of production, utilising better management practises and improved cultivars. Weeds commonly occur in canola crops [95] and their infestation is a major yield-reducing factor [139]. Weeds interfere with crop plants, causing serious impacts as a result of competition for either above or below-ground resources [113]. Canola is exposed to severe competition from weeds which are often considered as the most yield limiting factor in Canada [155]. In India, Gill et al. [63] reported that the magnitude of loss from weeds ranged from 30 to 50 %, depending on the growth and persistence of the weed population in the standing crop. Grass weeds, such as annual ryegrass (Lolium rigidum), vulpia (Vulpia myuros) and wild oat (Avena fatua) were most abundant in canola crop of south-eastern Australia [95]. Interference may be through severe soil nutrient depletion [173], water and shading. Weed competition also reduces grain yield and quality and market value of the canola seed. In Canada, Rose and Bell [136] showed that presence of seeds of wild mustard (Sinapis arvensis) and stinkweed (Thlaspi arvensis) in canola seeds mixtures reduced the seed quality of canola by increasing the level of erucic acid in the extracted oil and the glucosinolate content of the remaining meal. In Australia, heavy infestations of wild radish (Raphanus raphanistrum) have reduced canola yields by up to 90 % [22] and such infestations greatly reduced the quality of canola meal both through crop stress and direct seed contamination of harvested product [33, 101]. The use of herbicides and herbicide tolerant canola cultivars has increased rapidly in Australia and worldwide. However, the over reliance on herbicides can reduce their effectiveness and lead to the evolution of herbicide-resistant weeds [12]. High population densities of some weed species necessitate the input of more herbicides but the high use of herbicides exacerbates the development of the resistance problem [77, 126]. The widespread use of triazine-tolerant (TT) canola cultivars has increased the use of triazine herbicides and has led to increased triazineresistant populations of wild radish in Australia [72]. The escalating problem of herbicide-resistant weeds is a challenge to farmers as is the need to manage agrochemicals to minimise soil herbicide residues that can negatively impact on succeeding crops. Integrated weed management systems have the potential to reduce herbicide use and their associated costs where
there is greater reliance on non-chemical control tactics including enhancing crop interferences. It has been shown that the reliability of herbicide performance can be improved when combined with crop species or varieties of superior competitiveness [37, 91]. Interference is the term used to describe an induced effect by an individual plant on a neighbour through changes in the immediate environment [70]. It comprises competition and allelopathy. Zimdahl [173] reported that it is the total adverse effect that both plants exert on each other when growing in a common ecosystem. Competition is the negative interaction between two or more plant species for existence and superiority within a limited space [47]. Competition is greatest when available resources for both crop and weed are below the combined demand [47]. The phenomenon occurs between individuals of the same species (intra-species) and between individuals of different species (inter-species). Allelopathy is distinct from other negative plant interference in that the detrimental effect is through release of chemicals by a donor plant [133]. Molisch [109] indicated that this chemical interference can be both harmful and beneficial. At high concentrations allelopathic chemicals can act as inhibitors while at low concentrations they can sometimes stimulate neighbouring plant growth [110]. Weed responses to crop allelopathy have become well documented in recent decades [129, 135]. However, the impact varies depending on the plant species, cultivar, growth stage and various stress factors. In this review, we examine both forms of canola interference, competition and allelopathy, and discuss possible ways to maximise this beneficial attribute for improved weed control.
Competition Crops and weeds compete for various resources. The competitive ability of a particular plant is a major factor in suppressing the competitor. An increase in the biomass and/or population density of one species is the most likely route to increase competition for resources and thus influence the growth and survival of the affected species [154]. Competition for resources between species occurs through both above and below-ground interaction. The competitive ability of a plant is an integrated response over time, with contributions from a range of traits. Above-Ground Competition for Light and Related Canola Traits Light is an essential determinant of the energy balance of the soil and plant, and it drives water and nutrient transport [10]. Competition for light occurs in most cropping situations soon after seedling emergence [48, 131]. Plants
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intercept light using different light attributing characters and a successful plant is not necessarily the plant with more foliage but the plant with foliage in an advantageous position for light interception relative to that of its competitors [47]. Leaves are the principal source of assimilate production during the vegetative phase. In rapeseed (B. napus), the lower leaves have been shown to export assimilates basipetally, while the upper leaves exported assimilates almost exclusively acropetally [102]. They translocated and re-translocated the mobile nutrients in the plant system before they senesced [144]. Leaves of rapeseed exerted and developed source-sink capacity during the early growth stage, the expansion rate of leaves being positively correlated with seed yield [38, 153]. Thus, during early development, light interception by the rapeseed plant influences growth rate that determines competitiveness with neighbours. Plant height, leaf size, number and leaf area index are directly related to the interception of radiation by leaves. In Canada, Beckie et al. [13] indentified from field observations that canola height was as an important criterion of plant competitiveness for resources. Daugovish et al. [41] confirmed that the greater competitive ability of wild oat or yellow mustard over canola was attributed to greater plant growth rate and plant height. Other plant morphological traits such as stem elongation, upward leaf movement [21, 61, 110, 124] and leaf layer density [46] all contribute to competitiveness for light. These plant components usually relate to shade avoidance, allowing plants to photosynthesise and grow to become more competitive [11, 21, 124]. Further, the variation in morphological sensitivity of plants to light signals is known to vary among cultivars [86]. Thus, choice of a suitable shade-avoidance cultivar, combined with agronomic tactics (e.g. crop density and row arrangement), also helps to manipulate crop plant photomorphogenesis. In Australia, vigorous hybrid canolas have generally been shown to compete more successfully with, for example, annual ryegrass than did TT canola varieties [93]. The plant biomass measures of both cultivar types were negatively correlated with weed plant biomass [93]. The study was consistent with Canadian results that suitable vigorous hybrid genotypes provide more competition against weeds [68, 69, 171]. Vigorous hybrids produce tall plants with much foliage, thereby reducing light penetration to the weed canopy. Choice of vigorous cultivars can be an effective crop interference tactic for weed management especially in the early establishment phase of a canola crop. Below-Ground Competition for Nutrients and Water and Associated Canola Traits Competition for below-ground resources constitutes an important aspect of crop-weed interaction. This below-
ground interference has been reported to reduce plant performance more than do above-ground relations [165]. Below-ground competition usually occurs for space, soil nutrients and water. Plants take up soil nutrients mainly by diffusion and mass flow mechanisms from the depletion zone (the concentration gradient surrounding the roots) [118]. The competitive ability of a crop plant is likely determined by its capacity to make use of nutrients from this zone [47] and plants usually invest relatively more resources into roots compared with shoots for belowground competition [125]. Efficient nutrient acquisition by roots becomes an important key for plant competitive ability. Characteristics related to nutrient and water uptake include plant root size and depth, relative growth rate, biomass, root density and total surface area [1, 2, 31, 55]. The canola plant has an extensive root system [161] with abundant root hairs [66] to give it high root surface area and large potential to extract nutrients from the soil [66]. Strong and Soper [152] reported that roots of Brassica plants proliferate in areas of high nutrient concentration, although differences exist among genotypes in their ability for nutrient acquisition. Nitrogen uptake by canola, for example, has been linked to total root biomass rather than higher uptake per unit of length [81]. However, Laine et al. [89] demonstrated that if one half of the canola root system was starved of nitrogen, the other half was still able to supply the shoot with sufficient nitrogen through increased uptake per unit of root length. The optimisation of canola root traits for nutrient acquisition may link with its competitive ability against different weed species. The conversion of soil resources to plant biomass (referred to as nutrient use efficiency) differs between species and cultivars [31]. A typical canola plant usually has a higher demand for phosphorus and potassium than does a wheat plant [29, 137, 152]. These demands may influence success in gaining a greater share of the other nutrients to establish dominance over a less successful weed species. Duan et al. [50] reported that the rate of root biomass accumulation in canola was positively correlated with increased lateral root length [50] while, in another study, canola biomass was negatively correlated with weed biomass [92]. The biomass of canola was regulated by the reduced pH in the rhizosphere resulting from the release of organic acids by its roots [50]. In soil, insoluble phosphorus usually becomes more readily available to canola roots through the acidification of soil near the rhizosphere [2, 73, 138]. Understanding the process involved in the acquisition of soil resources, and the associated mechanisms by which canola competes, may help improve the below-ground competitive ability of canola for nutrient acquisition in the presence of weeds. Plants provide a pathway for water movement between the soil and the atmosphere. This path begins in the soil
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with water uptake and is influenced by numerous biotic and abiotic factors [31]. Plants experience competition for water when the moisture supply in the soil environment is reduced (e.g. uptake by neighbour) or is exceeded by the evaporative demand [130]. Donald [47] asserted that the success of any cereal plant for water competition depends on the rate and completeness with which it can make use of the soil water supply. This capacity for water uptake by crops is determined by several attributes within the environment such as transpiration rate and stomatal resistance capacity [31, 78] and the efficiency of water use by plant roots and leaves [75]. Poor stomatal control, for example, results in relatively high plant water use and this may increase competitiveness if the plant neighbours are water conservers [130]. In canola, it is assumed that hybrid cultivars with early vigour use available soil water more quickly, thereby making it relatively unavailable for use by neighbouring weeds. The competitive ability of a cultivar may increase in a specific location due to the environmental influence on evapotranspiration. Although the mechanisms were not clear, it has been suggested that in cool environments hybrid canola induces non-favorable conditions for weed growth by reducing soil resources [68]. Essential nutrients, once inside the canola plant, can be relocated to support growth and, advantageously, they are, therefore, not available to neighbouring weed species. Plant avoidance and tolerance mechanisms to soil water stress are related to its root morphology and distribution. Pavlychenko and Harrington [122] found that the considerable depth of the root systems of wheat provided good adaption for drought tolerance and weed competition. Likewise in canola, a deep root system is likely a key trait of the plant’s ability to access sufficient water. Canola roots have been shown to extract water from a depth of 150 cm although up to 95 % of the total seasonal uptake was removed from the top 105 cm of the soil profile [114]. Thus, cultivars with a deep root system trait may become more competitive by being able to adjust their avoidance or tolerance of soil water stress. Roots of canola and other Brassica species, however, are poorly adapted to dry regions and so agronomic adjustment of these early-seeding or early-maturing cultivars may be needed to improve tolerance to competition through better water use efficiency during the seed filling stage. In Western Australia, the early sowing and early flowering cultivars of B. napus produced the greatest total dry weight and seed yield due to efficient water use compared with a late sowing [153]. Early flowering cultivars also showed better competitive ability in Canada because they proliferated their root systems as soon as they sensed a water source, enabling them to fully utilise those resources [32]. These data demonstrate key aspects of canola roots in competitive interference: tolerance of water
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stress without changes in physiological adaption; and canola root architecture and cellular mechanisms. Selecting a Competitive Canola Ideotype The crop ideotype consists of morphological and physiological traits which contribute to enhanced yield relative to currently prevalent crop cultivars. Such a plant will make minimum demand on resources per unit of dry matter production [48]. The design of crop ideotypes, however, may likely involve modifications related to the environment. An evaluation of the competitive ability of different cereal crops, such as rice, wheat and barley, clearly showed that no one ideotype was appropriate for every environment [168]. Different combinations of plant traits could confer the best competitive advantage depending on growing season, climatic conditions and competitiveness with weed species as well as the timing of the competition [168]. Olofsdotter et al. [119] reported that the best competitive plants also have good biotic and abiotic stress resistance. Little consideration has been given to the inclusion of specific plant traits for strong competiveness with weeds to enhance yield stability. Understanding which traits are most strongly associated with competitive advantage of canola is important for developing new cultivars and should include allelopathy in the development of a canola ideotype.
Allelopathy The term allelopathy originated from the Greek word ‘‘allelon’’ meaning each other and ‘‘pathos’’ meaning suffering and was first introduced by Austrian plant physiologist Molisch [109]. The word ‘‘pathos’’ also means ‘‘feeling’’ or ‘‘sensitive’’ and could, therefore, be used to describe both positive (sympathetic) and negative (pathetic) interactions [65]. The concept of allelopathy received further attention by Rice [132]. He defined allelopathy as an important mechanism of plant interference mediated by the addition of plant-produced secondary products into the rhizosphere [133]. The organic secondary products involved in inhibitory or stimulatory effects are referred to as allelochemicals and these can be released through volatilisation, leaching from plant leaves, residue decomposition and active root exudation [36, 133]. Chemicals with allelopathic potential are present in nearly all plants and their respective tissues [164]. Under the appropriate environmental conditions, these phytotoxic compounds may be released into the environment in sufficient quantities to affect the growth of neighbouring plants [163]. Allelopathy is a significant component of crop/weed interference and, therefore, a potential weed
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management tool [15, 82, 117]. Allelopathy includes the use of phytotoxic chemicals released from crop residues as well as from intact roots of living plants [163, 164].
release occurs only during decomposition, and it is worthy of further investigation.
Allelopathy of Canola Residues
Biofumigation
Crop allelopathy evidence initially came from studies of the use of organic mulches and cover crops to suppress weed emergence. The presence of growth inhibiting substances in plant residues was reported by Collinson [39]. The decomposition products of residues can exert effects on weed germination and establishment [14, 107, 127, 128, 163] either taken up by the recipient singly, additively or synergistically [54], adsorbed onto soil colloids [40], modified or reduced or biochemically modified (including non-toxic chemicals into toxic chemicals) by soil organisms [58, 147]. These inhibitory allelopathic effects of residues of both native and cultivated Brassica spp and their relatives have been reported for weed suppression. Boydston and Hang [24] reported that residues of soil-incorporated foliage of canola suppressed plant populations of common lambsquarters (Chenopodium album), redroot pigweed (Amaranthus retroflexus), barnyard grass (Echinochloa. crus-galli), hairy nightshade (Solanum sarrachoides) and longspine sandbur (Cenchrus longispinus [Hack.] Fern.) [24]. In Australia, Jones et al. [80] reported that residues of barley, wheat and canola showed adverse effects on the survivability, growth and dry matter production of paradox grass (Phalaris paradoxa), wild oat (A. fatua) and turnip weed (Rapistrum rugosum). Several subsequent weed suppression studies showed that Brassica cover crops, such as rapeseed and mustard, have high potential to be used in an alternative weed management system. The researchers concluded that an allelopathic mechanism was involved [3, 24, 25, 85, 158]. Tissue damage and then hydrolysis of the Brassica plants released glucosinolate breakdown products, including isothiocyanates, oxazolidinethiones, ionic thiocyanate (SCN-) and organic cyanides [25, 67]. Most breakdown products of glucosinolates are volatile, whereas hydroxamic acids are water-soluble. In the soil, hydroxamic acids can be transformed into more toxic compounds by neighbouring weed species [59, 62]. Although the specific modes of action of these compounds on target weed species have not been thoroughly investigated, most compounds showed inhibitory effects on other species through reduced and delayed germination or inhibition of seedling emergence [115, 116]. The level and the time course of allelochemical release and of other residue-mediated alterations in the soil are largely dependent on the amount and decomposability of the residue, on soil biological, chemical and physical characteristics [34, 96] or on residue management practises [88]. It is unclear whether canola living roots release these compounds in exudation or whether
Biofumigation is defined as the use of biocidal compounds, primarily isothiocyanates, used as commercial fumigants, or released by Brassicaceous plants used as green manure or rotation crops, for suppression of soil-borne pests and pathogen [4, 83]. Such compounds have relatively high vapour pressure and are thoroughly dispersed throughout the surrounding soil where they may affect soil-borne fungi, pathogen, insects and nematodes [111]. This finding has led to an increased interest in the development of biofumigation strategies, where naturally formed isothiocyanates could be used as a control measures. Incorporation of Brassicaceous plants in order to control pathogens and nematodes has proven to be effective in several studies [108, 112]. The use of canola as a break crop to help control take-all fungus (Gaeumannomyces graminis) in cereal rotations in Australia is also an example of this biofumigation effect. However, the inconsistent results in biofumigation studies (reviewed by Matthiessen and Kirkegaard) [103] implied that other factors were involved. The profile of isothiocyanate production varies between Brassica species [84, 142, 143, 149, 159], between individuals of the same genotype [53, 84], and even within different plant tissues of a single individual [57, 104]. Furthermore, it needs to be considered that there are beneficial organisms including biocontrol agents, that are also affected by glucosinolate breakdown products and their presence may have consequences for pest control in an integrated pest management (IPM) agro-ecosystem. The existence of the biofumigation capability, however, is demonstrative of the potential of root exudation for crop management. Their role for weed control remains to be evaluated fully. Canola Allelopathy by Intact Roots of Living Plants Weed suppression via living plant exudation is considered a promising approach to exploit allelopathy in annual crops [7, 51, 52, 134]. Belz [15, 16] claimed that weed suppression by crop plant root exudation is a valuable mechanism if this trait can be exploited in much the same way as defence mechanisms against insects or pathogens. The approach has already been reviewed for major grain crops including rice [45, 145], wheat [17, 169] and barley [17, 18, 97]. Those reviews showed that the allelopathic ability of a crop plant to defend itself against weeds was possible and there was considerable genetic variability to exploit such mechanism among cultivars. The family Brassicaceae
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is often reported as having allelopathic properties that can affect establishment and growth of other species by root exudation [14, 98, 156]. An intercropping study between wild mustard and broccoli demonstrated that broccoli yield was reduced by 50 % due to the phytotoxic effect of plant exudation from wild mustard [79]. In the USA, cultivated or naturally occurring mustards often formed relatively pure stands when well established and, in the wild, they can be successful invaders of native grasslands [14, 163]. In Turkey, Uremis et al. [156] found that root exudates of the rapeseed cultivar Westar influenced the root growth of redroot pigweed (A. retroflexus L.), black nightshade (Solanum nigrum L.), common purslane (Portulaca oleracea L.), cutleaf ground cherry (Physalis angulata L.) and jungle rice (Echinochloa colonum) more than shoot growth, whereas other cultivars Jumbuck, Tobin, Lisoune and Galant showed less allelopathic activity through their root-secreted chemicals. This suggests that canola plants are also likely to show allelopathy through root exudation and raises the prospects of creating elite allelopathic canola genotypes with improved weed-suppressive capability.
glucosinolates [26, 85, 90, 115, 116, 119, 121, 166]. These sulphur-containing compounds are indole derivatives at the C-3 position of the indole ring [44, 123]. Phenylpropanoids have a wide variety of functions including defence against microbial attack and other sources of injury [74]. Glucosinolates provide pathogenic organism defence [106] and can accumulate and modify to yield a variety of products including isothiocyanates, thiocyanates and nitriles but this depends on the nature of glucosinolates and the stress imposed [35, 105]. Choesin and Boerner [35] measured the direct release of isothiocyanate from growing the root of B. napus but they did not evaluate its effect on weed species. Research is needed to clarify the type of chemicals released by intact canola roots and their role in weed inhibition. Such findings would facilitate investigation of the biochemistry and metabolomic pathways of these chemicals in plants in respect of canola allelopathy. It would also provide opportunities for new weed controlling cultivars.
Root Exudates and Rhizosphere Communication Canola Root Exudates and Phyto-Chemistry Plant living root hairs and actively growing primary and secondary roots typically release large quantities of secondary metabolites (known as root exudates) [19]. This phenomenon has long been regarded as a passive process of secreted photosynthetically fixed carbon into the soil [9]. Root exudates or secondary metabolites represent one of the largest direct inputs of plant chemicals into the rhizosphere and almost certainly root exudates comprise the major sources of allelochemicals [19]. Stressed plants secrete particular secondary metabolites for their defensive activity [6, 162]. For example, Arabidopsis thaliana (Brassicaceae) secretes a large number of defence metabolites when grown alone [6]. However, once a plant neighbour is identified, the repertoire of metabolites is reduced but overall their secretion increases significantly [6]. In addition to the role in plant defence, some metabolites have physiological functions by serving as mobile and toxic nitrogen transport and storage compounds [166, 167]. However, these multiple functions do not compromise the main role of secondary metabolites as chemical defence and signalling compounds [166]. Exuded compounds are highly species-specific. They move safely into the environment through a variety of plant sequestration (e.g. sub-cellular vesicles) and transport mechanisms (e.g. protein embedded) [9, 19, 162]. Allelopathy in Brassica spp. appears to be associated with the presence of several groups of exudated metabolites such as phenylpropanoid, flavonoids, isothiocyanates and
The rhizosphere is the narrow region of soil directly influenced by root secretions and associated soil biota [19, 157]. In this zone, plant root-secreted chemicals can influence several processes such as resources (e.g. soil nutrients) and non-resource plant-mediated interaction [133], microbial communities and their populations [9] and neighbouring plant species [147]. These influences may play an important role in communication between other plants in the rhizosphere [160].
Root-Microbes Communication Survival of a plant species in a particular rhizosphere depends on the mechanisms of adaption to interaction with biotic and abiotic components. The root rhizosphere is considered the place that provides habitat for plant roots and microorganisms and is inhabited by a wide range of microorganisms, including bacteria, fungi, algae, viruses and protozoa. These microbes may have a profound effect on allelopathic activity by altering and/or transforming the amount of allelochemicals [153]. On the other hand, allelochemicals may also influence the microbial community [71, 87] and these mechanisms can involve both stimulation (by providing nutrient sources) and inhibition (by interfering with nutrients) [124]. Various soil-borne organisms are highly sensitive to the Brassica plantsecreted 2-phenylethyl isothiocyanate, with bacteria being more tolerant than eukaryotic organisms [150]. In contrast,
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growth of ectomycorrhizal fungi was found to be stimulated by root exudates of various Brassica spp. [172]. Rumberger and Marschner [140, 141] reported that canola roots released sufficient amounts of 2-phenylethyl isothiocyanate into the soil rhizosphere to have a selective effect on the bacterial community. Bacterial community composition was significantly correlated with phenylethyl isothiocyanate concentration and moreover changed with plant growth stage [140, 141]. However, despite high residence time of this chemical, Choesin and Boerner [35] found in their study that this root secretion did not have an inhibitory effect on Medicago sativa L. This suggests that specific signals might be exchanged between Brassica plants and microorganisms, although this is not yet clear. It would be also interesting to know whether the possible allelopathic chemicals described for canola roots act directly against the neighbouring plants or indirectly through modifications by soil microorganisms. Root-Root Communication Crop plant roots are continually interacting with roots of neighbouring plant species; and are capable of detecting and responding in multiple ways [20, 42, 56, 99, 148]. Roots may communicate with other roots with the help of various secondary metabolites, which are secreted into the rhizosphere in response to biotic and abiotic stresses. Several research studies suggest that such a response of roots to their neighbours is not only explained by nutrients but also involves non-nutrient causes [8, 9]. Cahill and McNickle [27] divided these apparent non-nutrient root responses into three classes: (a) segregation (root growth away from neighbours), (b) neutral (no specific directionality of root growth) and (c) aggregation (root growth towards neighbouring roots). The actual sensing of the neighbour presence might be based on either physical touching of roots [100] or without physical touching via chemicals signals released by roots [6, 76]. For chemical signals, secondary metabolites have been largely credited with being involved in plant–plant interaction on the assumption that these compounds tend to be phytotoxic and persist in the soil [6]. Of course, such compounds could be hormonal or pseudo-hormonal in their influence on nonsame neighbours. Pierik et al. [124] reported that the high specificity of root exudates has the potential to transport such specific signals into the rhizosphere. It has been reported that the proteins in the root exudates are secreted differently depending upon the presence and identity of the neighbouring root [6, 43]. Such canola-neighbour root interactions have not been elucidated. Establishing these interactive mechanisms by canola exudates will elucidate the true complexity of the competitive arena (Fig. 1).
Fig. 1 Canola-weed below-ground interactions (resources and nonresources based) involve various signals, such as variations in nutrient concentrations, soluble root exudates and the activities of soil microbes
Conclusions Herbicide-resistant weeds can increase the cost of canola production and reduce yields. Weeds may become a greater economic issue, if non-chemical weed management tactics are ignored. To maintain a sustainable production system and effectively manage the weed burden, an integrated weed management program incorporating crop interference needs to be included in the canola crop production system. The implementation of a high interference strategy for canola in the field requires a fuller understanding of canola competition and allelopathy on weeds. This includes a greater knowledge of the response of plants to their environment and to the stresses created by neighbouring weeds. Such elucidation will help to understand which traits matter under which conditions. Understanding the regulatory mechanisms that enable an individual canola plant to optimise these traits is a key to understanding canola-weed competition. The need for further experimentation to estimate accurately the relative ranking of current canola varieties for competitive ability at regional level is desirable. Evidence thus far suggests that some varieties are consistently more competitive than others, but considerable environmental variation exists, making reliable recommendations for farmers difficult. Growing vigorous crops by the many means possible is the challenge [94]. Changing farming practises, such as the move from conventional cultivation to reduced tillage and stubble retention systems, may influence weed growth and population dynamics [30]. More research is needed to determine the
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impact of variety competitive ability on weed seed production for population dynamics modelling, particularly with respect to closely related weed species such as wild radish and wild mustard, to assist in predicting the longterm benefits of integrated weed management in a canola production system. Communication between canola shoots and the roots is also important to ensure the shoot is adequately receiving below-ground resources for enhancing above-ground competition. Potential already seems to exist for breeding enhanced canola competitive ability through greater early vigour and below-ground root characteristics. Competitiveness of canola can be increased by breeding for suitable plant traits and by manipulation of the management system but the benefits and costs of crop competitive ability need to be evaluated. The competitive ability of a specific genotype in a particular environment may be much lower in another environment. Increasingly, studies reveal that non-resources crop interference such as allelopathy plays an important role in some crop species. This opens the possibility to explore and utilise canola allelopathy. Below-ground plant–plant competition is more complex than above-ground and interdisciplinary research is needed to enable thorough understanding of canola allelopathy. The role of chemical signals between canola and other organism in the rhizosphere needs further study. The same chemical signal may deter one organism while attracting another [7]. Plants rarely secrete just one substance and so there may be a blend of potential signals from molecules which are highly selective [49, 124]. In addition, ecological knowledge indicates that below-ground interactions could potentially be transformed to above-ground responses in plants. Integration of the different technology platforms are needed to understand the complex network of canola plant responses to various external factors including regulation via various signalling pathways. In order to evaluate to what extent canola contributes in the crop-weed interference mechanism, the first task is to evaluate the existence of genetic variation of allelopathy in canola under laboratory conditions. Crop laboratory bioassays can demonstrate the potential chemical interference among crop cultivars within a limited time frame. Interestingly, much effort has been put into the development of sound screening protocols and most existing screening techniques are reliable, fast, cheap and space limited. Laboratory bioassays are also suitable for understanding different aspects of allelopathy (e.g. release of chemicals from the donor plant, fate and persistence in soil, growth and uptake of allelochemicals) [23, 60] but it is also important to know the fate of these chemical compounds in the soil and their interaction with abiotic and biotic influences. The outcomes of this research should address the
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sources of variation in allelopathy between cultivars. The bioactivity of the chemicals released by intact roots, however, may be compromised by an allelopathic species and could be rendered unavailable by the combined interactions of soil texture, organic matter, temperature and soil microbes [9, 64, 151]. The exudation of these compounds will determine the allelopathic effect. In the field, allelopathic effects are difficult to measure [120] and dependence on parallel in vitro experiments is required. Seal et al. [146] found that laboratory screened allelopathic rice cultivars performed well in the field and proved to be active against multiple weed species. More recently, field testing has been expanded from rice to wheat and barley. Discovery of the allelochemicals involved in interference is essential by both traditional and advanced metabolomics methods (with HPLC, IR, GC/LC MS-QTOF and NMR etc.). Metabolomics is an important tool for an unbiased view of metabolites with combined principal components analysis. If canola cultivars produce and release sufficient amounts of herbicidal compounds, then the biochemistry of the exudation process needs to be understood. Study of the genetic control of the allelopathic traits is important for the development of competitive canola varieties. In a study of allelopathic activity of population of 400 F2 rice plants on duck salad (Heteranthera limosa), Dilday et al. [45] found that rice allelopathic activity was normally distributed, suggesting that the rice allelopathic trait was quantitatively inherited. The genetic study of allelopathy is still in its infancy but it does represent a promising new frontier for future research. Modern methodologies in molecular genetics and biochemistry have made this type of research more rapid and more direct than in the past. To develop high-yielding commercial canola cultivars with elevated allelopathic activity without sacrificing other agronomic traits, breeders’ time and resources should be allocated after confirmation of significant crop allelopathic performance in the field. Allelopathy alone is unlikely to control all weeds but its enhancement will be a potential contributor for a sustainable integrated weed management system. Acknowledgments The senior author is grateful to Charles Sturt University, Australia for the award of an International Post Graduate Research Scholarship, an Australian Postgraduate Award research scholarship and the prestigious Writing up Award. He is indebted to the Department of Agronomy of Sher-e-Bangla Agricultural University, Dhaka, Bangladesh for allowing him study leave to do his PhD study at Charles Sturt University Wagga Wagga, NSW Australia.
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Chapter 3 Research Findings in the Laboratory As an initial step, this chapter evaluated canola stubble extract phytotoxicity on the germinating seeds of canola and annual ryegrass. This provided experience in experimental methodology and validity of literature reports.
Key contents
Stubble extracts
Laboratory bioassay
Inter-cultivar toxicity
Intra-cultivar toxicity
Inter-specific toxicity
Concentrations 75%, 50% , 25% and 0% (control)
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Phytotoxic effects of canola (Brassica napus) stubble on germination and seedling establishment of canola and annual ryegrass (Lolium rigidum L)
Introduction The phytotoxic effects of water extract from crop stubble have been reported by many researchers. Crop stubble toxicity has generally been tested by the germination and growth responses of the receiver species. Residues of many crop species including wheat (Kimber, 1973; Wu et al., 2003), barley and lentils (Cochran et al., 1977), oats, corn and sorghum (Guenzi et al., 1967) and lupins and field-peas (Lovett & Jessop, 1982) were phytotoxic to receiver growth and seedling establishment. The toxicity of donor stubble extract has also been shown to vary between species and between cultivars of the same species (Siemens et al., 2002; Agarwal, 2004). The stubble extracts of Brassica crops have also showed phytotoxicity to various receiver species. For example, water extracts of black mustard (Brassica nigra L.) inhibited seed germination and seedling growth of wild oat (Avena fatua) and wild radish (Raphanus raphanistrum) (Turk & Tawaha, 2002; 2003, Turk et al., 2003; Turk et al., 2005). Residue extracts of rapeseed inhibited the growth of maize (Zea mays) (Zaji & Majd, 2011), soybean (Oskoeui et al., 2012) and different weeds (Uremis et al., 2009). In a series of papers on the phytotoxic effects of the Brassica genus, Mason-Sedun and colleagues (Mason-Sedun et al., 1986; Mason-Sedun & Jessop, 1988) reported that water leachates of stubbles from Brassica genera all inhibited the growth of wheat in the laboratory. Canola (Brassica napus) is an 37
important break crop in Australia and stubble retention practices mean that crop residues are left in the field after harvest and available for leaching to occur. Annual ryegrass (Loliunm rigidum L.) is an important grass weed of winter crops in southern Australia. Surveys found annual ryegrass in 86% of canola crops (Lemerle et al., 1999). Differential competitive abilities against L. rigidum were detected in both hybrid and triazine-tolerant genotypes of canola (Lemerle et al., 2010), causing variation in weed biomass. The corresponding canola biomass was negatively correlated with weed biomass (Lemerle et al., 2010). Chemical options for ryegrass control have become more limited recently, because of the development of multiple and/or cross resistance of L. rigidum to herbicides (Powles & Howat, 1990; Powles et al., 1996; Pratley et al., 1996). Furthermore, the use of herbicide tolerant crop cultivars has only provided a short respite. In fact, the concentrated use of single herbicide or single modes-of-action has increased selection pressure and hastened the development of herbicide-resistant weed species such as wild radish (Raphanus raphanistrum) (Heap, 2013). In this study canola stubble aqueous extract was applied to canola and annual ryegrass germinated seeds under laboratory conditions to evaluate the inter-specific (on annual ryegrass), inter-cultivar (on different canola cultivars) and intra-cultivar (on same canola cultivar) toxicity.
Materials and methods Collection and preparation of extracts Four canola genotypes (Ag-spectrum, Sardi607, Charlton and Zhonshu-angNo4) were chosen from a canola field experiment conducted by NSW Department of 38
Primary Industry, Wagga Wagga in 2011. After mechanical harvest of the canola grain, the canola stubble was manually collected on 18 January, 2012 from each plot (9 m X 1.5 m). Stubble consisted only of stems and branches; leaves and pods and roots were not included. Canola stubble was oven-dried at 65 0C for 48 hours and samples were then ground to a fine powder. Ten g of powder from each canola genotype was extracted with 100 mL of warm distilled water (40 0C) in a glass jar for 24 hours at 27 0C. The water extract was filtered through a cheese cloth and the resulting filtrate was centrifuged at 13,000 rpm for 12 min at 8 0C. The supernatant was then vacuum filtered through one layer of filter paper (Whatman, 0.25 µm). The collected solution was designated as full strength (100%) and used for the betweencultivar and within-cultivars bioassay. For the annual ryegrass bioassay, the stock solution was diluted into four different concentrations viz. 0% (control), 25%, 50%, and 75%.
Bioassay of intra-cultivar and intra-cultivar phytotoxicity The four canola genotypes were used as both donors and receivers. Ten seeds of each of the receivers were sown onto 9 cm petri dishes lined with one layer of Whatman No.1 filter paper. Four millilitre of each extract from one of the four donor genotypes were used to irrigate each petri dish, and distilled water (4 mL) was used as the control. To reduce evaporation, each petri dish was sealed tightly with parafilm. All dishes were maintained in a growth chamber (light/dark 12/12 h and 20 0
C/18 0C) and arranged in a randomized complete block design with 3 replications.
The numbers of germinated seeds were counted every 24 hrs for 3 days (until no further seeds germinated). The speed of germination (S) of each receiver genotype
39
was calculated by the following equation as described by Einhellig et al. (1982) and Khandakar & Bradbeer (1983).
S=
where
,
,
...
is the proportion of seeds which germinated on day 1, 2,
3...n. A seeds was regarded as germinated if it had >1 mm of visible root and shoot length. Root and shoot length (mm) was measured after 6 days of incubation.
Bioassay of intra-specific phytotoxicity Ten seeds of ryegrass were sown into a 9 cm petri dishes lined with one layer of Whatman No. 1 filter paper. 4 mL of each stubble extract was used to irrigate each petri dish. To reduce evaporation, each petri dish was covered tightly with parafilm. All dishes were maintained in a growth chamber (light/dark 12/12 h and 20 0
C/18 0C) and arranged in a randomized complete block design with 3 replications.
The root length of the annual ryegrass seedling was measured after 7days incubation.
Statistical analysis The percentage inhibition of receiver root and shoot length was calculated compared with the control (data with donor/control x 100). All data were subjected to an analysis of variance (ANOVA) using GenStat version 16. The treatment means were tested separately with the least significant difference (l.s.d.) at a 5% level of probability. The residuals from the ANOVA were examined graphically to ensure they met the assumptions of the analysis: normality and homogeneity of variance.
40
Results Bioassay of intra-cultivar and intra-cultivar phytotoxicity There were significant differences (P<0.001) between genotypes in terms of their speed of germination, and the root and the shoot growth when exposed of different donor extracts. Charlton had the least inter-cultivar inhibitor effect on the germination of Sardi607, and interfered the most with the germination of Zhonshuang-No4 (Table 1). Overall, the germination processes of all receivers were reduced by Zhonshu-ang-No4 and Sardi607. Root and shoot growth was inhibited to varying degrees (Figure 1). Ag-spectrum and Charlton stimulated the shoot growth of Sardi607. On average, extracts from Zhonshu-ang-No4 and Sardi607 showed more toxicity than the other two genotypes. In addition, the receiver genotypes responded differentially to the donor extracts, with Zhonshu-ang-No4 and Ag-spectrum being more sensitive than Sardi607 and Charlton. The four canola genotypes Zhonshu-ang-No4, Sardi607, Charlton and Agspectrum exhibited different intra-cultivar (autotoxic) effects (Figure 2). The autotoxic effects on root growth were ranked in increasing order: Ag-Spectrum (80%) < Sardi607 (81%) < Charlton (83%) < Zhonshu-ang-No4 (93%). Aqueous extracts each of the donor genotypes Ag-Spectrum, Sardi607, Charlton, and Zhonshu-ang-No4 were also autotoxic to the shoot growth of the respective genotype at 10 %, 0 %, 44% and 43 % respectively. The results showed that the intra-cultivar autotoxic of Zhonshu-ang-No4 and Charlton was more pronounced followed by Sardi607 and Ag-spectrum.
41
Table 1 The speed of germination of receiver seeds when exposed to the aqueous extracts of donor canola genotypes Donor
Receiver
Speed of germination (%)*
Charlton
Charlton
76
Zhonshu-ang-No4
45
Sardi607
94
Ag-spectrum
88
Zhonshu-ang-No4
51
Sardi607
60
Ag-spectrum
48
Charlton
62
Sardi607
70
Ag-spectrum
70
Charlton
75
Zhonshu-ang-No4
50
Ag-spectrum
73
Charlton
71
Zhonshu-ang-No4
49
Sardi607
77
Zhonshu-ang-No4
Sardi607
Ag-spectrum
LSD (P = 0.05)
6.5
*Low value of speed germination indicating more inhibitory effects from respective treatment or vice versa. Bioassay of inter-specific phytotoxicity The germination process of ryegrass was not completely inhibited by any extract concentration of the four canola genotypes. The phytotoxic activity of canola residues varied between genotypes (P<0.001) and concentrations (P<0.001). Canola stubble extract inhibited the root growth of annual ryegrass in the range 12%-62% depending on genotype and extract concentration (Figure 3). Charlton was the most phytotoxic genotype while Ag-spectrum was the least phytotoxic. 42
Figure 1 Reduction in the root and the shoot length of receiver canola seedlings when exposed to the aqueous extracts of donor canola genotypes Charlton, Sardi607, Ag-spectrum and Zhonshu-ang-No4. Bars represent standard error of the mean. Key: root (■) and shoot ( ).
43
Figure 2 Growth inhibitions (% of control) of canola seedlings when exposed to the aqueous extract of the same genotype. Bars represent standard error of the mean. Key: root (■) and shoot ( )
Figure 3 Percent inhibition in ryegrass seedling root length (mm) when grown in the presence of different concentrations of aqueous extract made from field-grown stubble from different canola genotypes. 44
Discussion In this study, different inter-cultivar and intra-cultivar toxicities were observed among four canola genotypes. Autotoxicity is mainly of academic interest; however, the situation could occur in field if farmers are growing back-to-back canola (which is a severe risk to their crop rotation). It is a bonus if crop stubble suppresses weeds but not if it suppresses the next crop. Canola residue phytotoxicity causing inhibition of the root length of ryegrass seedlings varied between genotypes and extract concentration. Uremis et al. (2009) detected differential phytotoxicity of residue extracts of rapeseed in both laboratory and field conditions against Johnsongrass (Sorghum halepense). In Australia, Jones et al. (1999) reported that residue extracts of barley, wheat and canola showed adverse effects on the survivability, growth and dry matter production of paradox grass (Phalaris paradoxa), wild oat (Avena fatua) and turnip weed (Rapistrum rugosum). The cultivar Charlton (tested here) would be a good choice if ryegrass was a problem in that particular paddock, since suppression could be maximised from the stubbles. Of course, the extracts used here were from stubble collected immediately post harvest. In the farming situations, stubble will be in the field for at least 3, and possible 6, months before the subsequent crop is sown. That allows plenty of time for stubble leaching and breakdown which is likely to reduce toxicity, depending on the weather condition. In additions, stubble may be grazed by stock or cultivated also influencing its toxicity. The phytotoxicity was found to be correlated with the concentration of extracts. It may be concluded that increased stubble load (t ha-1) will likely result in higher residue and greater phytotoxic effect. Care is required to manage any negative 45
chemical and physical impacts of canola residues on the following crop. In general, stubble genotype and quantity will likely determine the allelopathic potential of canola. Previously Al-Khatib et al. (1997) reported that increasing the stubble load of rapeseed decreased the seedling emergence of common chickweed (Stellaria media). In this study different potential inter-specific, inter-cultivar and intra-cultivar toxicity was observed in a small set of canola genotypes. Extract bioassays may have little relevance to field settings. The process involved in the prepartion of aqueous extracts could result in the release of certain enzymes, salts, amino acids and nitrogen compounds which may not be released under natural circumstances (Chou & Muller, 1972). Stubble toxicity is largely a passive process, whereas establishing the cause and effect relationship of allelopathy needs a demonstration of the production of allelochemicals by the living host (donor) plant, their transport from the host plant to the affected receiver plants (weeds) (Einhellig, 1995; Khalid et al., 2002). It is, therefore, imperative to do bioassays where it can be shown that cropsecreted chemicals are affecting on the target species. Any suggestions of allelopathy based on laboratory results must be supported by observations under field conditions. Furthermore, this preliminary experiment was done to evaluate the findings of the literature and to provide a basis for the study of root exudates.
References Agrawal, A. A. (2004). Resistance and susceptibility of milkweed: competition, root herbivory, and plant genetic variation. Ecology, 85, 2118–2133. Al-Khatib, K., Libbey, C., & Botdston, R. (1997). Weed suppression with Brassica green manure crops in green pea. Weed Science, 45, 439-445.
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Chou, C. H., & Muller, C. H. (1972). Alleloapthic mechanisms of Arctoaphylos glandulosa var. zacaensis. Naturalist, 88, 223-227. Cochran, V. L., Elliot, L. F., & Papendick, R . I. (1977). The production of phytotoxins from the surface crop residues. Soil Science Society of American Journal, 41, 903-908.it Einhellig, F. A., Schon, M. K., & Rammussen, J. A. (1982). Synergistic effects of four cinamic acid compounds on grain sorghum. Journal of Plant Growth Regulators, 1, 251-258. Einhellig, F. A. (1995). Characterizing of the mechanism allelopathy. In: Chen, H. H., Inderjit, & Dakshini, K. M. M., eds. Allelopathy, organisms, process and applications. American Chemical Society, Washington, pp. 132-141. Gunezi, W. D., McCalla, T . M., & Norstate, F. A. (1967). Presence and persistence of phytotoxic substances in wheat, oat, corn and sorghum residues. Agronomy Journal, 59, 163-165. Heap,
I. (2013).The international survey of herbicide www.weedscience. org. Accessed 2 October 2013.
resistant
weeds.
Jones, E., Jessop, R., Sindal, B., & Hoult, A. (1999). Utilising crop residues to control weeds. Proceedings 12th Australian Weeds Conferecne, Devonport, Australia, pp. 373-376. Kimber, R. W. L. (1973). Phytotoxicity from plant residues III. The relative effects of toxins and nitrogen immobilisation on the germination and growth of wheat. Plant and Soil, 38, 543-555. Khalid, S., Ahmed, T., & Shad, R. A. (2002). Use of allelopathy in agriculture. Asian Journal of Plant Science, 1(3), 292-293. Khandakar, A. L. & Bradbeer, J. W. (1983). Jute seed quality. Bangladesh Agricultural Research Council, Dhaka. Lemerle, D., Blackshaw, R., Potter, T., Marcroft, S., & Barrett- Lennard, R. (1999). Incidence of weeds in canola crops across southern Australia, Proceedings 10th International Rapeseed Congress, Canberra, Australia. Lemerle, D., Lockley, D., Luckett, D., & Wu, H. (2010). Canola competition for weed suppression. Proceedings 17th Australasian Weeds Conference, Christchurch, New Zealand, pp. 60-62.
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Lovett, J. V., & Jessop, R. S. (1982). Effects of residues of crop plants in the germination and early growth of wheat. Australian Journal of Agricultural Research, 33, 909-916. Mason-Sedun, W., Jessop, R. S., & Lovett, J. (1986). Differential phytotoxicity among species and cultivars of the genus Brassica to wheat. I: Laboratory and field screening of species. Plant and Soil, 93, 3-16. Mason-Sedun, W., & Jessop, R. S. (1988). Differential phytotoxicity among species of the genus Brassica to wheat II. Activity and persistence of water- soluble phytotoxic from resiudes of the genus Brassica plant. Plant and Soil, 101, 69-80. Oskouei, B., Divsalar, M., Abbasian, A., Yari, L., Sheidaei, S., & Sadeghi, H. (2012). Allelopathic effects of rapeseed on soybean germination indices. International Journal of Agricultural Science, 2(10), 957-963. Powles, S. B., & Howat, P. D. (1990). Herbicide resistance in Australia. Weed Technology, 4, 178-185. Powles, S. B., Preston, C., Brain, I. B., & Justum, A. R. (1996). Herbicide resistance: impact and management. Advances in Agronomy, 58, 1-28. Pratley, J. E., Baines, P., Eberbach, P., Incerti, M., & Broster, J. (1996). Glyphosate resistance in annual ryegrass. Proceedings 11th Annual Conference of Grassland Society of NSW, Wagga Wagga, Australia, p.122. Siemens, D. H., Garner, S. H., Mitchell-Olds, T., & Callaway, R. M. (2002). Cost of defence in the context of plant competition: Brassica rapa may grow and defend. Ecology, 83, 505-517. Tawaha, A. M., Turk, M. A., & Lee, K. D. (2005). Inhibitory effects of aqueous extracts of black mustard on germination and growth of radish. International Journal of Biological Science, 1, 227-231. Turk, M. A., & Tawaha, A. M. (2002). Inhibitory effects of aqueous extracts of black mustard on germination and growth of lentil. Pakistan Journal of Agronomy, 1, 28-30. Turk, M. A., & Tawaha, A. M. (2003). Allelopathic effect of black mustard (Brassica nigra L.) on germination and growth of wild oat. Crop Protection, 22, 673-677. Uremis, I., Arslan, M., Uludag, A., & Sangun, M. K. (2009). Allelopathic potentials of residues of 6 brassica species on johnsongrass [Sorghum halepense (L.) Pers.]. African Journal of Biotechnology, 8 (15), 3497-3501. 48
Wu, H., Pratley, J., & Haig, T. (2003) Phytotoxic effects of wheat extracts on a herbicide-resistant biotype of annual ryegrass (Lolium rigidum). Journal of Agricultural Food Chemistry, 51, 4610– 4616. Zaji, B., & Majd, A. (2011). Allelopathic potential of canola (Brassica napus L.) residues on weed suppression and yield response of maize (Zea mays L.). Proceedings International Conference on Chemical, Ecology and Environmental Sciences (ICCEES'2011), Pattaya, pp. 457-460.
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Chapter 4 Optimisation of Laboratory Bioassay This chapter reports an evaluation of the Equal Compartment Agar Method (Wu et al., 2000) for assessing canola allelopathy in a large range of canola genotypes under laboratory conditions. Several factors were identified as playing a major role in determining canola allelopathy.
Key contents
Canola growth duration
Canola density
Sowing pattern
Sowing distance
Charcoal effect
Conference paper 2: Asaduzzaman. M., An, M., Pratley, J. E., Luckett, D., Lemerle, D. (2012). Allelopathic effect of canola on annual ryegrass. Proceedings 18th Australasian Weed Conference, Melbourne, Australia, pp. 174-177.
Paper 2 (research): Asaduzzaman. M., An, M., Pratley, J. E., Luckett, D., Lemerle, D. (2014). Optimisation of laboratory bioassay for canola allelopathy. Journal of Crop Science and Biotechnology. DOI No. 10.1007/s12892-014-0087-0 [accepted]. 50
Eighteenth Australasian Weeds Conference
Allelopathic effect of canola on annual ryegrass M. Asaduzzaman1,2,4, Min An1,4, James E. Pratley4, David J. Luckett3,4 and Deirdre Lemerle4 Environmental and Analytical Laboratories, Faculty of Science, Charles Sturt University, Wagga Wagga, NSW 2650, Australia 2 School of Agricultural and Wine Sciences, Faculty of Science, Charles Sturt University, Wagga Wagga, NSW 2650, Australia 3 NSW Department of Primary Industries, Wagga Wagga, NSW 2650, Australia 4 EH Graham Centre for Agricultural Innovation (an alliance between Charles Sturt University and NSW Department of Primary Industries), Wagga Wagga, NSW 2650, Australia (
[email protected])
1
Summary Canola is a leading winter grain crop in Australia but declining yields due to the impacts of weeds and resistances to herbicides is a significant issue for Australian cropping systems. Although weed control herbicide options are available for canola, the prospects of herbicide resistance necessitate considering alternative options such as the allelopathic potential of canola for weed suppression. To assess the allelopathic prospects of canola, a laboratory-based root exudates bioassay was conducted using ECAM (Equal-Compartment-Agar Method). The allelopathic effects of different growth duration (0, 3, 5, 7, 9, 11, 13, and 15 days) and density (15, 30, 45, and 60 seeds/ beaker) of canola (var. Ag-Spectrum) against annual ryegrass (as a test species) were investigated. During harvest the inhibited root length and diameter of ryegrass was measured. The experiment was designed as a randomised complete block with three replications and conducted under control conditions. Results showed that canola reduced the root length of ryegrass for 3–9 days, and at a density of 60 seeds/beaker was most inhibitory, suggesting that root exudates of canola are correlated with seedling density. Although, the root surface area was not influenced by density, it was significantly influenced by growth duration. Root surface area of canola was noticeably inhibited during 3–9 days. The effect of retention of canola root exudates prior to ryegrass sowing was also evaluated under the same experimental conditions. Canola was grown for 0, 3, 5, 7, 9, 11, 13 and 15 days with 60 seeds/beaker using ECAM, then canola seedlings were removed from the beakers before 15 pre-germinated ryegrass seeds were transplanted into each beaker. There was a significance difference between ryegrass grown with or without prior canola. Increasing growth duration of canola increased the inhibition effect up to 9 days but with growing time beyond this period there was no further noticeable inhibition. Keywords Canola, allelopathy, growth duration, density, root length.
174
INTRODUCTION Canola is an important rotational break crop in the Australian wheat belt, providing the benefits of a disease break and some improved ability to control weeds (Norton, 2003). Weeds are a major cost to canola production due to reduced yields, lower grain quality, and herbicide inputs. Weed management in canola has improved considerably with the development of a range of herbicide-tolerant (HT) cultivars (Lemerle et al. 20011) but Australia faces the prospect of loss of efficacy of the herbicide-tolerant options and so alternative weed management strategies such as crop competition and allelopathy, need to be evaluated. Allelopathy is the beneficial or harmful effect of one plant on another by the release of bioactive chemicals (Rice 1984). Through this mechanism, plants achieve a competitive advantage by releasing phytotoxins into their surrounds (Pratley et al. 1996) and cause the inhibition of weeds. Chon and Kim (2002) showed that in lucerne (alfalfa) crop growth duration affected the release of the allelochemicals. Research has indicated that canola stubbles (residues) have an allelopathic effect, influencing both the growth of canola itself and weeds (Moyer and Huang 1997, Urems et al. 2009). Furthermore, crop density can greatly influence the competitiveness and reduce the negative effect of weeds (Berkowitz 1988). O’Donovan (1994) reported that tartary buckwheat (Fagopyrum tataricum) was effectively suppressed with increasing canola density. Therefore, crop growth duration and density of crop may have agronomic potential for non-chemical weed management. A preliminary study was conducted to determine the allelopathic potential of canola, through its density and early growth duration, against test species annual ryegrass. MATERIALS AND METHODS General bioassay A simple laboratory root exudates bioassay (ECAM-Equal Compartment Agar method) developed by Wu (1999) was selected to evaluate the
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Eighteenth Australasian Weeds Conference allelopathic potential of canola (var. Ag-Spectrum) against annual ryegrass. Treatments comprised eight different canola growth durations (0, 3, 5, 7, 9, 11, 13 and 15 days) and four canola densities (15, 30, 45 and 60 canola seeds/beakers). At each growth time, 15, 30, 45 and 60 pre-germinated and uniform canola seeds were sown on the aseptic agar surface of onehalf of a glass beaker (9 cm diameter, 12 cm depth, and 600 mL) which was prefilled with 30 mL of 0.3% water agar. The beakers were sealed with parafilm and kept in a controlled growth chamber (light/dark 12/12 h and 20°C/18°C). After growth of the canola seedlings for 0 (control) 3, 5, 7, 9, 11, 13 and 15 days, 15 pre-germinated seeds of ryegrass were transplanted on the other half of the agar surface. A piece of preautoclaved white paperboard was inserted across the centre and down the middle of the beaker with the lower edge of the paperboard kept 1 cm above the agar surface. The beaker was divided into two equal compartments to minimise competition for space and light the between canola and ryegrass seedlings. The roots of canola freely enter the ryegrass compartment so that any allelochemicals produced and released by the canola seedlings can diffuse throughout the entire agar medium to influence ryegrass root growth. After ryegrass sowing, the beakers were again wrapped with parafilm and placed back in the growth chamber for seven days. The root length of the ryegrass seedlings was measured and root surface area was assessed by scanning and image analysis suing WinRhizo software (Regent Instruments, Montreal).
homogeneity of variance. Data were the two repeats of each experiment analysed separately subjected to an analysis variance (ANOVA) using GenStat version 13. RESULTS AND DISCUSSION Effect of growth duration and density The results of analysis of variance showed significant difference between canola growth durations (P <0.05) and between densities (P <0.05). The interaction effects of growth time and density on ryegrass was also significant (P <0.05). At lower densities of canola (15 and 30 canola seeds/beaker), the inhibition of ryegrass root was lower during all canola growth durations (Figure 1). The result suggests that there was no significance difference between densities 15 and 30 in terms of ryegrass root inhibition at each canola growth times except at 3 days. However, the inhibitory activity of canola increased and differences among growing times were significant with the greatest inhibition effect on ryegrass root length being observed at 60 canola seedlings per beaker after 9 days duration; with 5 days duration being next most inhibitive. Increasing the growing duration beyond 9 days had no further effects on annual ryegrass root growth. There were negligible differences between 11, 13 and 15 days duration at any densities. A similar trend with wheat seedling phytotoxicity was reported by Huang et al. (2003) with allelochemicals concentrations declining after 6–8 growing days. One explanation could be associated with the limited half-life of these compounds in agar medium. We also observed that after 9 days
Removal experiment The donor species canola was grown for 0 (control), 3, 5, 7, 9, 11, 13 and 15 days with 60 seeds per beaker using the ECAM method, then the canola seedlings were removed prior to 15 pre-germinated ryegrass seeds being sown into the agar surface, grown for a further 7 days growth. The root length of the ryegrass seedlings was then measured. Experimental design The experiments comprised RCBD (Randomized Complete Block Design) along with three replications under controlled condition. Both experiments were repeated twice under the same condition to check for consistent results. Square root transformation of the raw data was required to normalise and ensure
Figure 1. Effect of canola density and growth duration on root length of ryegrass (LSD = 0.56, P <0.05). 175
52
Eighteenth Australasian Weeds Conference of canola growth in the agar medium canola plants became stressed, presumably due to a shortage of nutrients in the agar medium. The average root surface area of ryegrass was not significantly changed due to interaction effects of canola growing time and density. However, it was significantly (P <0.05) affected by growth duration. The lowest root distribution was observed during 5–7 days (Figure 2). In a similar study with wheat, Li et al. (2011) reported that root surface area of ryegrass was significantly affected by both wheat density and genotype. Removal experiment Root exudates of canola significantly reduced ryegrass root length even after canola was removed from the agar medium (P <0.05). Canola density and growth duration effects on ryegrass growth were greater in the co-growth experiment than those in the ryegrass removal experiment (Figure 3). There was a significant difference between ryegrass grown with and without canola except at 13 days. Increasing growth duration of canola increased the inhibition effect up to 15 days. The root length of ryegrass was noticeably reduced during 0–9 days without canola and beyond this period the inhibition rate was reduced. Increasing canola growing time beyond 9 days produced no further inhibition, possibly due to degradation of the canola root exudates, by the ryegrass metabolism. CONCLUSION Growth duration and density of canola played a major role in the suppression of annual ryegrass root growth. The inhibitory activity of canola is growth period related and inhibition in this environment is greater in the early stages of growth (3 to 9 days). The root diameter of ryegrass was also inhibited by growing time. In addition, increasing canola density increased the inhibition, presumably due to increased concentration of root 176
exudates in the agar medium. This suggests that increased canola competitiveness can be achieved at high density leading to greater suppression of the target weed species. These investigations also suggest that there are opportunities to explore canola genotypes for their abilities to control ryegrass through allelopathy. The root exudates of canola could be used as potential natural herbicides but they must first be collected, purified and characterised.
Figure 2. Effect of canola growth duration on average root surface area of ryegrass (LSD = 1.07, P <0.05).
Figure 3. Root length of ryegrass as influenced by presence or absence of canola seedlings in the growth medium (LSD = 0.56, P <0.05).
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Eighteenth Australasian Weeds Conference REFERENCES Berkowitz, A.R. (1988). Competition for resources in weed-crop mixtures. In M. Altieri and M. Lieb-Man (Eds). ‘Weed management in agroecosystems: ecological approach’. Boca Raton, Florida: CRC press, p 89-119. Chon, S.U. and Kim, J.D. (2002). Biological activity and quantification of suspected allelochemicals from alfalfa plant parts. Journal of Agronomic crop Science 188, 281-285. Huang, Z.Q., Haig, T., Wu, H.W., An, M. and Pratley, J. (2003). Correlation between phytotoxicity on annual ryegrass (Lolium rigidum) and production dynamics of allelochemicals within root exudates of allelopathic wheat. Journal of Chemical Ecology 29, 2263-2279. Lemerle, D., Lockley, P., Koetz, E., Luckett, D. and Wu, H. (2011).Manipulating canola agronomy for weed suppression. 17th Australian Research Assembly on Brassicas, 15-17 August, Wagga Wagga, NSW, Australia. Li, C.J., An, M., Saeed, M., Li, L. and Pratley, J. (2011). Effects of wheat crop density on growth
of ryegrass. Allelopathy Journal 27 (1), 43-54. Moyer, J.R. and Huang, H.C. (1997). Effect of aqueous extracts of crop residues on germination and seedling growth of ten weed species. Botanical Bulletin of Academia Sinica 38. Norton, R.M. (2003). ‘Conservation Farming Systems and Canola’. The University of Melbourne, Melbourne. O’Donovan, J.T. (1994). Canola (Brassica napus) plant density influences tartary buckwheat (Fagopyrum tataricum) interference, biomass, and seed yield. Weed Science 42 (3), 385-389. Pratley, J.E. (1996). Allelopathy in annual grasses. Plant Protection Quarterly 11, 213-214. Rice, E.L. (1984). ‘Allelopathy’. Second Edition. Academic Press, New Work, pp 422. Urems, I., Arslan, M., Sangun, M. K., Uygur, V. and Isler, N. (2009). Allelopathic potential of rapeseed cultivars on germination and seedling growth of weeds. Asian Journal of Chemistry 21, 2170-2184. Wu, H., Pratley, J.E., Lemerle, D. and Haig, T. (1999). Crop cultivars with allelopathic capability. Weed Research 39, 171-180.
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Laboratory Bioassay for Canola (Brassica napus) Allelopathy Md. Asaduzzaman1,2*. Min An2,3. James E. Pratley1,2 . David J. Luckett2,4 . Deirdre Lemerle1,2 1
School of Agricultural and Wine Sciences, Faculty of Science, Charles Sturt University, Wagga
2
Graham Centre for Agricultural Innovation, Wagga Wagga, NSW 2650, Australia
3
Faculty of Science, Charles Sturt University, Wagga
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NSW Department of Primary Industries, Wagga Wagga, NSW 2650, Australia
*Corresponding author Md Asaduzzaman Bld 286 School of Agricultural and Wine Sciences Charles Sturt University Wagga Wagga, NSW 2650 AUSTRALIA Email:
[email protected] Telephone: +6169332749
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Laboratory Bioassay for Canola (Brassica napus) Allelopathy Abstract Crop allelopathy provides a viable alternative in managing resistant weed population. A successful demonstration of an allelopathic interaction is needed to be separated from resource competition. A reliable laboratory screening technique can test this chemical interaction between a donor and a receiver species. However the standardisation of any screening tactic for a new species is really challenging. In this study we optimised, the simple root exudates bioassay, Equal Compartment Agar Method (ECAM), for canola through basic features including sowing patterns, density and distance between canola and annual ryegrass. We established that all of the above feature have major role on canola seedling interference ability (allelopathy + competition). Due to the combined effect of allelopathy and competition, the zigzag canola sowing pattern enhanced the inhibitory effects of canola seedlings more than other sowing patterns i.e circular, parallel and cone. The sowing distance of canola played a major role on root growth of annual ryegrass that the nearer the receiver annual ryegrass plants to the donor canola seedlings, the greater was the toxic effects. Canola sowing distance at 1, 2 and 3 cm inhibited the root growth of ryegrass by 50%, 46% and 36% respectively. Results also showed that root growth of ryegrass decreased with increased canola densities (0-40 seedlings/beaker). Furthermore the added carbon experiment showed that the inhibitory effects of canola were diluted by added carbon in agar growth medium, indicating canola root exudates acted directly on root growth of annual ryegrass. This study suggest parameters such as canola sowing pattern, density and sowing distance between
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canola and test weed species need to be considered for designing canola allelopathy bioassay through ECAM under laboratory conditions.
Key word: allelopathy . competition . weeds. concentration. density
Introduction Canola has been rapidly adopted in Australia due to its diversified uses and break crop effects to become the third largest crop (Norton 2003). Weeds commonly occur in canola crops (Lemerle et al. 2001) and are a major cost to production due to reduced yield and product quality. Chemical options for weed control are effective but the use of herbicides has become challenging due to the development of herbicide resistance in many weeds, particularly annual ryegrass (Lolium rigidum) (Heap and Knight 1986; Powles and Howat 1990; Powles et al. 1996; Pratley et al. 1996). Thus suppression of weeds by the crop is a potentially important tactic for weed management and involves both crop competition and allelopathy. In the field, both phenomena occur together but are difficult to identify and quantify separately (Olofsdotter and Navarez 1996). Laboratory or greenhouse bioassays controlling for genotypic variation in competition for light, water, and nutrients provide an initial screening tool to identify lines that may lack competitive traits but possess superior allelopathic activity (Worthington and Rebergg-Horton 2013). The advantages of laboratory over field screening include the ability to differentiate allelopathic effects from competitive interactions and the increased conferred by controlled settings where environmental variance is minimised (Courtois and Olofsdotter 1998). Screening bioassays should be inexpensive, convenient, rapid, reproducible and simple to operate to be practical for plant breeding (Wu et al. 57
2000). Laboratory methods such as the plant box method (Fujii 1992), relay seedling (Navarez and Olofsdotter 1996) and the equal compartment agar method (Wu et al. 2000) are popular techniques for allelopathy research and have helped to separate competition and allelopathy. In such bioassays, seedlings of the crop (donor) species generally are grown with seedlings of weed (receiver) species for a specified period of time. For instance;
in ECAM, each species was placed into separate
compartments (divided by a pre-autoclaved white paperboard) of a glass beaker, where each species received equal space for its root system development in 0.3% agar-medium. The roots of the donor and receiver species could freely enter each other section, so that any allelochemicals produced and released by the canola seedlings could diffuse throughout the entire agar medium to influence the annual ryegrass root growth. Allelopathic potential then is measured as depressed receiver root or shoot development relative to a control (where the receiver is grown in the absence of any donor species). Furthermore, the agar medium is nutrient free and is much less cumbersome than any solution based screening techniques. The agar substances tend to have more buffering capacity, provide support for seeds and seedlings and adsorb organic and inorganic compounds on or within their matrix. However, several requirements are need to be optimised in ECAM for the particular donor and receiver species involved. In designing an appropriate screening technique, several features such as crop growth stage, donor crop sowing pattern in growth medium, choice of receiver test weed species, sowing density of both donor and receiver species and their sowing distance are essential. Crop density often influences the level of interference between crop and weeds (Radosevich et al. 1996). Crop/weed chemical interactions are 58
mediated by the allelochemical concentrations which are determined by the density of the donor crop (Belz and Hurle 2005). Wu et al. (2000) demonstrated that increasing wheat seedling density enhanced the allelopathic competitiveness of wheat against annual ryegrass. Wheat root exudates with alleopathic effect were shown to be more inhibitory when the receiver ryegrass was sown close to wheat seedlings (Wu et al. 2007). The evaluation of such mechanisms as crop exudates are challenging in field situations, but suitable laboratory design with reliable screening technique enables such phenomena to be explored. The aim of this study was to optimise the ECAM laboratory bioassay technique using different canola sowing patterns, densities and sowing distances between canola and ryegrass for a large evaluation program in respect to canola genotype allelopathy under laboratory conditions.
Materials and methods Selected bioassay and plant materials The simple laboratory root exudate bioassay, Equal Compartment Agar Method (ECAM) developed by Wu et al. (2000) was selected for optimisation. Seeds of a commercially available canola cultivar (cv. Ag-spectrum) were obtained from the National Brassica Germplasm Improvement Program, located at NSW Department of Primary Industries, Wagga Wagga, Australia. Seeds of annual ryegrass were obtained commercially. Agar (technical grade) and activated carbon were purchased from Sigma Aldrich (St. Louis, USA).
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a
b
c
d
Fig. 1. Seedling arrangements in the beakers used in experiment (a) circular (b) zigzag (c) cone and (d) parallel sowing pattern. Key: canola ( ) and ryegrass ( ).
Sterilisation and germination Seeds were surface-sterilised by soaking in 2% sodium hypochlorite (NaOCl) for 5 minutes, then rinsed six times in sterilised distilled water. The seeds were transferred to a petri dish with one sheet of Whatman No. 1 filter paper moistened with 5 mL 60
sterilised distilled water, and sealed with parafilm. The surface-sterilised seeds of Brassica and ryegrass were kept in a 12-hour light/12-hour dark, 20 °C/15 °C controlled environment.
Experiment 1: sowing pattern To evaluate the allelopathic effect of canola by different sowing patterns, canola seedlings were sown in four different patterns i.e. (a) circular, (b) zigzag, (c) cone and (d) parallel in the ECAM, where the glass beaker (9 cm diameter, 12 cm depth, and 600 mL) was prefilled with 30 mL of 0.3% water agar (nutrient free) as a growth medium (Fig. 1). For each sowing pattern 20 pre-germinated, uniform canola seeds were sown on the aseptic agar surface. The beakers were sealed with parafilm and kept in a controlled growth chamber (light/dark 12/12 h and 20 oC/18 oC). After growth of the canola seedlings for 6 days, 10 pre-germinated seeds of ryegrass were transplanted on the agar surface according to sowing pattern. After ryegrass sowing, the beakers were again wrapped with parafilm and placed back in the growth chamber. After seven days, the root and shoot lengths of ryegrass seedlings were measured.
Experiment 2: sowing distance To evaluate the diffusion effect of canola root exudates on receiver ryegrass, a sowing distance experiment was conducted. Using the parallel sowing patterns (Fig. 1d), 20 canola pre-germinated seedlings were sown as described in experiment 1. After 6 days of canola growth, three distances (1, 2 and 3 cm) from the line of the donor canola seedlings were marked and pre-germinated ryegrass seeds were sown separately on the 1, 2, or 3 cm pre-marked line. After ryegrass sowing, a piece of 61
pre-autoclaved white paperboard was inserted across the centre and down the middle of the beaker with the lower edge of the paper board kept one cm above the agar surface. The beaker was divided into two equal compartments to minimize competition for space and light the between canola and ryegrass seedlings. The roots of canola freely enter the ryegrass compartment so that any allelochemicals produced and released by the canola seedlings could diffuse throughout the entire agar medium to influence ryegrass root growth. After ryegrass sowing, the beakers were again wrapped with parafilm and placed back in the growth chamber for seven days.
Experiment 3: charcoal experiment To confirm the allelopathic effect between canola and annual ryegrass seedlings, 0.2% activated carbon was added to the agar in beaker. Activated carbon absorbs organic compounds such as allelochemicals; therefore, any allelopathic effect will be reduced where activated carbon is added to agar medium. The parallel sowing pattern (Fig. 1d) was used in this experiment. The carbon was mixed with agar just after the beakers were autoclaved. Beakers containing the carbon-agar mix were gently swirled to suspend the activated carbon before the mix was allowed to cool and set. Canola was established for 6 days prior to ryegrass being sown into the carbon containing agar medium. Controls with no carbon added were evaluated for treatment as control beakers. Ryegrass was sown at 1, 2, and 3 cm line away from the line of the donor canola seedlings. The beakers were rewrapped with parafilm and placed back in the growth chamber for seven days before the root lengths of the ryegrass seedlings was measured.
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Experiment 4: density experiment To evaluate the effect of density of donor canola crop on its allelopathic activity, a separate canola density experiment was conduct. Pre-germinated canola seeds at different densities (0, 5, 10, 20, 30 and 40) were sown on one half of the agar surface using the parallel sowing pattern (Fig. 4). After 6 days of canola growth, 10 pregerminated ryegrass seeds were sown on the other half of the aseptic agar surface. The beakers were rewrapped and kept in the incubator after a pre-autoclaved white paper board was inserted as described in experiment 2.
Statistical analysis A randomized complete block design with three replications was used for all experiments described above. Experimental data were subjected to an analysis of variance (ANOVA) using GenStat version 16. The residuals from the ANOVA were examined to ensure they met the assumption of the analysis: normality and homogeneity of variance.
Results Experiment 1 Canola sowing pattern did not show any effect on shoot growth of annual ryegrass (data not shown). However there was significant variation between sowing pattern of canola (P<0.001) in terms of ryegrass root inhibition. The zigzag and circular sowing patterns inhibited root growth of annual ryegrass the most followed by the parallel and cone sowing patterns (Fig. 2). The mean root length of ryegrass from these four different sowing patterns was 27 cm, 28 cm, 45 cm and 58 cm respectively. 63
Experiment 2 The sowing distance of canola had a significant effect (P<0.001) on the receiver ryegrass root growth. The nearer the ryegrass receiver plants were to the donor canola seedlings, the greater was the inhibitory effects in terms of reduced ryegrass seedling root length. With ryegrass sown at a distance of 1, 2 or 3 cm from the canola zone, inhibition was 50%, 46% and 36% respectively (Fig. 3). Ryegrass in the absence of canola (as control) average 64 cm in root length.
Fig. 2. Sowing pattern effects of canola root exudates on the root growth of annual ryegrass. Error bars represent standard errors of the mean and values with the same letters are not significantly different (P<0.001).
Experiment 3 In the absence of activated carbon, canola inhibited the ryegrass root growth with increasing effect as sowing separation distance decreased. The addition of activated 64
carbon completely negated the canola effect irrespective of the sowing distance (Fig. 4).
Fig. 3. Sowing distance effect of canola root exudates on root growth of annual ryegrass in parallel sowing pattern. The distances to the donor canola were 1 (□), 2 (■) and 3(⸗) cm distance from canola. Error bars represent standard errors of the mean and values with the same letters are not significantly different (P<0.001).
Experiment 4 Significant differences (P<0.001) between canola densities were obtained in terms of ryegrass root growth inhibition which ranged from 100% to 44% (Fig. 5). The lower densities of canola had low inhibition of ryegrass roots but the inhibition increased with increased density of canola. The maximum inhibition was observed at a density of 40 canola seedlings/beaker. The inhibition increased sharply at densities
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between 5 to 30. The calculated ID50 occurred at canola density more than 40 seedlings/ beaker.
Fig. 4. Effect of activated carbon (■) and sowing distance of canola on root growth of annual ryegrass in parallel sowing pattern. The canola was sown 1 (□), cm 2 (
) cm and 3 (⸗) cm. Error bars represent standard errors of the
mean and values with the same letters are not significantly different (P<0.001).
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Fig. 5. Density influenced canola allelopathy on root growth of annual ryegrass in parallel sowing pattern. Error bars represent standard errors of the mean and values with the same letters are not significantly different (P<0.001).
Discussion It can be argued that crop allelopathy is mainly determined by below-ground cropweed chemical interaction. However, crop secretions of secondary metabolites through the root into the rhizosphere are often constrained by the above-ground light and stress condition (Maldini et al. 2012). Differences in the magnitude of effect of canola allelopathy on ryegrass conditioned by different sowing patterns and distance 67
were identified in this study. The zigzag sowing pattern may have allowed both allelopathy and competition for light to occur between canola and ryegrass, as the donor canola plant was surrounded by receiver ryegrass plants that intercepted more light than the canola plants due to greater growth rate. The circular canola sowing pattern may also have some problem in that weed species are generally faster growing and expand leaves very quickly to become more competitive for light. The cone sowing pattern eliminated the shade effect of crop on weed and vice versa but allelochemicals from canola root exudates inhibited more closely ryegrass roots due to the diffusion of chemicals. Here the parallel line sowing tactic was more reliable as it separated crop competition and allelopathy in glass beaker. Both competition and allelopathy from crop plants may results in weed suppression in field situations but does not matter what is causing the suppression of the weed. In research, however it is very important to be able to distinguish between the two (Olofsdotter and Navarez 1996) and techniques need to be developed to distinguish the mechanisms. Research has shown that phytotoxic compounds are actively exuded by living plants into the soil where they disperse by diffusion and water flow. The nearer the receiver species is to the donor root exudates, the greater the toxic effects (Wu et al. 2007). By using different sowing distances from wheat, Wu et al. (2007) found that wheat root exudates released into the agar medium demonstrated a radial effect on root growth of ryegrass. Canola root allelochemicals also showed a diffusion effect in our experiment. Gimsing and Kirkegaard (2006) collected soil samples after removing the canola plants and showed that concentration of different toxic
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chemicals (i.e. isothyocyanates and glucosinolates) decreased with increased depth of soil sampling. The allelopathic effect observed between canola and ryegrass was significantly reduced when activated carbon was added to the system suggesting that the ryegrass growth responses observed were due to the presence of inhibitory organic chemicals from canola. The growth chamber provided sufficient light and the agar growth medium was nutrient free thereby removing the element of competition. The addition of activated carbon was used to verify the presence of putative inhibitory organic chemicals (Mahall and Callaway 1992; Callaway and Aschehoug 2000). Mahall and Callaway (1992) found that activated carbon ameliorated the negative effects of Larrea sp. roots on the roots of Ambrosia dumosa. Belliveau and Callaway (2001) found that roots of Festuca idahoensis grew significantly slower as they approached by the roots of Centaurea maculosa, a noxious invasive weed. However the presence of activated carbon reduced these effects. Activated carbon is not a precise experimental tool for manipulating particular root exudates but its effect provides evidence for chemically mediated direct interactions among roots (Schenk et al. 1999) Annual ryegrass root inhibitions at higher densities of donor canola indicate that more canola allelochemicals are being exuded than at low densities of canola. Research also revealed that the allelopathic activity of canola (Asaduzzaman et al. 2014) and wheat (Wu et al. 2000) seedlings was increased with increased density against annual ryegrass in vitro. Furthermore, Seal et al (2004) reported that density dependent allelopathy differed between rice cultivars, which suggest that increasing density of canola may improve competitiveness of weak allelopathic cultivars. 69
Conclusion These experiments showed that allelopathic influence is affected by spatial relationships and by density, which influence the concentrations of allelochemicals in the root environment. For each allelopathic study these relationship need to be optimised.
Acknowledgements The senior author thanks to Charles Sturt University for an IPRS (International Postgraduate Research Scholarship), an APA (Australian Postgraduate Award) Scholarship and Writing up Award.
References Asaduzzaman M, An M, Pratley JE, Luckett DJ, Lemerle D. 2014. Canola (Brassica napus) germplasm shows variable allelopathic effects against annual ryegrass (Lolium rigidum). Plant Soil 380 (1 & 2): 47-56 Belliveau R, Callaway RM. 2001. Relative effects of root comeptition and allelopathy between Cetaurea maculasa and a native bunchgrass. Oecologia 126: 444-450 Belz RG, Hurle K. 2005. Dose-response-a challenge for allelopathy? Nonlinearity 3(2): 173-211. Callaway RM, Aschehoug ET. 2000. Invasive plants versus their new and old neighbours: a mechanism for exotic invasion. Science 290: 521-523 Courtois B, Olofsdotter M. 1998. Incorporating the allelopathy trait in upland rice breeding programs: Allelopathy in rice. International Rice Research Institute, Philippines. Fujii Y (1992) The potential biological control of paddy weeds with allelopathyallelopathic effect of some rice varietie. In: Interantional Symposium Biological Control and Intreagted Management of Paddy and Aquatic Weeds in Asia. National Agricultural Research Centre of Japan, Tsukuba.
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Gimsing AL, Kirkegaard JA. 2006. Glucosinolates and isothiocyanate concentration in soil following incorporation of Brassica biofumigants. Soil Bio. Biochem. 38: 2255-2264 Heap J, Knight R. 1986. A population of ryegrass tolerant to the herbicide diclopmethyl. J. Aust. Inst. Agric. Res. 37: 149-156 Lemerle D, Blackshaw RE, Smith AB, Potter TD, Marcroft SJ. 2001. Comparative survey of weeds surviving in triazine-tolerant and conventional canola crops in south-eastern Australia. Plant Prot. Quart. 16: 37-40 Mahall BE, Callaway RM. 1992. Root communication mechanisms and intracommunity distributions of two major desert shrubs. Ecology 2145-2151 Maldini M, Baima S, Morelli G, Scaccini C, Natella F. 2012. A liquid chromatography-mass spectrometry approach to study glucosinoloma in broccoli sprouts. J Mass Spect. 47: 1198-1206 Navarez D, Olofsdotter M. 1996. Allelopathic rice for Echinochloa crus-galli control. In: 2nd International Weed Control Congress, (Eds. H. Brown, G. W. Cussans, M. D. D. Devine, C. S. O. Fernandez-Quintanilla, A. Helweg, R. E. Labrada, M. Landes and P. S. Kudsk, Denmark Norton RM (2003) Conservation Farming Systems and Canola. The University of Melbourne, Melbourne Olofsdotter M, Navarez D. 1996. Allelopathic rice for Echinochloa crus-galli control In: 2nd International Weed Control Congress, Eds. H. Brown, G. W. Cussans, M. D. D. Devine, C. S. O. Fernandez-Quintanilla, A. Helweg, R. E. Labrada, M. Landes and P. S. Kudsk, Denmark Powles SB, Howat PD. 1990. Herbicide resistance in Australia. Weed Technol. 4:178-185 Powles SB, Preston C, Brain IB, Justum AR. 1996. Herbicide resistance: impact and management. Advan. Agron. 58: 1-28 Pratley JE, Baines P, Eberbach P, Incerti M, Broster J. 1996. Glyphosate resistance in annual ryegrass. In: 11th Annual Conference of the Grassland Society of NSW, Wagga Wagga Radosevich S, Holt J, Ghersa C. 1996. Weed ecology: implication for management. pp. 145-150, John Wiley and Sons, Toronto Schenk HJ, Callaway RM, Mahall BE. 1999. Spatial root segregation: are plants territorial? Advan. Biol. Res. 28: 146-180 71
Seal AN, Pratley JE, Haig T, Lewin LG. 2004. Screening rice varieties for allelopathic potential against arrowhead (Sagittaria montevidensis), an aquatic weed infesting Australian Riverina rice crops. Aust. J. Agric. Resh. 55: 673-680 Worthington M, Reberg-Horton C. 2013. Breeding cereal crops for enhanced weed suppression: optimizing allelopathy and competitive ability. J. Chem. Ecol. 39 (3): 247-256 Wu H, Pratley JE, Lemerle D, Min A, Liu DL. 2007. Autotoxicity of wheat (Triticum aestivum L.) as determined by laboratory bioassays. Plant Soil 296: 8593 Wu H, Pratley JE, Lemerle D, Haig T. 2000. Laboratory screening for allelopathic potential of wheat (Triticum aestivum) accessions against annual ryegrass (Lolium rigidum). Aust. J. Agric. Res. 51: 259-266
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Chapter 5 Research Findings in the Laboratory This chapter reports investigation of canola seedling allelopathic variation between genotypes, and highlights the sources of allelopathic germplasm under laboratory conditions.
Key contents
Total 70 canola genotypes
Canola density 10, 20 and 30 (seedlings/beaker)
Annual ryegrass density 15 (seedlings/beaker)
ECAM method
Density effect
Genotype effect
Density x Genotype effect
Sources of genotypes
Appendix
Paper 3 (research): Asaduzzaman. M., An, M., Pratley, J. E., Luckett, D., Lemerle, D. (2014). Canola (Brassica napus) germplasm shows variable allelopathic effects against annual ryegrass. Plant and Soil, 380(1), 47-56. DOI 10.1007/s11104-014-2054-4. 73
Plant Soil (2014) 380:47–56 DOI 10.1007/s11104-014-2054-4
REGULAR ARTICLE
Canola (Brassica napus) germplasm shows variable allelopathic effects against annual ryegrass (Lolium rigidum) M. Asaduzzaman & Min An & James E. Pratley & David J. Luckett & Deirdre Lemerle
Received: 22 October 2013 / Accepted: 4 February 2014 / Published online: 18 February 2014 # Springer International Publishing Switzerland 2014
Abstract Aims The allelopathic activity of canola (Brassica napus) germplasm was investigated using the important Australian weed, annual ryegrass (Lolium rigidum) as the target species. Methods Three different canola plant densities (10, 20, and 30 seedlings/beaker) of each of 70 world-wide genotypes were tested in vitro in close proximity to annual ryegrass seedlings. Results The allelopathic activity of canola, as measured by reduction in annual ryegrass root and shoot growth, increased with canola crop seedling densities. Density did not consistently influence shoot length of annual ryegrass. Responsible Editor: Inderjit. M. Asaduzzaman (*) : J. E. Pratley : D. Lemerle School of Agricultural and Wine Sciences, Faculty of Science, Charles Sturt University, Bld No 286 Boorooma Street, Wagga Wagga, NSW 2650, Australia e-mail:
[email protected] M. An Faculty of Science, Charles Sturt University, Wagga Wagga, NSW 2650, Australia D. J. Luckett NSW Department of Primary Industries, Wagga Wagga, NSW 2650, Australia M. Asaduzzaman : M. An : J. E. Pratley : D. J. Luckett : D. Lemerle Graham Centre for Agricultural Innovation (an alliance between Charles Sturt University and NSW Department of Primary Industries), Wagga Wagga, NSW 2650, Australia
Greater shoot length suppression was observed in genotype cv. Rivette and BLN3343CO0402. The Australian genotype cv. Av-opal and the breeding line Pak85388-502 suppressed root length of ryegrass more than other genotypes, even at low densities. At the lowest density, the least allelopathic genotypes were cv. Barossa and cv. Cescaljarni-repka, although they became more allelopathic at higher density. An overall inhibition index was calculated to rank each of the canola genotypes. There were significant differences between canola genotypes in their ability to inhibit root and shoot growth in ryegrass. Conclusion Considerable genetic variation exists among canola genotypes for their allelopathic effects on annual ryegrass. Further investigation is required to determine the allelopathic mechanisms, particularly to identify the responsible allelochemical(s) and the gene(s) controlling the trait. This research suggests that highly allelopathic canola genotypes can be potential for controlling weeds such as annual ryegrass in integrated weed management programs. Keywords Canola . Weeds . Allelopathy . Allelochemicals
Introduction Canola (Brassica napus L.) has become an important oilseed crop worldwide and a profitable break crop for grain growers in Australia. This enhanced production can be partially attributed to the increased need for diversity in farming systems, and demand for higher
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quality oils for human consumption. Accordingly, the global canola area has grown rapidly over the past 20 years, rising from the sixth to the second most important oilseed crop (AOF 2013; Canola Council of Canada 2013). Weeds are a restrictive factor that significantly reduces the grain yield and quality of canola (Lemerle et al. 2012). Grass weeds including annual ryegrass, vulpia (Vulpia myuros) and wild oat (Avena spp), are the most important weeds of canola crops in Southern Australia (Lemerle et al. 2001). The Brassicaceae weeds, such as wild radish (Raphanus raphanistrum) are also prevalent and their heavy infestation can reduce canola yield up to 90 % (Blackshaw et al. 2002). The management of such weeds is a challenge due to the limited availability of post-emergent selective herbicides for use in conventional canola cultivars and the low efficacy against these ‘canola-like’ weeds (Preston and Baker 2009). The introduction of herbicide-tolerant cultivars allows growers to manage many of their most difficult weeds (Harker et al. 2000). However, prolonged and widespread use of these herbicides increases the risk of herbicide resistance in Australian annual ryegrass including to glyphosate (Heap 2013; Pratley et al. 1999). The intensive and repeated use of a single herbicide (or those with the same mode-of-action) also facilitates the shifting of the weed population from susceptible to tolerant species (Green 2009). In addition, herbicideresistant crop seed left behind at harvest and in the following season can become volunteers which are difficult to control. Left uncontrolled, these plants eventually set seed and increase the incidence of herbicideresistant weeds, causing escalating economic loss. The combination of herbicides and associated resistant cultivars is the most cost-effective and widely used weed control method in canola (Beckie et al. 2006). Canola growers have few alternatives to current weed management systems, because the likelihood of new herbicide modes-of-action becoming available is limited (Pratley et al. 1998). There has been speculation about the factors limiting new herbicide appearance (Duke 2012). However, low commodity prices, herbicideinduced crop injury, herbicide residue concerns, and public concern about the environmental and human health effect of herbicides are forcing growers to consider non-chemical alternative options (Blackshaw et al. 2008). One feasible option, as a supplement to synthetic herbicides, is canola competition and allelopathy to increase the weed suppression by the crop. Crop
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competition occurs in communities when two or more plant seeks a common resource within limited spaces (Harper 1977). Furthermore agronomic factor, crop density, can influence the competitive effects of weeds and reduce the need for herbicides (O’Donovan 1994). The manipulation of canola agronomy by choice of canola genotype and by increasing crop density has been shown to reduce weed impacts in Australia (Lemerle et al. 2012). Increasing seeding rate has a major effect on crop/weed interaction (Hume 1985) and allelochemical concentrations are a function of the density of the allelopathic crop (Belz and Hurle 2005). This suggests that density may be an important factor in enhancing canola allelopathic activity . Allelopathy, as first described by Molisch (1937), is the stimulatory or inhibitory impact of any biochemical interaction between plants (Rice 1984). Different plant species have been reported to have allelopathic activity that could be utilised in agricultural or ecological systems (Rice 1984). Where the allelopathic effect is inhibitory, the term phytotoxicity is commonly used. Brassica spp have received attention because of their allelopathic activity via their residues and plant extracts especially when used as cover crops (Haramoto and Gallandt 2005; Norsworthy et al. 2011). The development of crops with the capability to exert allelopathic effects on crop weeds through root exudates is another option (Olofsdotter et al. 2002). Research has shown that in wheat (Wu et al. 2000a) and rice (Dilday et al. 1994; Seal et al. 2004) the degree of allelopathic effect differs between crop cultivars. The production of allelochemicals is also influenced by environmental conditions (Quader et al. 2001). It is especially important to evaluate the allelopathic potential of a crop or its cultivars under field conditions but it is difficult to eliminate the influence of competition when assessing the allelopathic potential of a crop in the field (Wu et al. 2000b). The standardized laboratory assay is a rapid and an inexpensive procedure for screening the allelopathic potential of large numbers of crop genotypes against target weed species (Wu et al. 2000b). Further, the interaction between crop and weed is critical at the seedling stage. Where weed species can be allelopathically suppressed by crop plants during the seedlings establishment period, the crop will gain competitive advantage over weeds. Due to the economic importance of canola and the diversity of cultivars grown throughout the world, research is required to determine the potential of crop allelopathy for weed
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management in canola. The objectives of this study are to (i) evaluate the role of canola density on its allelopathic impact and (ii) evaluate canola seedling allelopathy for the suppression of annual ryegrass in 70 diverse Brassica genotypes.
Methods and materials Plant materials Seeds of 60 Brassica napus genotypes and ten genotypes from closely-related Brassica species were selected for the bioassay screening. All seed was obtained from the National Brassica Germplasm Improvement Program, located at NSW Department of Primary Industries, Wagga Wagga, Australia. The Brassica genotypes originated from Australia, Asia, Europe and Canada. The genotypes were chosen to try and maximise the genetic diversity present in the set of 70 genotypes. Seed of annual ryegrass was obtained commercially. Agar (technical grade) was purchased from Sigma Aldrich (St. Louis, USA). Sterilisation and germination Brassica seeds were surface-sterilised by soaking in 2 % sodium hypochlorite (NaOCl) for 5 min, then rinsed six times in sterilised distilled water. The seeds were transferred to a petri dish with one sheet of Whatman No. 1 filter paper, moistened with 5 ml sterilised distilled water, and sealed with parafilm. The surface-sterilised seeds of Brassica and ryegrass were kept in a 12-h light/ 12-h dark, 20 °C/15 °C controlled environment. General bioassay and growing conditions The equal-compartment-agar-method (ECAM), described previously by Wu et al. (2000b) and based on the plant box method and relay seedling technique, was used for the bioassay screening. This technique provides a rapid, simple, inexpensive method for the initial screening of the allelopathic potential of a large number of genotypes against a target weed species under laboratory conditions. Glass beakers (600 ml, 12 cm depth, 8 cm diameter) containing 30 ml of 0.3 % agar-medium (no nutrients, 1.3 cm depth) were autoclaved. The preliminary experiment with a single genotype showed canola density played a major role in its allelopathic activity in suppressing annual ryegrass root growth
49
and diameter (Asaduzzaman et al. 2012). Hence for each Brassica genotype, 10, 20, or 30 uniform seedlings per beaker were chosen and aseptically transplanted from the germination dish onto one half of the agar surface, with the embryo up. The beaker tops were sealed with parafilm to prevent contamination and evaporation from the agar surface, and were placed in a controlled growth incubator with a daily 12-h light/12-h dark, 20 °C/15 °C cycle. After the Brassica plants had been left to grow for 6 days, 15 pre-germinated seeds of annual ryegrass were aseptically sown on the other half of the agar surface, at a distance of 4 cm from the Brassica seedlings. A piece of pre-autoclaved white paperboard was inserted down the centre of the beaker with the lower edge of the paperboard ending 1 cm above the agar surface. The beaker was divided this way to minimize competition for space and light between the Brassica and annual ryegrass seedlings. The roots of the Brassica could freely enter the annual ryegrass section of the agar volume, so that any allelochemicals produced and released by the Brassica seedlings could diffuse throughout the entire agar medium to influence the annual ryegrass root growth. After the ryegrass was sown, the beaker was again wrapped with parafilm and placed back in the growth cabinet for a further 7 days cogrowth. The receiver species, annual ryegrass, was also grown alone as a control. After 7 days, each annual ryegrass seedling was carefully removed from the agar to avoid root breakage, and the root and shoot lengths were measured. Experimental design and statistical analysis A randomized complete block design with four replications was used for the experiment described above. For each genotype, 4 × 4 (1 control+3 density)=16 experimental units were arranged spatially using DiGGer design software in R (Coombes 2002). A total of 35 separate experiments were needed to test all 70 Brassica genotypes while all experimental condition was identical. Raw data for the root and shoot length of annual ryegrass for the different densities of each Brassica genotype were used separately for statistical analysis. Data (expressed as the percentage of the control root and shoot growth) were subjected to analysis of variance using Genstat v13 (VSN International, Hemel Hempstead, UK) and the treatments means compared using the least significance difference (LSD) at a 5 % level of probability. Plots of residual versus fitted values were
76
50
Plant Soil (2014) 380:47–56
examined for all traits to ensure that the assumptions of analysis of variance were met. The density-response data were further subjected to the analysis of whole-range assessment proposed by An et al. (2005). Whole-range assessment is a simple method for analyzing allelopathic density-response data. It considers the overall effect or response across the whole range of application rates instead of assessing the effect of each individual rate on the test species. The approach used here was to calculate the inhibition areas of the ryegrass. Compared with the control (100 %) over the whole range of genotype densities on the X axis. Thus inhibi-
Table 1 Genotype, density and genotype × density effects from ANOVA of root and shoot length (as percent of control) of annual ryegrass in the presence of 70 diverse Brassica genotypes Character
Component
df
Root
Genotype
69
Density
3
Genotype × Density Residual Genotype
Shoot
ms
P
1,535.3
<0.01**
13,3971.2
<0.01**
207
285.4
<0.01**
837
121.3
69
735.2
<0.01**
Density
3
12,155.4
<0.01**
Genotype × Density
207
167.4
<0.01**
Residual
837
104.9
100
t i o n a r e a = ∫ CT ½100−f ðC ÞdC w h e r e C i s t h e allelochemicals concentration or equivalent and CT is the threshold concentration for causing inhibition in annual ryegrass. Overall biological activity across the whole range of concentrations or equivalent is then summarised, calculated and presented by a single value “inhibition index” which is defined as the percentage of the inhibition area to the total area, therefore inhibition index = (inhibition area/total area) × 100, where the total 100
area as defined as ∫ 0 100dC: WESIA software developed by Liu et al. (2007) was used to compute the inhibition area and calculation of ‘inhibition index’, which was defined as the percentage of the maximum area inhibited. The inhibition index gives a relative indication of the biological activity for each genotype. Genotypes with strong allelopathic activity will have high index values whereas low values indicate weak or no activity. The calculated inhibition index of each Brassica genotype for root and shoot of annual ryegrass was also analysed with Genstat v13.
was considerably reduced at higher densities of canola when compared with the control. The results of the bioassay of the root length of annual ryegrass for the 60 B. napus and 10 non-napus genotypes were plotted in a density-response curve. For illustration simplicity only the four most allelopathic and the four least allelopathic genotypes are presented (Fig. 1). Most Brassica genotypes significantly reduced the root growth of annual ryegrass with increased density. However, this trend was not apparent in three napus genotypes, Cescaljarni-repka (69), Lantern (67) and Barossa (70), and two non-napus genotypes, Kaga (46) and Hosin (25). At densities of 10 and 20 seedlings per beaker, these genotypes still permitted the elongation of the
Results Effect of density
The suppression of annual ryegrass shoot length was variable (data not shown). However, there were significant interaction effects between densities and genotypes (Table 1). The highest shoot length inhibition of annual ryegrass was recorded at increased density of Rivette (8) and BLN3343CO0402 (18). Minimum inhi-bition of shoot length was observed at the low density of genotypes Tarcoola-141 (61) and Maintainer-gsr-ms- 501 (28). In contrast, root growth of annual ryegrass
Fig. 1 Effect of canola density and genotype on ryegrass root length for the eight most extreme genotypes. Open symbols are the least allelopathic genotypes, closed symbols are the most allelopathic. white square = Barossa, white down-pointing triangle = cescaljarni-repka, white up-pointing triangle = Urvashi, O = Lantern, black square = Pak85388-502, black diamond = JC134, black circle = Roy47-99P1, and black up-pointing triangle = Av-opal
77
Plant Soil (2014) 380:47–56
annual ryegrass roots but inhibited root length at density 30 seedlings per beaker. Interestingly, at a density of ten seedlings per beaker, the weakest genotype Barossa slightly stimulated annual ryegrass root growth. All genotypes significantly reduced the root but not shoot growth of ryegrass at a density of 30 seedlings per beaker compare with the control. At this highest density, the least phytotoxic genotype Cescaljarni-repka reduced by only about 15 % the root length, whereas Av-opal (1) and Pak85388-502 (2) controlled root growth by 73 % and 70 % respectively. The combined density results of all genotypes were processed in the WESIA software to calculate the overall allelopathic effect of each genotype.
Genotypic effects on the root and shoot growth of annual ryegrass The allelopathic inhibition indices of Brassica genotypes against annual ryegrass roots ranged from 55 to 8 % depending on genotype (Table 2). Annual ryegrass shoot inhibition, due to the phytotoxic activity of canola genotypes was less than that against ryegrass roots, although there was significant variation between genotypes and that ranged from 24 to 1 % (Table 2). In Fig. 2, deviation of data from the solid 1:1 line shows a weak relationship between root and shoot inhibition of annual ryegrass but significant correlation was present. Several genotypes showed strong inhibition of root length but were less active against shoot growth. However, the most allelopathic genotypes, such as Av-opal, Pak85388-502, Rivette (8) and Rainbow (11) showed stronger suppression of both root and shoot growth than the less allelopathic genotypes. The genotype BLN3343CO0401 (19) had the highest index value of 24 % for annual ryegrass shoots followed by Rainbow. These were statistically similar to both Av-opal and PAK85388-502 which showed the greatest allelopathic activity on root growth. The lowest shoot inhibition index of 1 % was seen in Maintainer-gsr-ms-501(18) and was statistically similar to the two least-allelopathic genotypes with regard to root elongation, Barossa and Cescaljarni-repka. Of the 70 Brassica crop genotypes, nine were strongly allelopathic or phytotoxic, significantly inhibiting the root growth of ryegrass with an inhibition index of more than 45 %. By contrast, three genotypes were very weakly allelopathic, with considerably less inhibition
51 Table 2 Name and overall root allelopathic index of 70 diverse Brassica genotypes tested against annual ryegrass under laboratory conditions Number Name
Brassica species
Root Shoot inhibition inhibition index (%) index (%)
1
Av-opal
napus
55
2
Pak85388-502
napus
52
20
3
Roy98310
52
24
4
Roy47-99P1
52
15
5
JC134
51
20
6
Sardi603
napus × juncea napus × juncea juncea × carinata napus
49
16
7
Atr-beacon
napus
49
17
8
Rivette
napus
47
23
9
44C76
napus
46
9
10
Bau-m-58-501
napus
45
21
11
Rainbow
napus
45
24
12
BLN 4143
napus
44
21
13
Surpass 400
napus
44
12
14
Ag-outback
napus
44
5
15
ATC94044-1
carinata
43
9
16
RP004
napus
43
10
17
Dong-hae-18-501
napus
43
12
18
BLN3343CO0402 napus
43
24
19
BLN3343CO0401 napus
42
24
20
Tarcoola-1
napus
42
7
21
Monty
napus
42
10
22
Skipton
napus
41
15
23
Charlton
napus
41
10
24
44C73
napus
41
10
25
Hosin
rapa
40
8
26
Sardi607
napus
39
27
14
29
Surpass400-NCB4 napus × 38 carinata Maintainernapus 38 gsr-ms-501 Taiwan-2-501 napus 38
30
Eureaka
napus
38
15
31
Wesway
napus
38
7
32
BLN1990
napus
37
13
33
Azuma-501
napus
37
3
34
Vinnickij-501
napus
37
7
35
Buk-wuk-13-501
napus
37
5
36
Iiwao-natane-502
napus
36
10
37
Ukraine-c-501
napus
36
5
38
Teri-oo-r9903
napus
36
15
28
21
7
1 13
78
52
Plant Soil (2014) 380:47–56 25
Table 2 (continued) Brassica species
Root Shoot inhibition inhibition index (%) index (%)
39
Tarcoola-191
napus
36
10
40
Tarcoola-22
napus
35
12
41
Seetha
napus
35
8
42
Tarcoola-21
napus
34
7
43
Rafal-502
napus
34
6
44
Cb-telfer
napus
33
10
45
BLN 3614
napus
32
11
46
Kaga
rapa
32
5
47
Ag-spectrum
napus
32
6
48
Austria-3-501
napus
30
12
49
A-19890
napus
30
5
50
Atr-cobbler
napus
29
6
51
Zhongyou-za-no8
napus
29
7
52
Purler
napus
29
8
53
Topas
napus
28
6
54
BLN 4135
napus
26
19
55
Ag-emblem
napus
26
13
56
Drakkar
napus
25
6
57
Chon-nam
napus
24
7
58
Av-jade
napus
22
9
59
BLN 4139
napus
22
7
60
Hurricane-TT
napus
22
3
61
Tarcoola-141
napus
21
2
62
Mutu-98-1
napus
19
5
63
NU-41737-502
juncea
18
10
64
WA050085
napus
17
8
65
X-06-06-3725
napus
17
3
66
Maluka
napus
16
8
67
Lantern
napus
16
3
68
Urvashi
juncea
11
11
69
Cescaljarni-repka
napus
10
5
70
Barossa
napus
8
7
Mean inhibition index
35
10
Inhibition index LSD (5 %)
10
9
of ryegrass root growth and an inhibition index of less than 15 %. Both napus and non-napus Brassica species showed similar variation in their phytotoxicity regarding root and shoot growth of ryegrass (Fig. 3). However, of 10 non-napus genotypes, the inter-specific progeny from crosses B. napus × B. juncea (3), B. napus × B. juncea
3
10 12
LSD (5%)
Shoot inhibition index (%)
Number Name
19 1811 8
20
1 52
54 7
15 68
10 70
5
69
3830 22 27 29 55 32 17 13 48 40 45 63 36 24 44 39 232116 15 9 58 66 41 52 25 64 5957 51 42 34 3126 20 56 5350 47 43 4946 37 35 62 14 67 65 33 60 28 61
6 4
0 0
10
20 30 40 Root inhibition index (%)
50
Fig. 2 Annual ryegrass root and shoot inhibition indices (%) for 70 Brassica genotypes (r=0.37*, P=0.002; r is Pearson’s correlation co-efficient). The solid line is the 1:1relationship between the root and shoot indices. Numbers refer to the genotypes listed in Table 2
(4), and B. juncea × B. carinata (5), demonstrated greater phytotoxic activity. These three genotypes were among the eight most phytotoxic groups of the 70 in the bioassay. The representative of the species B. carinata (15) was found to have a medium phytotoxic effect with an inhibition index of 43 % for root growth and 9 % for shoot growth. B. rapa accession (46) and a progeny from a cross of B. napus × B. carinata (27) were comparatively less inhibitory to the shoots but more inhibitory to the roots of annual ryegrass. In this bioassay genotypes originating from five different continents were used (Fig. 4) and broad range of phytotoxic differences between genotypes were shown even though they originated from same continent. The Australian genotypes were well represented in the most phytotoxic group with regards root and shoot inhibition. However, although Av-opal, an Australian genotype, was the most phytotoxic, another Australia-originating genotype, Barossa, was the least phytotoxic. All Asian genotypes showed medium phytotoxic potential and genotypes originating from unknown sources demonstrated a wide range of allelopathic phytotoxicity, as did the Australian genotypes.
Discussion A broad range of phytotoxic potential exists within this Brassica germplasm. This work, together with other published studies in rapeseed (Uremis et al. 2009a), rice (Dilday et al. 1994; Seal et al. 2004), and wheat (Wu et al. 2000a), suggests that there is a potential genetic
79
Plant Soil (2014) 380:47–56
53
Fig. 3 Comparisons of annual ryegrass root inhibition indices (%) of napus and non-napus Brassica genotypes as listed in Table 2 (LSD= 10; P<0.05*)
basis to allelopathy. Several attempts have been made to understand the genetic basis of phytotoxicity and to locate genetic markers governing the production of allelochemicals (Dilday et al. 1998; Niemeyer and Jerez 1997). The present study determined that there is substantial variation in allelopathic phytotoxic activity in seedlings of canola genotypes, thereby providing a sufficient gene pool for the development of allelopathic
canola cultivars to suppress weeds, and to track-down the genes controlling the allelochemicals responsible. Canola allelopathy could be a quantitative trait because it is normally distributed across the tested genotypes. However, this needs validation using a segregating population from a cross between extreme parents. Identifying crop cultivars with allelopathic potential is the first step in the process of incorporating the genes involved
Fig. 4 Comparisons of annual ryegrass root inhibition index (%) between Brassica genotypes from different continents (LSD= 10; P<0.05*)
80
54
into competitive, high-yielding cultivars and ultimately becoming a tool in an integrated weed management program. Brassica genotypes showed similar patterns in the density-response curve for annual ryegrass root growth and there was a density by genotype interaction (P< 0.01). This indicates that the agronomic trait of density has a role in canola and other Brassica allelopathy, with higher densities inducing greater inhibition for both weakly and strongly allelopathic genotypes. We confirmed that root elongation of the target species was more affected, than shoot length, by increasing canola density, as found in rice (Navarez and Olofsdotter 1996; Seal et al. 2004) and in wheat (Li et al. 2011). At a high density of Brassica seedlings per beaker, the degree of annual ryegrass root inhibition by all genotypes was significant when compared with the control. At this density the concentration of allelochemicals had extended well beyond the threshold concentration required to produce an effect. Olofsdotter et al. (2002) noted that any compound can be toxic if applied at a high enough dose. A differential allelopathic potential was apparent at the lower density of ten canola seedlings per beaker in Barossa, Cescaljarni-repka and Urvashi. There is a contrary stimulatory effect at very low concentrations of allelochemicals that could complicate any analysis at these low levels (Rice 1984; Streibig 1988). Williamson and Weidenhamer (1990) indicated that the toxicity of allelochemicals depends on their bioactive concentration which is determined by the concentration of allelochemicals at a given point and the flux of toxin in and out of the system. From Fig. 1, it is apparent that there is a genotypic effect in addition to a concentration effect and non-napus genotypes had the potential to be more toxic if used at even higher densities. It is also possible that, if the set of allelochemicals is much the same for all canola genotypes, then the genotypic variation in phytotoxicity is due to the amount of allelochemicals they exude. Both the composition and concentration of these exudates determines their effect. It has yet to be shown whether the differential allelopathic effect is due to different mixtures of exudate compounds or to varying concentrations of the same compounds. The chemical composition of allelochemicals of the canola that impacted on annual ryegrass needs to be determined. In the present research, some of the tested genotypes were non-napus and derived from interspecific hybrids of closely related Brassica species, for example
Plant Soil (2014) 380:47–56
B. napus × B. juncea and B. juncea × B. carinata. It was speculated that non-napus Brassica species may be generally more phytotoxic because of their high glucosinolate content. However, the results of this study do not support that finding because, despite low glucosinolate content (<30 μmol/g oil-free meal), phytotoxicity was high in some of the canola-quality napus genotypes. This implies that napus canola does not necessarily have lower allelopathic activity than non-napus, or vice versa. If adapted napus genotypes have the same phytotoxic potential as more distant relatives, there is more potential to breed for allelopathy without undesirable side-effects. Similar findings have also been reported by Uremis et al. (2009b), demonstrating that the allelopathic activity of Brassica species is not attributable to glucosinolate content, and varies between species. The similar range of allelopathic activity in genotypes originating from different continents suggests that there is no geographical influence on the degree of allelopathy, with a range of strong and weak allelopathic genotypes found within countries and possibly spread worldwide. In the current bioassay the phytotoxic effects on receiver plants are due to allelochemicals via chemicals exuded into the agar medium by Brassica roots. While such laboratory studies can identify key genotypes that possess outstanding phytotoxic potential, the question remains as to whether ECAM results predict field performance. In Australia, in an allelopathy study of rice, Seal et al. (2008) found good conformity between laboratory (using ECAM) and field outcomes. Rice cultivars ranked as allelopathic in the bioassay also performed well in the field and tended to produce lower weed dry biomass. A relatively high correlation coefficient (r=0.84**) was reported when the field outcomes were compared with the ECAM bioassay data (Seal et al. 2008). The identification and quantification of distinct categories of phytotoxic compounds and their complex biochemical pathways through metabolomic approaches is essential. The identification and mapping of genes influencing the production of such chemicals is also an important future direction for canola allelopathy research. Identifying genotypes of varying allelopathic activity allows for the quantification of the biochemical cost of allelopathy (Meiners et al. 2012) by comparing growth rates in the presence and absence of competition, which will provide opportunities to understand the underlying trade-offs related to allelopathy.
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Plant Soil (2014) 380:47–56 Acknowledgments The senior author is very grateful to Charles Sturt University for the award of an International Post Graduate Research Scholarship, and an Australian Postgraduate Award research scholarship.
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56 (Sagittaria montevidensis), an aquatic weed infesting Australian Riverina rice crops. Aust J Agric Res 55:673–680 Streibig JC (1988) Herbicide bioassay. Weed Res 28:479–484 Uremis I, Arslan M, Sangun MK, Uygur V, Isler N (2009a) Allelopathic potential of rapeseed cultivars on germination and seedling growth of weeds. Asian J Chem 21:2170–2184 Uremis I, Arslan M, Uludag A, Sangun MK (2009b) Allelopathic potentials of residues of 6 Brassica species on johnsongrass [Sorghum halepense (L.) Pers.]. Afri J Biotecnol 8:3497– 3501
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Pre-germinated canola seeds on agar surface
Canola seedlings grew alone for 6 days under controlled conditions
Co-growth of canola and annual ryegrass in separated compartment
Appendix I The Equal Compartment Method (Wu et al., 2000) used in the laboratory bioassay. 84
Chapter 6 Research Findings in the Laboratory This component of the research showed a distinct pattern of root growth behaviour in annual ryegrass seedlings in the presence of a neighbouring canola species.
Key contents
ECAM method
Response to density
Response to proximity distance
Active responses
Adaptive mechanism of ryegrass
Paper 4 (research): Asaduzzaman. M., An, M., Pratley, J. E., Luckett, D., & Lemerle, D. (2014f). The seedling root response of annual ryegrass (Lolium rigidum) to neighbouring seedlings of a highlyallelopathic canola (Brassica napus cv. Av-opal). Journal of Ecology [to be submitted].
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The seedling root response of annual ryegrass (Lolium rigidum) to neighbouring seedlings of a highly-allelopathic canola (Brassica napus cv. Av-opal)
Md Asaduzzaman*, Min An, James E. Pratley, David J. Luckett, Deirdre Lemerle
Md Asaduzzaman*, Min An, James E. Pratley, David J. Luckett, Deirdre Lemerle First and Second authors: Faculty of Science, Charles Sturt University, Wagga Wagga, NSW 2650, Australia First, third, fourth and fifth authors: School of Agricultural and Wine Sciences, Faculty of Science, Charles Sturt University, Wagga Wagga, NSW 2650, Australia Fourth author: NSW Department of Primary Industries, Wagga Wagga, NSW 2650, Australia All authors: Graham Centre for Agricultural Wagga Wagga, NSW 2650, Australia
*Corresponding author Email:
[email protected] Telephone: +6169332749
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Abstract Laboratory experiments under controlled conditions were used to examine the avoidance responses of seedling roots of annual ryegrass (Lolium rigidum) to the presence of seedling roots of a highly-allelopathic canola (rapeseed) genotype (Brassica napus cv. Av-opal). The postulated concentration gradient of the canola (donor) allelochemicals was altered by changing the seedling density and/or the proximity in the nutrient-free agar medium. In addition, activated carbon was tested for its ability to nullify the effect of the allelochemicals. The ryegrass (receiver) roots initially grew towards the canola roots but then grew away from them, causing bent or curved growth, and with generally shorter and thicker roots. This effect was greatest at high canola density and at closer proximity but was negated by the addition of activated carbon. These findings add considerable weight to the conclusion that canola rootexuded allelochemicals from certain genotypes are detected by the annual ryegrass roots causing an active response that modifies and inhibits the growth of this significant weed of canola crops. Key words: Allelopathy, allelochemicals, rhizosphere, competition, and neighbor
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Introduction A major challenge facing plant scientists is achieving a greater understanding of the nonresource-driven interactions among plants. Allelopathy is one example of a non-resource plant interaction mechanism in which neighbours are chemically suppressed (Inderjit et al., 1995). The production and the release of biologically active chemical compounds differs between species and between cultivars (Jeffery et al., 2003; Bennett et al., 2004; Keurentjes et al., 2006; Abdel-Farid et al., 2007), although relatively few have strong allelopathic properties (Bhomik and Inderjit, 2003; Khanh et al., 2005; Xuan et al., 2005). Recent research has shown that some genotypes of canola (Brassica napus L., rapeseed, oilseed rape) are strongly allelopathic against weeds, when tested in vitro with annual ryegrass (Lolium rigidum) (Asaduzzaman et al., 2014a). Laboratory rankings were confirmed in the field against several weeds (monocots and dicots) (Asaduzzaman et al., 2014b; Asaduzzaman et al., 2014c). Canola allelopathy seems to be independent of the competitive traits seen in the aboveground morphology, growth and phenology of the crop (Asaduzzaman et al., 2014d), and is a component of the crop’s overall interference ability. High allelopathy, in addition to any beneficial crop competition (Lemerle et al., 2014), will result in desirable crop tolerance of weeds. Allelopathy has been mostly by identification of the allelochemicals being released in bioactive concentrations in root exudates (Einhelling and Leather, 1988; Cheng, 1992). The roots of highly-allelopathic canola genotypes (e.g. cv. Av-opal) exude a small number of unique chemicals into the surrounding rhizosphere (Asaduzzaman et al., 2014e). Weaklyallelopathic genotypes (e.g. cv. Barossa) do not exude these chemicals. Some of these exuded
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chemicals have reported signalling (hormonal) or allelopathic (toxic) effects in other situations. It seems reasonable to postulate that these chemicals exuded from canola roots are indeed having direct allelopathic effects against some weed species. Since the chemicals are exuded into the surrounding rhizosphere there will be an expected concentration gradient as the distance from the source (donor) canola plant roots increases. The gradient seen in soil will depend on many soil factors: physical, chemical and biological (Bias et al., 2006; Foy, 1999; Goodall et al., 2010; Stowe, 1979). This hypothesis for canola allelochemicals still requires testing in appropriate experiments using both pure chemicals and various mixtures. Canola allelochemical concentration, as experienced by the roots of a weed species, can be influenced in two ways: donor plant density (the amount of tissue producing the chemicals), and proximity. It is reasonable to hypothesise that a higher density of canola seedlings will result in a higher allelochemical concentration. It follows that if a weed plant is growing closer to the canola plant(s) then it will experience a higher allelopathic concentration. The work reported in this paper was undertaken to see whether it was possible to observe an allelopathic chemical gradient near the seedling roots of canola. We aimed to observe the seedling roots of an important weed species in response to the canola allelochemicals, and to record differences in root growth and/or direction. We examined the growth patterns of annual ryegrass seedling roots in vitro, when grown in the presence of canola seedlings from the highly-allelopathic Australian cultivar Av-opal. The density of the canola plants was varied, as was the spacing distance (proximity) between the crop and the weed seedlings. Organic molecules can be rendered inactive by the presence of activate carbon (AC) (Mahall and Callaway 1992). We aimed also aimed to see whether 89
the canola allelochemicals were inactivated by the addition of AC to the agar growing medium. Materials and Methods Plant materials Australia’s most prolific winter crop weed, annual ryegrass (Lolium rigidum) was used as test species, and seeds were obtained commercially. Seeds of canola (cv. Av-opal) were obtained from the National Brassica Germplasm Improvement Program, located at the NSW Department of Primary Industries, Wagga Wagga, Australia. Agar (technical grade) and activated carbon were purchased from Sigma Aldrich (St. Louis, USA). Growth conditions For all experiments (1-3), seeds of canola were surface sterilised and pre-germinated before being sown in glass beakers (1000 mL, 12 cm depth, 9 cm diameter) prefilled with 40 mL of 0.3% non-nutrient water agar (Asaduzzaman et al., 2014a). The experimental details are given in Table 1. Experiments 1 and 2 were repeated in their entirety three times. The results were combined in a single analysis for each experiment.
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Table 1. Experimental treatments and layouts Experiment Treatments
Canola densities
Proximities
(plants/beaker)
(cm)
Replication
Layout*
Whole experiment repeats
1
Density
2
Charcoal
3
Density
$
x
0, 5, 10, 20, 30, 40
4
4
4x6
3
0, 5, 10, 20, 30, 40
4
4
4x6
1
0, 5, 10, 20, 30, 40
2, 4
4
4x6x2
3
proximity
$, activated carbon (as charcoal) was either present or absent (see text for details).
Experiment 1: Density A total of 15 pre-germinated annual ryegrass seedlings were placed (4 cm apart from the canola seedlings) in one half of each glass beaker against six-day old seedlings of canola at varying densities (5, 10, 20, 30 and 40 plants/beaker). The beakers were checked frequently to ensure no dead seedling were present in the growth medium. Any seedlings that died were removed. After seven days co-growth, various ryegrass root traits were measured (Table 2).
Experiment 2: Charcoal To confirm the allelopathic effect between canola and annual ryegrass seedlings, 0.2% activated carbon (charcoal) was added to the agar in each beaker just after the beakers were autoclaved. Beakers containing the carbon-agar mix were gently swirled to suspend the activated carbon before the mix was allowed to cool and set. As before, canola seedlings at one of five different densities (5, 10, 20, 30 or 40 plants) were established for 6 days prior to ryegrass being sown into the carbon-containing agar medium. Controls with no carbon added were included in the experiment for each canola density. Ryegrass was sown 4 cm away from the donor canola seedlings.
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Experiment 3: Density x Proximity
Pre-germinated canola seedlings were sown at densities 5, 10, 20, 30 and 40 in beakers and grown for six days before 15 ryegrass pre-germinated seeds were sown either 4 cm or 2 cm apart from the canola. (Fig. 1). Both species were then grown together for seven days as before and then various ryegrass traits were measured (Table 2). Scoring The positions of ryegrass seedling roots were examined by eye against a background that showed the 1 and 2 cm distances from the ryegrass planting line. Roots whose growth had curved through more than 90° were scored as “bent”. After positional scoring, ryegrass roots were removed from the agar medium, rinsed, suspended in water and then scanned at high resolution. The images were then analysed with WinRHIZO software to derive three variables (Table 2). Statistical analysis The number of bent (curled) ryegrass roots, and the number of root intersection at a distance of 1 cm were analysed using the generalized linear mixed model (GLMM). The frequency of ryegrass root tips that reaching between 1 cm and 2 cm from their sowing position, and those >2 cm, were converted to a proportion and analysed by the generalized linear model (GLM). The root surface area and root diameter of ryegrass were analysed by the REML model. For all statistical analysis, Genstat v16 (VSN International, Hemel Hempstead, UK) software was used. Random effects fitted in all analyses were Experiment-repeat and Replicate-withinExperiment. Wald statistics for fixed effects were tested for significance by their approximation to the Chi-squared distribution (Table 3). Treatments means were compared using the least significance difference (LSD) at the 5% probability level (P=0.05). The four 92
proportion or frequency variables (Table 2) were log-transformed prior to analysis. Treatment means are presented here on the back-transformed scale.
Fig. 1. Schematic view of the glass beakers used in experiments. Fifteen pre-germinated seeds of ryegrass were planted after 6 days growth of canola at five different densities in the opposite half of the beaker. Both species (canola and ryegrass) were transplanted into a beaker at the prescribed proximity apart, either: D = 4 cm or 2 cm. Ryegrass root growth was recorded at the 1 cm line, or in in 1-2 and 2-4 cm zones.
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Table 2. Scoring variables, data transformation, and analysis methods for three experiments (see Table 1) examining canola allelopathy against annual ryegrass. Ryegrass trait scored after 7 days of co-
Experiments
How scored
Transformation
growth with canola Proportion of bent (curved) root tips (> 90°) in 2 cm zone* Frequency of root tips >1 cm and <2 cm from planting line Frequency of root tips >2 cm from planting line Proportion of root intersections at 1 cm from the planting line Total surface area of 10 seedling roots (cm2) Mean root diameter of 10 seedling roots (cm)
Fitted
Analysis method**
distribution 1, 2, 3
Visual
Log
Poisson
GLMM
3
Visual
Log
Binomial
GLM
3
Visual
Log
Binomial
GLM
3
Visual
Log
Poisson
GLMM
3
WinRHIZO
none
Binomial
REML
3
WinRHIZO
none
Binomial
REML
* any ryegrass roots that initially grew below the planting line (i.e. away from the canola) were excluded from these counts. Consequently, bent-root counts are expressed as a proportion out of some number <= 15; $, WinRHIZO image analysis software (manufacturer name. location); **, GLM = generalised linear model, GLMM = generalised linear mixed model, REML = residual maximum likelihood.
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Table 3. Analysis summary of fixed effects fo seven ryegrass seedling traits (see Table 2) measured after 7 days variously in three canola allelopathy experiments (see Table 1). Experiment 1
Trait Proportion of bent roots (> 90°) in 1-2 cm zone
Fixed effect Density
df 5
Wald statistic 635.40 *** (P<0.001)
2
Proportion of bent roots (> 90°) in 1-2 cm zone
Density Charcoal Density x Charcoal
5 1 5
NS (P=0.432)
3
Proportion of bent roots (> 90° ) in 1-2 cm zone
Density Proximity Density x Proximity Density Proximity Density x Proximity Density Proximity Density x Proximity Density Proximity Density x Proximity Density Proximity Density x Proximity
5 1 5 5 1 5 5 1 5 5 1 5 5 1 5
1436.70 *** (P<0.001) 62.51*** (P<0.001)
Frequency of root tips in 1-2 cm zone
Proportion of root intersections at 1 cm from planting line Total root surface area of 10 seedling roots (cm2)
Mean diameter of 10 seedling roots (cm)
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40.99 *** (P<0.001)
638.61 *** P<0.001) 234.21 *** (P<0.001) 310.98 *** (P<0.001) 1220.22 *** P<0.001) 122.21 *** (P<0.001) 60.41 *** (P<0.001) 27.65 *** (P<0.001) 0.64 *** (P<0.001) 11.25 *** (P<0.001)
Results All fixed effects for all traits in all experiments were highly significant (Table 3), except for Density x Charcoal in Experiment 2.
Experiment 1: Density At low canola density (5 seedlings/beaker), the lowest number of ryegrass roots showed the bent response. At the highest density of canola (40 seedlings/beaker) many ryegrass roots became bent and avoided all contact with the canola roots or growth towards them. Under medium canola density (20 seedlings/beaker), although some ryegrass roots reached the canola territory and physically touched canola roots, the vast majority first grew towards the canola territory and then changed their growth direction by >90° and up to 180° to grow away from the canola (Fig. 2).
a
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b
c
d
Fig. 2. (a) Frequency of bent ryegrass roots (>90° angle) at three densities of canola (cv. AV-Opal) transplanted at 4 cm away from ryegrass. LSD (5%) = 1.7. Photographic and diagrammatic representation of active ryegrass root behaviour and growth at (b) low, 5 canola plants/beaker (c) medium, 20 and (d) high, 40. In all cases annual ryegrass is in the lower half of each beaker and canola is in the upper half (Variation is expressed as SE ± ; P<0.001). In the diagrams, the canola seedlings are omitted to make the ryegrass root shapes clearer.
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Fig. 3. Number of ryegrass roots curled (around 180° angle) [in agar medium mixed with activated charcol (0.2%)] by five densities [0(control), 5, 10, 20, 30 and 40 seedlings/beaker] of canola (cv. Av-opal) transplanted at 4 cm apart before ryegrass. (LSD = 0.86).
Fig. 4. The total number of ryegrass roots curled (>900° angle) by six densities of canola (cv. Av-opal) transplanted at 4 cm and 2 cm apart. LSD (5%) = 0.28. 96
Fig. 5. Proportion of ryegrass root tips position at 2 cm from ryegrass sowing position to canola (cv. Av-opal) for 2 and 4 cm sowing distance between canola and ryegrass. Experiment 2: Density x Charcoal
In the presence of activated carbon (charcoal), the frequency of bent ryegrass roots was greatly decreased even at high density of neighbouring canola. The addition of activated carbon negated the canola effect irrespective of the canola sowing density (Fig. 3).
Experiment 3: Density x Proximity This experiment
also demonstrated the bent behaviour of ryegrass root as in
Experiment 1 but with the additional effect that at the closer proximity to canola (2 cm v 4 cm) the effect was significantly magnified (Fig. 4). For both proximities the frequency of bent ryegrass roots was still increased with increased neighbouring 97
canola density (P<0.001). At 30 and 40 canola seedlings/beaker at a sowing proximity of only 2 cm, most ryegrass roots limited their growth to within a very small region close to their planting site.
Fig. 6. The number of ryegrass roots, bent and non-bent) intersectingwith the 1 cm scoring line between the ryegrass and canola sowing positions (see Figure 1). LSD (5%) = 0.36. When ryegrass was transplanted 4 cm away from the high density canola, significantly (P<0.001) fewer ryegrass roots (both bent and un-bent) were present close to the canola roots than when sown with a low number of canola. In particular, at 5 canola seedlings/beaker, about 94% of ryegrass root tips were present in the zone 1 cm from the ryegrass towards the canola territory. At a density of 40 seedlings/beaker, about 60% root tips were present in that 1 cm zone (Fig. 5), and this proportion was further decreased to 39% when ryegrass was planted within 2 cm of canola. Under such conditions, most of the root tips were situated in close 98
proximity to the ryegrass sowing position even when their initial growth had been behind the ryegrass sowing line (i.e. directly away from the canola).
Table 4. Allelopathic effect of canola seedling density and proximity on ryegrass root morphology measured in Experiment 3. The ryegrass traits were measured via image analysis using WinRHIZO software.
Root surface area of ryegrass Canola
ryegrass
density
(cm2/10 roots) at 2 cm distance
Root diameter of annual
(cm/10 roots) at 4 cm distance
at 2 cm distance at 4 cm
distance 0
17.27
17.50
0.28
0.28
5
14.98
14.46
0.32
0.31
10
13.12
13.91
0.33
0.28
20
9.97
12.78
0.35
0.30
30
8.98
12.01
0.38
0.36
40
8.05
10.79
0.35
0.36
LSD (density x distance)
0.75, P<0.001**
0.5, P<0.001**
*Sowing distance between canola and annual ryegrass was 2 cm and 4 cm Root (both bent and non-bent) intersection counting data showed that ryegrass roots grew directly towards the 4 cm line when 5 seedlings/beaker of canola were present and there was very little bending. Most roots reached the predefined 1 cm distance towards canola (Fig. 6). At 40 canola seedlings planted 2 cm away, the lowest number of ryegrass roots grew towards canola (P<0.001), remaining instead close to their sowing position. Ryegrass placed at the 4 cm distance from 5 canola
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seedlings/beaker had larger root surface area with smaller root diameter than those grown at the 2 cm distance from 40 canola seedlings/beaker (Table 4). Discussion Our first experiment (repeated three times) showed that annual ryegrass roots initially grew towards the strongly-allelopathic canola seedlings but then grew in a curved way to distance themselves from the canola. This ryegrass response was greater with higher densities of canola and when the canola was growing closer to the ryegrass. This density and proximity response disappeared when activated carbon (AC) was added to the growth medium, and presumably, acted to neutralise or inactivate the organic allelochemicals. Organic chemicals are adsorbed onto the AC, the concentration of free molecules is reduced, and they can no longer exert their allelopathic effect to the same degree (Mahall and Callaway 1992). Here AC ameliorated the neighbouring effects of canola roots exudates and provides evidence for chemically-mediated interactions among the roots. Mahall and Callaway (1992) found that AC diluted the negative effects that Larrea sp. roots had on each other and on the roots of Ambrosia dumosa. Belliveau and Callaway (2001) found that roots of Festuca idahoensis grew significantly slower as they approached the roots of Centaurea maculosa, but AC added to the soil minimised the effects of Centaurea maculosa. All the evidence presented here suggests that shortened root length of ryegrass and bent growth pattern behaviour were active responses to canola root exudates containing allelochemicals The root-placement patterns of plants grown with different types of neighbours vary between species and factors additional to resource depletion are likely to be involved in their development (Semchenko, John & Hutching, 2007). In this study, at a high 100
density of canola, roots of ryegrass became bent without any physical contact with the roots of canola. In contrast, they intermingled at a low density of canola. This indicates that density has a role for inducing more root exudates and greater inhibition of neighbours. At high canola densities, the concentration of allelochemicals exceeds the threshold required to produce an effect in ryegrass roots. The lack of physical contact with hetero-specific neighbouring roots further strengthens the likelihood that this behaviour is due to canola root exudates, where both composition and concentration of these exudates determines their effect. It has yet to be shown whether the observed allelopathic effect is due to a mixture of exudate compounds, or to varying concentrations of the same compound. Our conclusions that crop allelochemicals are responsible for the weed response is also supported by recent findings in Deschampsia caespitosa (Semchenko, Saav & Lepik, 2014). We speculate that the change in the rhizosphere conditioned by neighbouring canola root exudates is sensed by the roots of ryegrass, which activates an internal physiological signalling pathway. This alerts the ryegrass seedlings to the presence of hetero-specific neighbours causing growth patterns of avoidance characterised by curled or bent root shapes. Hodge (2009) reported that root systems have recognisable developmental plans when grown in solution or agar. The modular structure of roots enables them to respond to their environment, and roots are very adaptive at modifying growth throughout the root system to concentrate their efforts in the areas that are the most profitable.
In our experiments a limited number of ryegrass roots still grew towards and touched canola roots possibly due to inherent tolerance in some individuals. This merits further investigation and may reflect the out crossing nature of ryegrass and its 101
consequential genetic heterogeneity. The bent root responses of sensitive ryegrass was not due to competition for light, nutrients or water because the growth chamber ensured plentiful light for both species and the transparent agar employed was nonnutritive. It demonstrates, therefore, that roots of ryegrass actively responded to the toxic chemicals of canola seedlings released into the agar matrix. The strength of these chemical compositions varied with canola density. Because higher density of neighbouring donor living plants is known to increase the amount of allelochemicals (Belz, Hurle & Duke, 2005), the increased canola density enhanced allelopathic inhibition of root growth of ryegrass and caused more extreme avoidance growth (Asaduzzaman et al. 2014a). Close proximity of the two root systems reduced the count number of ryegrass root intersections. A study by Wu et al. (2007) reported that allelopathic root exudates of wheat in ECAM were more inhbitory when receiver ryegrass was sown close to wheat seedlings. Similary, in our study, the curvature responses of ryegrass to two different canola sowing proximity indicates that diffusion occurs in the agar gel medium. Thus ryegrass root segregation was induced by the concentrations of canola root exudates diffusions in the medium rather than by physical contact. The adoption by ryegrass of avoidance-type growth (curled roots) took place only when roots of ryegrass reached a critical distance from the canola roots and their diffusing chemical signals. These results may suggest that active sensitivity or recognition ability is present in ryegrass roots and curled response to the presence of a heterospecific dissimilar neighbour and their density-driven chemical signals.
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Plants depend on their dynamic and industrious root systems to provide nutrients and water to the rest of the plant (Biedrzycki and Bais, 2010), often competing with other plants for these necessities. From an agricultural point of view it is not particularly important whether or not hetero-specific detection (or identification or recognition) is occurring between the crop and the weed (in this case canola and ryegrass). What is important is that the net effect of the two-way interaction results in poorer growth for the weed species and better growth, or at least maintained growth, for the crop species. The crop yield will then be more likely to be maintained at an economic level, while weed biomass (resource ‘wastage’) and weed seed recruitment are minimised. Furthermore a negative influence on the weed species might be detected as a simple reduction in root length (as was shown in our previous in vitro study) (Asaduzzaman et al.,
2014a). In the field it can be shown via reduced weed
incidence, reduced weed biomass, reduced weed seed-set, etc. (Asaduzzaman et al., 2014c). As the growth medium provided no nutrition to the seedlings, growth was limited to the seed reserves present at germination and removed responses due to resource detection. Seedlings were grown for a short period and no seedling death from inadequate nutrition occurred. Seedling cotyledon leaves remained green and well-hydrated throughout. It has long been hypothesised that toxic and non-toxic signals between roots occur (Caldwell, Nabwaring & Durham, 1996; Lund 1947). Distinguishing between the effects of toxins and non-toxin signals is challenging (Schenk, Callaway & Mahall, 1999) but there is growing evidence that toxic allelochemicals contribute to active root growth pattern leading to avoidance of nonself neighbours (Hodge 2009). Whether this canola-ryegrass interaction is a signalling response (canola-to-ryegrass) or a direct toxic effect (or both) has not been established by this work. It may remain a moot point in a commercial field situation. 103
It seems likely that the production and secretion of allelochemicals will have a biochemical penalty. If signalling allelochemical molecules are effective at much lower concentrations that toxic molecules, then the production of signalling chemicals may be the most desirable option in new, improved canola cultivars, provided that a broad range of weed species are susceptible. Many studies have examined toxic properties of root exudates in plant-plant interaction by mean of allelopathy (reviewed in Schenk, Mahall & Callaway, 1999; Bais et al., 2006; Inderjit et al., 2011). Olofsdotter et al. (2002) noted that any bioactive compound can be toxic if applied at a high enough dose but there can also be a contrary stimulatory effect at very low concentrations of some allelochemicals (Rice 1974). Our findings indicate that canola shows allelopathy to receiver ryegrass and that the weed is able to initiate to avoidance growth to try and minimise exposure to the toxic exudates of hetero-specific neighbours. Collectively these studies suggest that where a healthy ryegrass seedling root encounters canola allelochemicals in the rhizosphere we can envisage several possible responses including, cessation of growth and possible seedling death (an extreme response), change in direction of root growth (down the allelochemical concentration gradient), reduction in root length, and/or a change in root diameter (leading to a change in root volume). There may be other changes in the root morphology of the receiver species but this requires further work. In addition, the allelochemical interaction is a two-way dynamic. In our experiments we gave canola a head-start in the contest by establishing it before the weed. We need to investigate whether ryegrass shows greater resilience if it is given a headstart over the crop. If nutrients (N, P, and K for example) are added to the medium, will this change the interference dynamic? 104
ACKNOWLEDGEMENTS We thank Charles Sturt University (CSU) Australia, for the award of an International Post Graduate Research Scholarship, an Australian Postgraduate Award research scholarship and Writing up Award. We are indebted to New South Wales Department of Primary Industry, Wagga Wagga, Australia for providing laboratory facilities. We thank Neil Coombes, New South Wales Department of Primary Industry, Wagga Wagga, Australia for statistical analysis. The authors wish to thank the anonymous reviewers of another journal for their valuable comments on an earlier version of this manuscript.
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Belz, R,, Hurle, K. & Duke, S. O. (2005) Dose-response- a challenge for allelopathy? Nonlinearity 3,173-211 Bennett, R. N., Rosa, E. A. S., Mellon, F. A., & Kroon, P. A. (2006). Ontogenic profiling of glucosinolates, flavonoids and other secondary metabolites in Eruca sative, Diplotaxis erucoides, Diplotaxis tenuifolia and Bunias orientalis. Journal of Agricultural food chemistry, 54, 4005-4015. Bhowmik, P. C., & Inderjit. (2003). Challenges and opportunities in implementing allelopathy for natural weed management. Crop Protection 22, 661-671. Biedrzycki, M. L. & Bais, H. P. (2010). Kin recognition in plants: a mysterious behaviour unsloved. Journal of experimental Botany, 15, 423-428. Caldwell, M. M., Nabwaring, J. H. & Durham, S. L. (1996) Species interactions at the level of fine roots in the field: Influences of soil nutrient heterogenicity and plant size. Oecologia, 106, 440-447. Einhellig, F. A. & Leather, G. A. (1988). Potential for exploiting allelopathy to enhance crop production. Journal of Chemical Ecology,14, 1829-1844. Foy, C. (1999). Principles and practices in Plant Ecololgy: How to make bioassays for allelopathy more relevant to field conditions with particular reference to cropland weeds. Newbury: UK. Goodall, J., Witkowski, E. F., Ammann, S., & Reinhardt, C. (2010). Does allelopathy explain the invasiveness of Campuloclinium macrocephalum (pompom weed) in the South African grassland biome? Biological Invasion, 12, 3497-3512. Hodge A (2009) Root decisions. Plant Cell Environ 32: 628-640 Inderjit, Daskshini, K. M. M. & Einhellig, F. A. (1995). Allelopathy: organism process and application. ACS symposium series. Vol 1582. American chmeical Society, Wasington DC. Inderjit, Wardle, D. A., Karban, R. & Callaway, R. M. (2011) The ecosystem and evolutionary contexts of allelopathy. Trends in Ecological Evaluation, 26, 655-662 Jeffery, E. H., Brown, A. F., Kurilich, A. C., Keck, A. S., Matusheski, N., Klein, B. P. & Juvik, J. A. (2003). Variation in content of bioactive components in broccoli. Journal of Food Commodities Analysis, 16, 323-330. doi: 10.1016/S0889-1575(03)00045-0 Keurentjes, J. J. B., Fu, J. Y., De Vos, R. C. H., Lommen, A., Hall. R. D., Bino, R. J., Van der Plas, L. H., Jensen, R. C., Vregugdenhil, D. & Koornneef, M. (2006). The genetics of plant metabolisms. Nature Genentics,. 38, 842-849 Khanh, T. D., Chung, M. I., Xuan, T. D. & Tawata, S. (2005). The exploitation of crop allelopathy in sustainable agricultural production. Journal of Agronomy and Crop Science, 191, 172-184 106
Lemerle, D., Luckett, D.J., Lockley, P., Koetz, E. & Wu, H. (2014) Competitive ability of Australian canola (Brassica napus) genotypes for weed management. Crop & Pasture Science Submitted & Revised, Lund, E. J. (1947) Bioelectric fields and growth. The University of Texas Press,Texas Mahall, B. E. & Callaway, R. M. (1991) Root communication among desert shrubs. Proceedings of National Academic of Sceicne USA, 88, 874-876 Mahall, B. E. & Callaway, R.M. (1992) Root communication mechanism and intracommunity distributions of two major desert shrubs. Ecology, 73, 2145-2151 Olofsdotter, M., Jensen, L. & Courtois, B. (2002) Improving crop competitive ability using allelopathy—an example from rice. Plant Breeding, 121, 1-9 Rice, E. L. (1974) Allelopathy, 1st edn. Academic, Orlando Schenk, H. J., Callaway, R. M. & Mahall, B. E. (1999) Spatial root segregation: are plants territorial? Advces Biological Research, 28, 146-180 Semchenko, M., John, E. A. & Hutchings, M. J. (2007) Effects of physical connection and genetic identity of neighbouring ramets on root-placement patterns in two clonal species. New Phytologist, 176, 644-654 Semchenko, M., Saar, S. & Lepik, A. (2014) Plant root exudates mediate neighbour recognition and trigger complex behaviour changes. New Phytologist, [in press] Stowe, L. G. (1979). Allelopathy and its influence on the distribution of plants in an Illinois old-field. Journal of Ecology, 67, 1065-1085. Wu, H., Pratley, J. E., Lemerle, D., An, M. & Liu, D. (2007) Autotoxicity of wheat (Triticum aestivum L.) as determined by laboratory bioassays. Plant and Soil, 296, 85-93 Xuan, T. D., Shinkichi, T., Khanh, T. D. & Chung, I. M. (2005). Biological control of weeds and plant pathogens in paddy rice by exploiting plant allelopathy: an overview. Crop Protection, 24, 197-206
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Chapter 7 Research Findings in the Field
A total of 312 canola genotypes were screened to assess their allelopathic activity in the field. The allelopathic potential of 36 common canola genotypes measured in the laboratory was correlated with the field study results. A further follow-up experiment was conducted with six extreme genotypes at two different sowing times.
Key contents
Field experiment in 2012 o
312 genotypes
o
Natural weed population
o
Plant height vs weed infestations
o
Weed infestation vs grain yield
o
Correlation between laboratory and the field
Field experiment in 2013 o
4 extreme allelopathic and 2 extreme competitive genotypes
o
Two Sowing times (early and late)
o
Artificially sown annual ryegrass plus natural weeds
o
Crop biomass vs weed biomass
o
Grain yield and quality vs weed infestations
o
Reduced rosette diameter of E. plantagineum
Field experiment 2012 vs 2013
Appendix
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Paper 5 (research): Asaduzzaman, M., Luckett, D. J., Cowley, R. B., Min, A., Pratley, J. E., & Lemerle, D. (2014). Canola cultivar performance in weed-infested field plots confirms allelopathy ranking from in vitro testing. Journal of Biocontrol Science and Technology DOI: org/10.1080/09583157.2014.942596.
Conference paper 3: Asaduzzaman, M., Luckett, D. J., Min, A., Pratley, J. E., & Lemerle, D. (2014). Management of Paterson’s curse (Echium plantagineum) through canola interference. Proceedings 19th Australasian Weed Conference, 1st -4th September, Hobart, Tasmania, pp162-165. Conference paper 4: Asaduzzaman, M., Luckett, D. J., Min, A., Pratley, J. E., & Lemerle, D. (2014). Evaluation of canola (Brassica napus L) allelopathy: from laboratory to field. Proceedings 7th World Congress on Allelopathy, 28th July-1st August, Vigo, Spain, p. 162.
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Biocontrol Science and Technology, 2014 Vol. 24, No. 12, 1394–1411, http://dx.doi.org/10.1080/09583157.2014.942596
RESEARCH ARTICLE Canola cultivar performance in weed-infested field plots confirms allelopathy ranking from in vitro testing Md Asaduzzamana,b,c*, David J. Luckettc,d, Raymond B. Cowleyc,e, Min Anb,c, James E. Pratleya,c and Deirdre Lemerlea,c a
School of Agricultural and Wine Sciences, Charles Sturt University, Wagga Wagga, NSW, Australia; bFaculty of Science, Charles Sturt University, Wagga Wagga, NSW, Australia; c Graham Centre for Agricultural Innovation (an alliance between Charles Sturt University and NSW Department of Primary Industries), Wagga Wagga, NSW, Australia; dNSW Department of Primary Industries, Wagga Wagga, NSW, Australia; eDuPont Pioneer, Wagga Wagga, NSW, Australia (Received 3 April 2014; returned 13 May 2014; accepted 4 July 2014) Crop competition and allelopathy are two cultural control options for possible inclusion in cropping systems. This research aimed to identify superior allelopathic canola genotypes through a two-year field study. First year screening results of 312 diverse Brassica genotypes showed genotypes differed significantly in their ability to suppress weed infestations. Crop plant height was correlated with the competitive ability of several genotypes, while other genotypes showed good weed-suppressive ability despite being short. Thirty-six of the genotypes grown in the field had been previously assessed for their allelopathic ability to inhibit the growth of annual ryegrass (Lolium rigidum) seedlings using an in vitro technique. The highly allelopathic genotypes: Av-opal, Sardi603, Rivette and Atr-beacon performed well against annual ryegrass in the laboratory and also against other species, including Capsella bursapastoris, Sisymbrium orientale and Hordeum leporinum in the field. The weakly allelopathic Barossa and X-06-6-3725 genotypes performed poorly both in the laboratory studies and in the field. The following year, field testing of selected genotypes at two sowing dates further suggested that the most allelopathic genotypes in the laboratory bioassay were generally those that suppressed weed numbers and their biomass in the field. The late sowing time increased the natural weed pressure leading to a decrease in both canola grain yield and quality. Many of the highly allelopathic canola genotypes, which caused low weed populations in the field, had relatively low grain yield. This suggests that the allelopathic trait is independent of local adaptation and yields potential under weed-free conditions. Ideally, cultivars with both high allelopathy and high competitive ability would be most useful to help farmers maximise yield and control weeds. Selection for allelopathy in canola shows potential as a future non-chemical weed control option and requires further investigation. Keywords: Brassica napus; genotypes; weeds; interference; competition; allelopathy
*Corresponding author. Email:
[email protected];
[email protected] © 2014 Taylor & Francis
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Biocontrol Science and Technology Introduction Canola (Brassica napus L.) is a major oilseed crop widely grown across southern Australia. The availability of improved varieties, crop agronomy packages, market demand and high grain prices has led to a rapid expansion of this crop in Australia (Australian Oilseeds Federation, 2013). However, weeds remain a constraint to canola production due to the cost of herbicides and the threat of resistance, and yield and quality losses where weeds are inadequately controlled. Annual ryegrass (Lolium rigidum), vulpia (Vulpia myuros) and wild oat (Avena spp.) are the most important grass weeds affecting canola production in southern Australia (Lemerle, Blackshaw, Smith, Potter, & Marcroft, 2001). Brassicaceous weeds are difficult to control in canola; and Lemerle et al. (2001) found that wild radish (Raphanus raphanistrum) was still present in 13% of the canola fields after all weed management practices were completed. Heavy infestations of wild radish can reduce canola yields by up to 90% (Blackshaw, Lemerle, Mailer, & Young, 2002), and such infestations greatly reduce the quality of canola meal by direct seed contamination (Blackshaw et al., 2002; Cheam & Code, 1995). The pressing need for the effective control of weeds (especially wild radish) led to the rapid adoption of herbicide-tolerant crop technology, particularly triazine-tolerance (TT), in both open-pollinated and hybrid cultivars, despite the known yield penalty of the TT trait (Walsh, Duane, & Powles, 2001). The persistent use of herbicides in herbicide-tolerant canola varieties has encouraged weeds to evolve herbicide resistance (Beckie et al., 2011; Heap, 2002; Powles, Lorraine-Colwill, Dellow, & Preston, 1998). For example, the widespread use of TT canola cultivars in Australia has led to an increase in resistant populations of wild radish (Heap, 2014). Imidazolinone-tolerant (IT) canola, while avoiding the yield penalty of TT, has produced a large number of imidazolinone-resistant weed populations (Preston, Roush, & Powles, 1999). Similarly, the introductions of glyphosate-tolerant GM canola raise concerns about the build-up in glyphosateresistant weeds in Australia (Heap, 2014). Such weeds and glyphosate-resistant cultivars have greater potential to become problems as volunteer crops than do conventional crops (Cerdeira & Duke, 2006). Under such situations, the control of both weeds and volunteer canola plants may become more troublesome. These challenges have focussed attention on the possibility of using non-chemical control tactics in weed management strategies. Suppression of weeds by a crop is an important tactic for weed management. Plant interference can be separated into competition and allelopathy. Competition occurs in live plant communities when two or more plants seek a common resource within limited space, such as mineral nutrients, light and water (Harper, 1977). In canola, strong competitive ability can be due to varieties with high early vigour, increased height or a denser canopy (Zand & Beckie, 2002). In contrast, allelopathy is the direct or indirect negative effect of one plant on another through the production of secondary metabolites that are released into the immediate environment (Rice, 1984). The impact of genetic differences of crop allelopathy against weeds has been assessed under laboratory conditions in rice (Dilday, Yan, Moldenhauer, & Gravois, 1998; Seal, Pratley, Haig, & Lewin, 2004), wheat (Wu, Pratley, Lemerle, & Haig, 2000), rapeseed (Uremis, Arslan, Sangun, Uygur, & Isler, 2009) and recently in canola (Asaduzzaman, Min, Pratley, Luckett, & Lemerle, 2014).
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M. Asaduzzaman et al. However, it is important to demonstrate that such observed in vitro allelopathy effects also occur under field conditions. In the field, organic toxins produced by an allelopathic species can be rendered harmless by the combined interactions of soil texture, organic matter, temperature, irradiance and microbial breakdown (Bais, Weir, Perry, Gilroy, & Vivanco, 2006; Blum, Shafer, & Lehman, 1999; Foy, 1999; Goodall, Witkowski, Ammann, & Reinhardt, 2010; Stowe, 1979). Due to the complexity of field interactions and responses, a laboratory bioassay alone does not adequately demonstrate that allelopathy is operational in the field (Inderjit & Weston, 2000; Olofsdotter, Navarez, Rebulanan, & Streibig, 1999). Few studies have attempted to correlate laboratory and field results, and most allelopathy experiments fail to take this crucial step of in-field validation. However, linking laboratory and field results goes some way to explaining the possible allelopathic performance of crop cultivars. There are no previous reports of field studies of allelopathy in canola. The overall aim of this study was to identify superior competitive and/or allelopathic Brassica genotypes which suppressed weeds under field conditions; and to relate field performance to published rankings of allelopathy in canola (Asaduzzaman et al., 2014) from an in vitro bioassay.
Materials and methods Experimental site The field experiments were conducted at the Agricultural Institute, NSW Department of Primary Industries, Wagga Wagga, NSW, Australia (35°30′07″S; 147°21′06″ 0E) in a duplex Red Kandosol of pH 5.3. The experiment in 2012 was grown as part of the National Brassica Germplasm Improvement Program. Field experiment 2012 Plant materials and experimental layout A set of 312 diverse Brassica genotypes comprised: 112 breeding lines, 107 current and historic cultivars from national and international collections, 74 germplasm accessions and 15 commercial F1 hybrids. Two genotypes, OasisCL and Mitre503 are B. juncea (Indian mustard). Roy100-99W1 and Roy40-99W1 are derived from an interspecific cross of B. napus × B. juncea, and the remainder was B. napus (rapeseed, canola). Some commercial genotypes are identified only by a code indicating their involvement in the Australian National Variety Trials (NVT). The experiment was sown on 23 May with 140 kg ha 1 of Grain-u-Lok fertiliser treated with the fungicide (fluquinconazole, Farmoz) to protect against the fungal disease blackleg (Leptosphaeria maculans). Foliar applications of prothioconazole and tebuconazole were applied at the 2-leaf and 6-leaf stages to further protect against blackleg. Urea (46% N) was applied on 8 August at 50 kg ha 1. DiGGeR design software (Coombes, 2002) was used to arrange three replicates in a spatially optimised layout of 24 ranges × 39 rows. All plots were 10 m long and 1.8 m wide with 8 rows (row to row distance was 20 cm). Each plot was sown with an accurately counted number (1500) of fresh seeds that had been stored under ideal conditions. The autumn weather at sowing was unusually warm and this greatly reduced the efficacy of the pre-sowing trifluralin herbicide, resulting in a uniform and high weed infestation of several weed species such as shepherd’s purse (Capsella
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Biocontrol Science and Technology bursa-pastoris), Indian hedge mustard (Sisymbrium orientale), barleygrass (Hordeum leporinum) and annual ryegrass. Grain yield was harvested on 3 December, using a small-plot header (Kingaroy Engineering, Kingaroy, QLD, Australia). General measurements on 312 genotypes The time of 50% canola flowering of each genotype was recorded (late September to mid October) for each genotype. After 50% flowering, the level of weed infestation was scored in each plot using a score of 0 (nil weeds) to 5 (high weed numbers). At the same time, visual scores were made for crop height (1 = short, 2 = medium and 3 = tall). Just before harvest, average crop plant heights (60–150 cm) to the top of the canopy (pods) were also measured. Detailed measurements on 36 genotypes Based on previous laboratory studies (Asaduzzaman et al., 2014), 36 canola genotypes were chosen from 312 genotypes for more detailed observations (Table 1). The weedsuppressive performance of the selected 36 genotypes was assessed against different weed species. Canola density (average, 75 plants m−2), weed diversity and frequency of each weed species were counted in each plot using a random quadrate of 1 m2 over three days, with one replicate completed per day. Weed diversity and frequency were summarised using Simpson’s Diversity Index (SDI; Simpson, 1951). SDI is used to quantify biodiversity in ecological studies. It takes into account the number of species P present, as well as the abundance of each species: SDI ¼ 1 n Nðn1Þ ðN 1Þ, where n is the total number of plants of a particular species and N is the total number of all weed species. SDI values (%) for the 36 canola genotypes were correlated with the inhibition index from the laboratory bioassay (Asaduzzaman et al., 2014), which used annual ryegrass as the target weed species. The inhibition index values for the respective genotypes are provided in Table 1. Field experiment 2013 Plant materials and experimental layout Based on 2012 results, the 2013 experiment used six canola genotypes. Previous field and laboratory screening results showed that among the six genotypes Av-opal and Pak85388-502 were strongly allelopathic, while Atr-409 and Barossa were weakly allelopathic. The other two genotypes were chosen based on a previous canola competition study by Lemerle, Lockley, Koetz, Luckett, and Wu (2011): Av-garnet was strongly competitive and Cb-argyle was weakly competitive with weeds in that study. In order to vary the weed/crop dyanamics, two sowing dates were included four weeks apart. Furthermore, to ensure the presence of at least one weed species, 40 seeds m−2 of annual ryegrass were sown simultaneously with 80 canola seeds m−2 in both sowing times. Sowing dates were 12 May (commercial recommended sowing time) and 11 June. Fertiliser and fungicide treatments were as for year 2012. The experimental area was previously a barley crop for grain and no herbicide was used after the barley harvest and during the canola growing season. The experimental layout of each sowing date was designed by DiGGER design software (Coombes, 2002). The individual plot size was 10 m × 1.8 m and rowto-row distance was 20 cm as in 2012. Each genotype had adjacent paired plots (each
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M. Asaduzzaman et al. Table 1. The 36 canola (Brassica napus) genotypes chosen from 312 genotypes for detailed study in a field experiment in 2012.
ID
Genotype
Inhibition index (%) in laboratory
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
Av-opal Sardi603 Atr-beacon Rivette Bau-m-58-501 BLN4143 Surpass400 Ag-outback Dong-hae-18-501 BLN3343-C00401 BLN3343-C00402 Tarcoola-1 Monty Skipton Charlton Taiwan-2-501 Azuma-501 Sardi607
55 49 49 47 45 44 44 44 43 42 42 42 42 41 41 38 37 37
ID
Genotype
Inhibition index (%) in laboratory
19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36
Buk-wuk-13-501 Iwao-natane-502 Ukraine-c-501 Tarcoola-191 Tarcoola-22 Tarcoola-21 Rafal-502 Cb-telfer BLN3614 Ag-spectrum Atr-cobbler Topas BLN4135 BLN4139 Tarcoola-141 X-06-3725 Maluka Barossa
37 36 36 36 35 34 34 33 32 32 29 28 26 22 21 17 16 8
Note: Genotypes with strong allelopathic activity will have high inhibition index values whereas low values indicate weak or no activity. These data mere originally published in Asaduzzaman et al. (2014).
10 m long and 1.8 m width), where one plot of each genotype was used for all destructive measurements including crop and weed plant biomass assessment. To maximise experimental precision, there were six replications. Measurements At 75 days after sowing, the level of weed infestation was scored in each plot using a score of 0 (nil weeds) to 5 (high weed numbers) as in 2012. At the same time, canola density (average 77 plants m−2) weed diversity, and frequency of each weed species was measured (plants m−2). Canola and weed above-ground biomass were sampled using a quadrate of 1 m2 from the first plot of each genotype on 12 and 26 September for early and late sowing times. The weed flora comprised annual ryegrass, barley grass, vulpia (Vulpia sp), Paterson’s curse (Echium plantagineum), shepherd’s purse and wireweed (Polygonum aviculare). Biomass samples were weighed combined after drying in a ventilated dehydrator at 80°C for 72 hrs. The second plot of each genotype was used for machine harvest of final grain yield and grain yields from both sowing times were obtained on 22 November, 2013 using a small-plot header. Quality analysis Harvested canola seed was cleaned to remove pods, stem and other debris and then seed protein, oil and glucosinolate concentrations were determined using a near
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Biocontrol Science and Technology infrared reflectance spectrometer (Foss Model 6500, Foss NIR system Inc. Silver spring, MD, USA) after adjusting seed moisture levels to 6% for oil and glucosinolates and 13% for protein. Statistical analysis All data of 2012 and 2013 were subjected to analysis of variance (ANOVA) using Genstat v16 (VSN International, Hemel Hempstead, UK) and the restricted maximum likelihood analysis model, where fixed effects = genotype, random effects = replication + range + row) and fixed effects = genotype, random effects = replication + range) respectively. The treatment means were compared using the least significance difference (LSD). Plots of residual versus fitted values were examined for all traits to ensure that the assumptions of ANOVA were met.
Results Significant (P < 0.001) effect of treatments and their interactions (genotypes, plant height and biomass) were observed on weed infestations in both years (Table 2). Field experiment 2012 The 312 Brassica genotypes differed significantly in their weed-suppressive ability, with genotype mean weediness scores ranging from 0.26 to 4.4 (P < 0.001) (Figure 1). Several genotypes exhibited a strong ability to suppress weeds under these field conditions: NVT-1, Av-opal, Sardi607, Mitre503, Roy100-99W1, Pak85388502, Sardi603, BLN3343-CO04002, U1104 and China-D-501 were the ten best genotypes, each with a weediness score of less than one (Table 3). In contrast, Atr-409, Agt-346, 95-17033-2, TP003, Flinders-TTC, 06-P71-1, 05-P71-11, NVT-2, Atr-eyre and Cb-boomer had high levels (P < 0.001), weediness score greater than three. Brassica flowering time differed significantly between genotypes but had no significant effect on weed infestation (data not shown). Crop height differed significantly (P < 0.001) between genotypes and was related to weediness score (Figure 1). Genotypes Roy40-99W1, Mitre503, OasisCL, Roy100-99W1, Ding 474, QU1104, Ukraine-501, Fan168, Norin 41-502 and Saron-CN1866 were the 10 tallest genotypes, whereas NVT-3, NVT-4, TPO03, Atr-becon, TN6, Sardi1524TT, Hurricane-TT, NVT-5, Rainbow and NVT-6 were the shortest (Table 3). However, even though crop vigour was not measured, we observed that the F1 hybrids tended to be more vigorous at the vegetative stage. The taller genotypes were not always the most weed-suppressive. TT genotypes generally had more weeds than other genotypes (Figure 1). The grain yield (t ha−1) differed significantly (P < 0.001) among the 312 Brassica genotypes, but was not always negatively correlated with that genotype’s level of weed infestation. Some of the TT and open-pollinated genotypes had high yields relative to the hybrids. The maximum grain yield was produced by NVT-7 followed by Hyola76, Monty, Hyola50, Tarcoola-27 and NMC130, which were all only moderately infested by weeds (Figure 2). In the more detailed study of 36 Brassica napus genotypes, four different weed species (shepherd’s purse, Indian hedge mustard, barleygrass, and annual ryegrass) were commonly present but in widely varying frequency depending upon the
M. Asaduzzaman et al. Table 2. Statistical significance of canola genotype, crop height, flowering time and biomass effect.
Year 2012
2013
Component Weediness score (0–5) Crop height (cm) Crop flowering time (days) Grain yield (t ha−1) Crop density (plants m−2) Crop density (plants m−2) Early sowing Late sowing Annual ryegrass density (plants m−2) Early sowing Late sowing Weed density (plants m−2) Early sowing Late sowing Crop biomass (g m−2) Early sowing Late sowing Weed biomass (g m−2) Early sowing Late sowing Oil content (%) Early sowing Late sowing Protein content (%) Early sowing Late sowing Glucosinolates content(µ mol g−1) Early sowing Late sowing
df
mean
Genotype
311 311 311 311 311
2.26 109 110 0.62 70
* * * * NS
5
72 63
NS NS
5
6 6
* *
5
39 56
* *
5
429 310
* *
5
116 183
* *
5
38 35
* NS
5
41 43
* NS
5
22 24
* *
*Significance difference; NS, not significance difference.
Brassica genotype. Annual ryegrass was present in the plots of only four genotypes (BLN4135, Tarcoola-22, Topas and X06-06-3725), while shepherd’s purse was detected with all canola genotypes (Figure 3); densities were highest in BLN4139 [32] and BLN4135 [31]. The lowest densities of shepherd’s purse were in Av-opal [1], Rivette[4] and Sardi607[18], Sardi603[2], Tarcoola-1[12] and BLN3343-CO0402[11]. The highest frequencies of Indian hedge mustard were in Barossa [36], BLN4135 [31], Cb-telfer [26] and Maluka [35] (Figure 3); whereas, Surpass 400 [7], Donghae-18-501 [9], Charlton [15], Tarcoola-191[22] and BLN4143 [6] were least infested by Indian hedge mustard. Sardi603 [2] and Atr-beacon [3] had zero Indian hedge mustard plants present. The density of barley grass also varied between canola genotypes (Figure 3). Barossa was infested by the highest level of barley grass individuals. In contrast, Charlton was infested by a very low frequency of barley grass, and Rivette had none of this weed present.
Biocontrol Science and Technology
Figure 1. Relationship between genotype means of weediness score (where 0 nil weeds to 5 = high weed numbers) and crop height score (1 = short, 2 = medium and 3 = tall) of 312 Brassica genotypes grown in field conditions with a high weed infestation (O = Openpollinated, ▼= Triazine-tolerant and ● = Hybrid genotypes). Data are from ANOVA. Genotypes found in the bottom-left quadrant are likely to be allelopathic.
The infestation levels of the three weed species were reflected in the calculated values of SDI, which ranged from 0.1 to 0.49. (P < 0.001) (Figure 4). A significant correlation co-efficient of 0.77 (P < 0.001) was obtained when the SDI value from these field data was compared with the inhibition indices (%) from the in vitro bioassay (Asaduzzaman et al., 2014). Several of the genotypes identified as the most allelopathic in the bioassay, such as Av-opal, Sardi603, Rivette and Atr-beacon, also performed well under field conditions, while Barossa, and X-06-6-3725 [34] were consistently poor in both field and laboratory experiment (Figure 4). Field experiment 2013 Significant (P < 0.001) differences between genotype were found in order of their weed-suppressive ability (Table 2). The weed infestations for each genotype were higher in the late sowing than in the early sowing. Genotypes Av-opal, Pak85388502 and Av-garnet performed well against all weed species in contrast to Atr-409, Cb-argyle and Barossa which showed less impact on total weed populations at both sowing dates (Figure 5 and Plate 1). Separately counted ryegrass number was significantly higher in Barossa followed by Atr-409, and Cb-argyle particularly in the late sowing (Figure 6). Crop above-ground biomass was significantly (P < 0.001) greater in Pak85388502, Av-opal, Av-garnet and Barossa compared with Atr-409 and Cb-argyle which had low biomass (Figure 7). The weed biomass varied from 21 to 228 g m−2 in the early and from 78 to 297 g m−2 in the late sowing depending on genotype. Av-opal and Pak85388-502 plots contained significantly less weed biomass (P < 0.001) while Atr-409, Cb-argyle and Barossa had higher weed biomass in both sowing
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M. Asaduzzaman et al. Table 3. Twenty Brassica genotypes out of 312 tested in the field at Wagga Wagga, Australia in 2012, showing the 10 least weed-infested genotypes (top 10) and the 10 most weed-infested genotypes (bottom 10). Genotype NVT-1 Av-opal Sardi607 Mitre503 Roy100-99W1 Pak85388-502 Sardi603 BLN3343-CO0402 Qu1104 China-d-501 CB-boomer Atr-eyre NVT-2 05-p71-11 06-p71-1 Flinders-TTC TP003 95-17033-2 Agt346 Atr-409 LSD (P < 0.001)
Weediness score (0–5)
Crop height (cm)
Time of 50% flowering (days)
Yield (t/ha)
0.25 0.34 0.39 0.49 0.53 0.56 0.62 0.72 0.72 0.73 3.83 3.89 4.00 4.04 4.06 4.10 4.11 4.15 4.20 4.44 1.31
113.67 102.00 109.34 140.00 136.68 123.34 113.34 105.01 131.67 112.34 99.39 102.68 79.00 98.39 119.39 102.39 86.68 97.01 95.34 100.34 13.9
104 107 104 106 102 105 104 104 109 108 112 107 104 120 150 114 108 108 109 114 3
0.76 0.75 0.77 0.80 0.73 0.78 0.62 0.53 0.67 0.55 0.64 0.38 0.49 0.32 0.60 0.62 0.45 0.58 0.64 0.68 0.30
Note: Genotype differences were highly significant (P < 0.001) for weed infestation crop height, time of flowering and grain yield. Weediness score, 0 = nil weeds to 5 = high number of weeds.
times. Weed biomass in early sowing was lower than in late sowing by 25, 30 and 35% in Atr-409, Cb-argyle and Barossa, respectively. The regression analysis model for both sowing dates showed that weed biomass was negatively correlated with canola biomass. Canola grain yield, oil and glucosinolate contents differed among genotypes (P < 0.001) in both sowing times. Av-garnet and Av-opal produced the highest seed yields (Table 4). The seed yields of all genotypes were almost 50% lower in the late sowing time. Despite the high weed-suppressive ability, Pak85388-502’s yield was low compared with the other strongly competitive or allelopathic genotypes in both sowing times indicating its lack of local adaptation for yield. Canola grain oil content (%) varied with genotypes in either sowing times. The protein and glucosinolates content increased with increased weed pressure in late sowing. Differences in glucosinolate levels were found among genotypes. The concentration of this chemical increased in all genotypes except Av-garnet in late sowing. The high concentration of glucosinolates was present in Pak85388-502 followed by Cb-argyle, while low concentrations were found in Av-opal.
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Figure 2. Correlations between canola weediness score (0–5 scale) and grain yield for 312 Brassica genotypes grown in a field plot experiment at Wagga Wagga in 2012. For illustration simplicity the majority of the genotypes are plotted as solid points; however, selected extreme genotype are plotted using their genotypes name (centred).
Figure 3. Weed density (plants m−2) of shepherd’s purse, Indian hedge mustard (plants m−2) and barley grass growing in the field in 2012 with 36 different canola genotypes. Names refer to the genotypes listed in Table 1 (LSD = 67, 17 and 19; P = 0.05 for shepherd’s purse, Indian hedge mustard and barley grass, respectively).
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Figure 4. Correlation between in vitro laboratory screening (% inhibition index) using annual ryegrass as the weed species (Asaduzzaman et al., 2014), and weed infestation under field conditions (Simpson Diversity Index) at Wagga Wagga in 2012. Numbers refer to the 36 Brassica napus genotypes listed in Table 1.
Figure 5. Total weed density (plants m−2) in six canola genotypes at early and late sowing times in the field in 2013 (LSD = 9 and 16, respectively; P = 0.05).
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Plate 1. (Colour online) Photos depicting the weed interferences in weak (left: cv. Atr-409) and strong (right: cv. Av-opal) canola genotypes in 10-m long plot in 2013.
Over the two years, the weed-suppressive trend of the selected six canola genotypes was consistent. Av-opal and Pak85388-502 performed well either year and significant correlations exist between weediness score in 2012 and 2013 (Figure 8).
Figure 6. Annual ryegrass density (plants m−2) in six canola genotypes at early and late sowing times in 2013. The solid line is the 1:1 relationship between the early and late sowing. Weed densities in the genotypes is plotted using genotype name (centred).
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Figure 7. The relationship between canola and weed above-ground biomass at early (a) and late (b) sowing times of six canola genotypes in 2013. The plotted regression line illustrates the overall negative relationship. Genotypes are plotted using their name (centred).
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Biocontrol Science and Technology Table 4. Canola grain yield and quality at two different sowings dates in 2013 as influenced by various naturally growing weeds. Yield (t ha−1) Genotype Atr-409 Av-garnet Av-opal Barossa Cb-argyle Pak85388–502 LSD (P < 0.001)
% oil
% Protein
Glucosinolates (µ mol g−1)
Early sowing
Late sowing
Early sowing
Late sowing
Early sowing
Late sowing
Early sowing
Late sowing
0.353 0.993 0.970 0.762 0.349 0.449 0.05
0.105 0.464 0.414 0.231 0.105 0.190 0.05
37.22 38.99 40.80 36.64 36.95 37.79 0.96
35.42 36.05 36.88 33.68 34.34 35.17 1.41
41.17 38.45 42.43 40.04 41.38 41.56 1.0
43.46 40.41 44.00 42.16 43.04 42.72 1.5
9.85 10.94 3.36 17.10 16.70 76.51 2.35
13.45 10.45 4.19 16.08 22.46 77.80 3.35
Discussion Crop competition is influenced by plant morphological traits such as plant height and early growth rate (Bastiaans, Kropff, Kempuchetty, Rajan, & Migo, 1997; Kropff, Kotz, & Weaver, 1993). In this study, a significant negative correlation was seen between Brassica plant height and weed infestation and several Brassica genotypes had good weed-suppressive ability due to their vigorous growth and high plant height. The straightforward conclusion for these genotypes is that their weedsuppressive ability is due to strong crop competitive ability. However, some hybrids
Figure 8. Relationship between weed-suppressive performances/score of six canola genotypes in the field: a comparison between results in 2012 and 2013. The upper (r = 0.89**) and lower (r = 0.92**) line illustrates the early and late sowing correlation with weediness score in 2012, respectively. Genotypes are plotted using their name (centred), where non-italic and italic fonts represent the early and late sowing time, respectively.
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M. Asaduzzaman et al. were not exceptionally competitive, and some short genotypes achieved very high weed suppression. This was also reflected in grain yield, where some genotypes were clearly poorly adapted to the local conditions (they had low grain yields) and yet still produced plots with very low weed numbers, for example cv. Av-opal. These observations are strongly indicative of allelopathy rather than competition, especially when the finding is supported by in vitro assay results. Evidence of a crop’s chemical interference of weed growth (allelopathy) has been reported in an evaluation of 111 genotypes of rice (Olofsdotter et al., 1999). Rice allelopathic potential was not correlated with plant height (Olofsdotter & Navarez, 1996), root biomass (Jensen et al., 2001) or any other competitive trait (Olofsdotter et al., 1999). However, plant height can be a component of competitive ability by reducing light penetration for weeds and their production of biomass (Bastiaans et al., 1997; Pierik, Millenaar, Peeters, & Voesenek, 2005). In wheat, plant height was correlated with cultivar weed-suppressive ability (Lemerle, Verbeek, Cousens, & Coombes, 1996). Since weed-suppressive ability in Brassica is strongly influenced by genotype, this suggests that the amount and type of allelochemicals produced will also vary with genotype. Previous reports using Brassica nigra revealed a high concentration of a putative allelopathic agent sinigrin, which affected the targeted weed species (interspecific interference) but did not adversely affect like-individuals (intra-specific interference) (Lankau, 2008). Canola genotypes responded differently to the same weed species, presumably due to selective allelopathic action from a specific chemical mode-of-action which may not act on the other weeds. In rhizospheric research, it has been reported that root-secreted chemicals and their quantity may deter one species while attracting another (Bais et al., 2006; Pierik, Mommer, & Voesnek, 2013). Furthermore, often plants do not secrete just one substance but a mixture of chemicals which is highly species-specific or even ecotype-specific (Pierik et al., 2013). The determination of the individual active chemicals, and the genes encoding those chemicals, is worthy of further study for potential application in canola breeding and for the production of new herbicides. Canola genotypes ranked as allelopathic in the bioassay resulted in less weed pressure and tended to produce lower weed biomass than even the strongly competitive genotype (cv. Av-garnet). Genotypes such as Av-opal, Pak85388-502, Av-garnet and Barossa produced similar plant biomass but weed infestations differed greatly between them. Weed-suppressing genotypes thus have potential and further work is needed to produce a genotype with combined competitive ability and allelopathy. In Australia, Seal, Pratley, and Haig (2008) showed that 8 of the top 10 rice allelopathic cultivars in the bioassay were among the top 10 suppressive cultivars in the field. Bertholdsson (2010) found mean early weed biomass was significantly lower in the highly allelopathic wheat lines compared with the non allelopathic lines. Unfortunately, the high allelopathic lines were also significantly lower yielding than the lower allelopathic lines. Similarly in our study, it is unclear what causes the low yield observed in some highly allelopathic genotypes (e.g. Pak85388-502, Bau-m-58-501, Atr-becon and Sardi603). Is it due to simply poor adaption or to some fitness penalty due to the production of allelochemicals? The yield reduction of canola genotypes in late sowing demonstrated that environment influenced canola-weed interference by reducing the tolerance of weed
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Biocontrol Science and Technology pressure in all genotypes, particularly in Pak85388-502. This suggests that it is important to evaluate the allelopathic potential of canola genotypes under varying environmental variable climatic conditions before an allelopathic cultivar is recommended for general use. The yield reduction due to weed pressure was not common for all genotypes. Thus weed tolerance capability of canola may be due to a genotype’s specific trait. It appears that the yield potential, plant height, TT-status and flowering time are all independent of a Brassica genotype’s ability to suppress weeds via allelopathy, although some may remain relatively weed-free due to high competitive ability. A combination of both mechanisms should result in genotypes with a substantial yield advantage. Dilday et al. (1998) successfully developed a high-yielding rice line with moderate allelopathic activity to duck salad (Heteranthera limosa) using simple crossing and selection thereby showing the trait to have relatively simple genetic control. Maintaining crop yield under weed pressure and weed supression are two different mechanisms of crop competition (Lemerle et al., 2001). It has been reported that canola crop tolerance to weeds varies between genotypes (Lemerle et al., 2010). In our study, these differences can be due to the combination of a genotype’s competitive and allelopathic mechanisms as, in the field, both phenomena occur together but are difficult to identify and quantify separately (Olofsdotter et al., 1999). Farmers and canola breeders require that high-yielding genotypes with enhanced weed-suppressing ability be developed without sacrificing other desirable agronomic traits. The findings of this work suggest that the breeding of canola cultivars with enhanced competitiveness coupled with high allelopathy is possible. The economics of such breeding, and the cost-savings to farmers after adoption, need to be determined. In this study, weed suppression by canola genotypes under field conditions was due to negative interference either via competition or allelopathy or both. However, the outcomes described here suggest there is sufficient information to plan a genetic cross between a high allelopathic and low competitive genotype and a low allelopathic and high competitive genotype to study the genetic control of these traits. The next step in this research is to understand the mechanisms of canola allelopathy including identifying the allelochemicals responsible and their genetic control. Acknowledgements We thank the Grains Research and Development Corporation of Australia for partly funding the National Brassica Germplasm Improvement Program (NBGIP) project. Various commercial canola breeding companies are thanked for providing seed of their cultivars present in the National Variety Testing (NVT) scheme. We thank David Roberts and Peter Deane for technical assistance.
References Asaduzzaman, M., Min, A., Pratley, J. E., Luckett, D. J., & Lemerle, D. (2014). Canola (Brassica napus) germplasm shows variable allelopathic effects against annual ryegrass (Lolium rigidum). Plant and Soil, 380(1 & 2), 47–56. Australian Oilseeds Federation (AOF). (2013). Crop report (Report No. September 2013). Mulwala, NSW: Author. Retrieved from www.australianoilseeds.com/oilseeds
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M. Asaduzzaman et al. Bais, H. P., Weir, T. L., Perry, L. G., Gilroy, S., & Vivanco, J. M. (2006). The role of root exudates in rhizosphere interactions with plants and other organisms. Annual Review, 57, 233–266. Bastiaans, L., Kropff, M. J., Kempuchetty, N., Rajan, A., & Migo, T. R. (1997). Can simulation models help design rice cultivars that are more competitive against weeds? Field Crops Research, 51, 101–111. doi:10.1016/S0378-4290(96)01046-5 Beckie, H. J., Harker, K. N., Legere, A., Morrison, M. J., Swartz, G. S., & Falk, K. C. (2011). GM canola: The Canadian experience. Farm Policy, 8, 43–49. Bertholdsson, N.-O. (2010). Breeding for spring wheat for improved allelopathic potential. Weed Research, 50, 49–57. doi:10.1111/j.1365-3180.2009.00754.x Blackshaw, R. E., Lemerle, D., Mailer, R., & Young, K. R. (2002). Influence of wild radish on yield and quality of canola. Weed Science, 50, 344–349. doi:10.1614/0043-1745(2002)050 [0344:IOWROY]2.0.CO;2 Blum, U., Shafer, S. R., & Lehman, M. E. (1999). Evidence for inhibitory allelopathic interactions involving phenolic acids in field soils: Concepts vs. an experimental model. Critical Review of Plant Science, 18, 673–693. doi:10.1016/S0735-2689(99)00396-2 Cerdeira, A. L., & Duke, S. O. (2006). The current status and environmental impacts of glyphosate-resistant crops: A review. Journal of Environmental Quality, 35, 1633–1658. doi:10.2134/jeq2005.0378 Cheam, A. H., & Code, G. R. (1995). The biology of Australian weeds. 24. Raphanus raphanistrum L. Plant Protection Quarterly, 10, 1–13. Coombes, N. E. P. T. (2002). The reactive tabu search for efficient correlated experimental design (PhD thesis). Liverpool John Moores University, Liverpool. Dilday, R., Yan, W., Moldenhauer, K., & Gravois, K. (1998). Allelopathy in rice: Allelopathic activity in rice for controlling major aquatic weeds. Manila: International Rice Research Institute. Foy, C. (1999). Principles and practices in plant ecology: How to make bioassays for allelopathy more relevant to field conditions with particular reference to cropland weeds. Newbury: CRC Press. Genstat v16 (VSN International, Hemel Hempstead): Bioscience software and consultancy, Herts. Goodall, J., Witkowski, E. F., Ammann, S., & Reinhardt, C. (2010). Does allelopathy explain the invasiveness of Campuloclinium macrocephalum (pompom weed) in the South African grassland biome? Biological Invasion, 12, 3497–3512. doi:10.1007/s10530-010-9747-2 Harper, D. (1977). Population biology of plants. London: Academic Press. Heap, I. (2002, September). Herbicide resistance – Australia versus the rest of the world. 13th Australian Weeds Conference, Perth. Heap, I. (2014). International survey of herbicide resistant weeds. Retrieved from www. weedscience.org Inderjit, & Weston, L. A. (2000). Are laboratory bioassays for allelopathy suitable for prediction of field responses? Journal of Chemical Ecology, 26, 2111–2118. doi:10.1023/ A:1005516431969 Jensen, L. B., Courtois, B., Shen, L., Li, Z., Olofsdotter, M., & Mauleon, R. P. (2001). Locating genes controlling allelopathic effects against barnyardgrass in upland rice. Agronomy Journal, 93, 21–26. doi:10.2134/agronj2001.93121x Kropff, M. K., Kotz, L., & Weaver, S. E. (1993). Practical applications in modelling crop-weed interactions. Wallingford: CAB International. Lankau, R. (2008). A chemical trait creates a genetic trade-off between intra- and interspecific competitive ability. Ecology, 89, 1181–1187. doi:10.1890/07-1541.1 Lemerle, D., Blackshaw, R. E., Smith, A. B., Potter, T. D., & Marcroft, S.T. (2001). Comparative survey of weeds surviving in triazine-tolerant and conventional canola crops in south-eastern Australia. Plant Protection Quarterly, 16, 37–40. Lemerle, D., Lockley, P., Koetz, E., Luckett, D., & Wu, H. (2011, August). Manipulating canola agronomy for weed suppression. 17th Australian Research Assembly on Brassica, Wagga Wagga. Lemerle, D., Lockley, P., Luckett, D., & Wu, H. (2010, September). Canola competition for weed suppression. 17th Australasian Weed Conference, Christchurch.
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Biocontrol Science and Technology Lemerle, D., Verbeek, B., Cousens, R. D., & Coombes, N. E. (1996). The potential for selecting wheat varieties strongly competitive. Weed Research, 36, 505–513. doi:10.1111/ j.1365-3180.1996.tb01679.x Olofsdotter, M., & Navarez, D. (1996). Allelopathic rice for Echinochloa crus-galli control. 2nd International Weed Control Conference, Copenhagen. Olofsdotter, M., Navarez, D., Rebulanan, M., & Streibig, J. C. (1999). Weed-suppressing rice cultivars – does allelopathy play a role? Weed Research, 39, 441–454. doi:10.1046/j.13653180.1999.00159.x Pierik, R., Millenaar, F. F., Peeters, A. J. M., & Voesenek, L. A. C. J. (2005). New perspectives in flooding research: The use of shade avoidance and Arabidopsis thaliana. Annals Botany, 96, 533–540. doi:10.1093/aob/mci208 Pierik, R., Mommer, L., & Voesnek, L. A. C. J. (2013). Molecular mechanisms of plant competition: Neighbour detection and response strategies. Functional Ecology, 27, 841–853. doi:10.1111/1365-2435.12010 Powles, S. B., Lorraine-Colwill, D. F., Dellow, J. J., & Preston, C. (1998). Evolved resistance to glyphosate in rigid ryegrass (Lolium rigidum) in Australia. Weed Science, 46, 604–607. Preston, C., Roush, R. T., & Powles, S. B. (1999, September). Herbicide resistance in weeds of Southern Australia: Why are we the worst in the world? 12th Australian Weeds Conference, Tasmanian. Rice, E. L. (1984). Allelopathy. London: Academic Press. Seal, A. N., Pratley, J. E., & Haig, T. (2008). Can results from a laboratory bioassay be used as an indicator of field performance of rice cultivars with allelopathic potential against Damasonium minus (starfruit)? Australian Journal of Agricultural Research, 59, 183–188. doi:10.1071/AR06333 Seal, A. N., Pratley, J. E., Haig, T., & Lewin, L. G. (2004). Screening rice varieties for allelopathic potential against arrowhead (Sagittaria montevidensis), an aquatic weed infesting Australian Riverina rice crops. Australian Journal of Agricultural Research, 55, 673–680. doi:10.1071/AR03238 Simpson, E. H. (1951). The interpretation of interaction in contingency tables. Journal of the Royal Statistical Society, 13, 238–241. Stowe, L. G. (1979). Allelopathy and its influence on the distribution of plants in an Illinois old-field. The Journal of Ecology, 67, 1065–1085. doi:10.2307/2259228 Uremis, I., Arslan, M., Sangun, M. K., Uygur, V., & Isler, N. (2009). Allelopathic potential of rapeseed cultivars on germination and seedling growth of weeds. Asian Journal Chemistry, 21, 2170–2184. Walsh, M., Duane, R., & Powles, S. (2001). High frequency of chlorsulfuron-resistant wild radish (Raphanus raphanistrum) populations across the Western Australian wheat belt. Weed Technology, 15, 199–203. doi:10.1614/0890-037X(2001)015[0199:HFOCRW]2.0.CO;2 Wu, W., Pratley, J., Lemerle, D., & Haig, T. (2000). Evaluation of seedling allelopathy in 453 wheat (Triticum aestivum) accessions against annual ryegrass (Lolium rigidum) by the equalcompartment-agar method. Australian Journal of Agricultural Research, 51, 937–944. doi:10.1071/AR00017 Zand, E., & Beckie, H. (2002). Competitive ability of hybrid and open-pollinated canola (Brassica napus) with wild oat (Avena fatua). Canadian Journal Plant Science, 82, 473–480. doi:10.4141/P01-149
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Management of Paterson’s curse (Echium plantagineum) through canola interference Md. Asaduzzaman1,3,4, David J. Luckett2,4, Min An3,4, James E. Pratley1,4, and Deirdre Lemerle1,4 1 School of Agricultural and Wine Sciences, Faculty of Science, Charles Sturt University, Wagga Wagga, NSW 2650, Australia 2 Department of Primary Industries, Wagga Wagga, NSW 2650, Australia 3 Faculty of Science, Charles Sturt University, Wagga Wagga, NSW 2650, Australia 4 Graham Centre for Agricultural Innovation, Wagga Wagga, NSW 2650, Australia (
[email protected])
Summary Canola is a major oilseed crop in Australia but weeds reduce yield and quality. Paterson’s curse (Echium plantagineum L.) is an aggressive winter weed in Australia and often causes yield losses in canola crops. The prospects of herbicide resistance in weed species necessitate the search for alternative weed control options, such as canola interference (crop competition and allelopathy). A field experiment was conducted with two different sowing times, to investigate the interference ability of six canola genotypes. The results showed that canola genotypes had an effect on the number of E. plantagineum plants in the early sowing. Genotypes that display strong interference such as Av-opal, Pak85388-502 and Av-garnet significantly reduced the vegetative growth of E. plantagineum at both early and late sowing times, while genotypes Atr409, Cb-argyle and Barossa showed a much weaker interference ability. Keywords Canola, allelopathy, competition, sowing time.
Competition is the negative interaction between two or more plant species for resources (e.g. light, water and nutrients) within a limited space (Donald 1963). In contrast, allelopathy is a mechanism where a plant gives itself a competitive advantage by placing phytotoxins into the adjacent environment to reduce the viability of competitors (Pratley 1996). The phenomenon varies with plant species, cultivar, growth stage and various stress factors but overall is gaining interest among weed scientist as a tool for weed suppression. Furthermore, in the field situation both competition and the allelopathy phenomenon act collectively (Olofsdotter et al. 1999). Thus, canola cultivars with strong weed-suppressing ability, as a result of optimising both competitive and chemical interference, could become an important tool for weed management. We hypothesed that canola shows interference ability against Paterson’s curse under a field environment via competition and allelopathy or both.
INTRODUCTION Canola is the third largest broadacre crop in Australia (Zhang et al. 2011). It provides the additional rotational benefits of a disease break and some options to control weeds (Norton 2003). Despite of modern blackleg resistance varieties (Cowling 2007), weeds are still a major cost to canola production. Paterson’s curse (E. plantagineum) is a common and aggressive weed in canola fields in southern Australia (Lemerle et al. 2001). It produces prolific quantities of dormant seed and has robust vegetative growth (Naughton et al. 2006) and can significantly reduce the yield of canola. Chemical herbicides are an effective tool to control Paterson’s curse but herbicides have other negative impacts with evolves resistant in weeds. In such circumstances, crop interference becomes a potential weed control tool. Crop interference involves the combined effect of crop competition and allelopathy (Zimdahl 2007).
MATERIALS AND METHODS Plant materials Six canola genotypes were selected for this study. Previous field and laboratory screening results showed that among the six genotypes Avopal and Pak85388-502 are strongly allelopathic, while Atr409 and Barossa are weakly allelopathic (Asaduzzaman et al. 2014). The other two genotypes were chosen based on a previous canola competition study by Lemerle et al. (2011): Av-garnet was strongly competitive, Cb-argyle was weakly competitive. To investigate the influence of environmental factors two different sowing dates were used. All seed was obtained from the National Brassica Germplasm Improvement Program, located at New South Wales Department of Primary Industries, Wagga Wagga, Australia. The early and late sowing was done on 12 May and 11 June 2013 respectively with 140 kg ha−1 of Grain-u-Lok fertiliser treated with the fungicide Jubilee (fluquinconazole, Farmoz) to protect against 1
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RESULTS Effect of canola interference on Paterson’s curse density At 90 days after sowing, the number of Paterson’s curse plants was significantly different between the genotypes in the early sowing (P <0.001) but not in late sowing. In the early sowing, the highest number of Paterson’s curse plants were recorded under the genotype Atr409 followed by Barossa, Cb-argyle and Av-garnet. In contrast, a much lower number was recorded with Av-opal and Pak85388-502 (Figure 1). Effect of canola interference on Paterson’s curse rosette diameter For both sowing dates, canola genotypes differentially reduced weed vegetative growth. Strong interference by some canola cultivars such as Av-opal and Pak85388-502, significantly reduced the weed rosette diameter by 55 cm and 51 cm respectively, relative to the weak (Figure 2). The vegetative growth of Paterson’s curse was increased in the late sowing compared to the early sowing time, but still varied significantly between canola genotypes (P <0.001). It was also observed that with the weak allelopathic or competitive genotypes, Paterson’s curse emerged early and produced more reproductive organs early (in October 2013), whereas its reproductive 2
LSD (5%)
8 6 4 2
2 850
le
38
Pa k
Genotypes
85
sa
bar gy
C
Ba ro s
al
t
Av -o p
rn e
09
0 AV -g a
Measurement and statistical analysis At ninety days after sowing (DAS) of canola, the number of Paterson’s curse plants was counted (plants per plot). In addition, the diameter of five random rosettes per plot was measured. Data from two different sowing dates was analysed separately. All data of field experiments were subjected to analysis of variance using Genstat v16 (VSN International, Hemel Hempstead, UK) using the REML analysis model where fixed effects = genotypes, random effects = replication + range + row. Treatments means were compared using the least significance difference (LSD) at a 5% level of probability. Plots of residual versus fitted values were examined for all traits to ensure that the assumptions of analysis of variance were met.
10
At r4
Experimental design The experimental layout of each sowing date was designed by DiGGER design software (Coombes, 2002). The individual plot size was 10 m × 1.8 m and row-to-row distance was 20 cm. To maximise experimental precision, each genotype was replicated six times.
12
Figure 1. Number of Paterson’s curse plants present under six canola genotypes at an early sowing time.
160 LSD (5%)
140
Atr409
Cb-argyle Barossa AV-garnet
Late sowing
the fungal disease Blackleg (Leptosphaeria maculans). The experimental area was previously a barley crop grown for grain. No herbicide was used after barley harvest and during canola was grown.
Number of Paterson’s curse (plants plot−1)
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120 100 Pak85388-502 Av-opal
80 60
10
20
30
40
50
Early sowing
60
70
80
Figure 2. The rosette diameter (cm) of Paterson’s curse plants under six canola genotypes at early and late sowing times.
stage was delayed (in December 2013) by the strong allelopathic and competitive genotypes (Figure 3). DISCUSSION Early sowing of canola established a greater competitive advantage over Paterson’s curse relative to late sowing in some genotypes. Farmers who sow canola relatively late are likely to require a pre-sowing knockdown herbicide (e.g. glyphosate) to ensure that any established weeds are killed prior to the sowing. Some canola genotypes showed strong interference by reducing the diameter of Paterson’s curse rosettes. This suggests that canola competition and allelopathy
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Figure 3. Flowering stage of Paterson’s curse in 10 m long × 1.8 m wide plots of suppressive (left) (Avopal) and less suppressive (right) canola genotypes (Barossa) in 2013 at Wagga Wagga. In the Av-opal plot there were no flowering Paterson’s curse plants visible. On the right, there are many Paterson’s curse plants visible (purple flowered plants).
tactics can be applied to reduce the weed pressure in the field. It can be argued that impact of canola interference on Paterson’s curse rosette size may not influence the weed competitive ability and seed production. However, any reduction in weed vigour is an advantage (Cousens and Mortimer 1995). The use of high interference canola genotypes may, therefore, have an important long-term effect on the Paterson’s curse weed population in a canola rotation. Combined early sowing and strong canola interference is likely to have a major effect on Paterson’s curse. ACKNOWLEDGMENTS We thank David Roberts for technical assistance. The field trial was partially funded by GRDC through project DANØØ1Ø8. REFERENCES Asaduzzaman, M., Min, A., Pratley, J.E., Luckett, D.J. and Lemerle, D. (2014). Canola (Brassica napus) germplasm shows variable allelopathic effects
against annual ryegrass (Lolium rigidum). Plant and Soil (in press). Coombes, N. (2002). The reactive tabu search for efficient correlated experimental design, PhD thesis, Liverpool John Moores University. Cousens, R. and Mortimer, M. (1995). ‘Dynamics of weed populations’. (Angus and Robertson, Cambridge University Press). Cowling, W.A. (2007). Genetic diversity in Australian canola and implications for crop breeding for changing future environments. Field Crops Research 104, 103-1. Donald, C.M. (1963). Competition among crop and pasture plants. In ‘Advances in agronomy’, ed. C.M. Donald, pp. 46-51. (Academic Press, London). Lemerle, D., Blackshaw, R.E., Smith, A.B., Potter, T.D. and Marcroft, S.J. (2001). Comparative survey of weeds surviving in triazine-tolerant and conventional canola crops in south-eastern Australia. Plant Protection Quarterly 16, 37-40. 3
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Nineteenth Australasian Weeds Conference Lemerle, D., Lockley, P., Koetz, E., Luckett, D. and Wu, H. (2011). Manipulating canola agronomy for weed suppression. Proceedings of the 17th Australian Research Assembly on Brassicas, pp. 181-3. (New South Wales Department of Primary Industries). Naughton, M., Kidston, J., Sullivan, P. and Bourke, C. (2006). Paterson’s curse. New South Wales Department of Primary Industries. Primefact 109, pp. 1-12. Norton, R.M. (2003). Conservation farming systems and canola. (University of Melbourne, Melbourne, Victoria).
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Olofsdotter, M., Navarez, D., Rebulanan, M.S. and Streibig, J.C. (1999). Weed-suppressing rice cultivars – does allelopathy play a role? Weed Research 39, 441-54. Pratley, J.E. (1996). Allelopathy in annual grasses. Plant Protection Quarterly 11, 213-14. Zhang, H., Berger, J.D. and Milroy, S.P. (2011). Genotype × environment interaction of canola (Brassica napus L.) in multi-environment trials. Proceedings of the 17th Australian Research Assembly on Brassicas, pp. 50-6. (New South Wales Department of Primary Industries). Zimdahl, R.L. (2007). ‘Fundamentals of weed science’. (Academic Press, London).
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7th World Congress on Allelopathy. Vigo, July 28 – August 1, 2014
Evaluation of canola (Brassica napus) allelopathy: from laboratory to field Md. Asaduzzaman1,3*, David J Luckett2,3, Min An3,4, James E Pratley1,3, and Deirdre Lemerle1,3 1
School of Agricultural and Wine Sciences, Faculty of Science, Charles Sturt University, Wagga Wagga,
NSW 2650, Australia *e-mail:
[email protected] 2
NSW Department of Primary Industries, Wagga Wagga, NSW 2650, Australia
3
Graham Centre for Agricultural Innovation (an alliance between Charles Sturt University and NSW
Department of Primary Industries), Wagga Wagga, NSW 2650, Australia 4
Faculty of Science, Charles Sturt University, Wagga Wagga, NSW 2650, Australia
. ABSTRACT Canola (Brassica napus L) is a major oilseed crop widely grown in Australia. Concern about herbicide-resistance weeds is encouraging consideration of nonchemical weed management tactics such as allelopathy. The impact of crop allelopathy on weeds can be demonstrated under controlled conditions, but field studies are required to confirm the commercial impact of this phenomenon. It is difficult to prove such phenomena in field studies but laboratory to field linking can provide an overall assessment of the allelopathic effects crop species. This study was conducted to validate laboratory allelopathic outcomes of several canola genotypes under field condition. Results from laboratory studies using the equal compartment agar method on annual ryegrass (Lolium rigidum), was linked with suppression of Shepherd’s purse (Capsella bursa-pastoris), Indian hedge mustard (Sisymbrium orientale), barley grass (Hordeum leporinum) and annual ryegrass in the field using the ecological parameter of Simson’s diversity index (%SDI). A strong correlation co-efficient of r=77** was observed between laboratory and field suppression outcomes. The allelopathic genotypes in the laboratory bioassay, such as Av-opal, Sardi603, Rivette and Atr-beacon, also performed well in the field whereas cv. Barossa and X-06-6-3725 consistently poorly performed in field conditions. It is recognized that the specificity of allelopathy only results in effects from certain genotypes against a specific weed. These results do not imply that allelopathic potential in canola will negate the necessity to apply chemical herbicides but rather that allelopathy can be a valuable component in an integrated weed management program.
Keywords: Canola, allelopathy and genotypes Tel: + 61-0402095316
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Appendix II Canola genotype characteristics most likely to distinguish the various weed interference combinations
Trait matrix
Poorly competitive
Highly competitive
Poorly allelopathic
Short, low vigour.
Tall, early-flowering, high
Low yield.
vigour.
High weed numbers in field.
High yield.
Low in vitro score.
Low weed numbers in field.
e.g. Barossa
Low in vitro score. e.g. Tarcoola-91
Highly allelopathic
Short, medium vigour.
Tall, early-flowering, high
Low weed numbers in field.
vigour.
High in vitro score.
High yield.
e.g. Av-opal
Low weed numbers in field. High in vitro score. e.g. Sardi607
The outcomes described in the above table suggest there is sufficient information to plan a genetic cross between a high allelopathic and low competitive genotype and a low allelopathic and high competitive genotype to study the genetic control of these traits.
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(b)
(a)
20 cm
20 cm
(a) Weed inhibition by a tall genotype (Agt346), and (b) Close-up view
(c)
(d)
20 cm
20 cm
(c) Weed inhibition by a short genotype (Av-opal), and (d) Close-up view
Appendix III. A comparison between tall but less weed suppressive and short but more suppressive genotypes in the field experiment in 2012 at Wagga Wagga. 134
Appendix IV. Annual ryegrass infestation in the strong (cv. Av-opal) and in the weak (Barossa) allelopathic canola genotypes in field experiment in 2013 at Wagga Wagga.
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Appendix V. Paterson’s curse rosette diameter in strong allelopathic (cv. Av-opal) and weak (Barossa) canola genotypes in field experiment in 2013 at Wagga Wagga.
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Chapter 8 Research Findings of Metabolites The previous chapters (5, 6 and 7) reported the allelopathic potentiality of canola under laboratory and field conditions. In this chapter, the chemical basis of canola allelopathy in extreme genotypes was studied through a metabolomics approach with an advance analytical tool (LC-QTOF-MS).
Key contents
LC-QTOF-MS
Total number metabolites in six genotypes
Metabolites in shoot and root tissues
Metabolites in root exudates
Principle component analysis
Identified secondary metabolites
Paper 6 (research): Asaduzzaman. M., An, M., Pratley, J. E., Luckett, D., & Lemerle, D. (2014). Metabolites differentiation of canola genotypes: towards an understanding of canola allelochemicals. Frontiers in Plant Science [accepted].
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Metabolomics differentiation of canola genotypes: towards an understanding of canola allelochemicals M. Asaduzzaman1,3*, James E. Pratley1,3, Min An2,3, David J. Luckett3,4 and Deirdre Lemerle1,3 1
School of Agricultural and Wine Sciences, Faculty of Science, Charles Sturt University, Wagga Wagga, NSW 2650, Australia 2 Faculty of Science, Charles Sturt University, Wagga Wagga, NSW 2650, Australia 3 Graham Centre for Agricultural Innovation (an alliance between Charles Sturt University and NSW Department of Primary Industries), Wagga Wagga, NSW 2650, Australia 4 NSW Department of Primary Industries, Wagga Wagga, NSW 2650, Australia * Correspondence: Md. Asaduzzaman, School of Agricultural and Wine Sciences, Charles Sturt University, Boorooma Street, Wagga Wagga, NSW 2650, Australia. Keywords: Brassica napus, rapeseed, weed, root exudates, LC-QTOF-MS and metabolomics.
Abstract Allelopathy is one crop attribute that could be incorporated in an integrated weed management system as a supplement to synthetic herbicides. However, the underlying principles of crop allelopathy and secondary metabolite production are still poorly understood including in canola. In this study, an allelopathic bioassay and a metabolomic analysis were conducted to compare three non-allelopathic and three allelopathic canola genotypes. Results from the laboratory bioassay showed that there were significant differences among canola genotypes in their ability to inhibit root and shoot growth of the receiver annual ryegrass; impacts ranged from 14% (cv. Atr-409) to 76% (cv. Pak85388-502) and 0% (cv. Atr-409) to 45% (cv. Pak85388-502) inhibition respectively. The root length of canola also differed significantly between genotypes, there being a significant negative interaction (r = 0.67; y=0.392x+71.59) between the root length of donor canola and of receiver annual ryegrass. Variation in chemical composition was detected between organs (root extracts, shoot extracts) and root exudates and also between canola genotypes. Root extracts contained more secondary metabolites than shoot extracts while fewer compounds were recorded in the root exudates. Individual compound assessments identified a total of 14 secondary metabolites which were identified from the six tested genotypes. However, the strongly allelopathic genotypes Pak85388-502 and Av-opal were the only genotype which exuded sinapyl alcohol, p-hydroxybenzoic acid and 3,5,6,7,8-pentahydroxy flavones, which revealed that these compounds are combinedly playing a role in canola allelopathy against annual ryegrass in vitro.
1.
Introduction
Weed control options for canola in Australia have been improved considerably with the development of a wide range of herbicide–tolerant cultivars with resistance to triazine, imidazinolinone or glyphosate herbicides. The implementation of glyphosate-tolerant canola has changed the pattern of herbicide use, decreasing the use of other herbicides, and has given growers an efficient and simple solution for weed control worldwide (Harker et al., 2000; Beckie et al. 2011). Unfortunately, the use of herbicides in herbicide-tolerant canola cultivars has encouraged weeds to evolve herbicide-resistance (Powles et al., 1998; Heap, 2002). The ubiquitious weed annual ryegrass (Lolium rigidum L.) has already shown resistance to glyphosate in Australia (Pratley et al., 1999). Thus, herbicide resistance of weeds is a major threat to sustainable crop production. Consequently, alternatives to conventional synthetic herbicide application have become a focus of much research in Australia and worldwide. The potential use of crop allelopathy as part of a weed control program is one option gaining attention of the researchers (Kathiresan, 2005). Rice (1984) defined allelopathy as the direct or indirect (harmful or beneficial) effect of a plant, and microbes, on another plant through the release of compounds into the environment. Allelochemicals have usually been considered to be secondary metabolites or waste products of the main metabolic pathways in plants (Swain, 1977) and released via several mechanisms (Seigler, 1996; Singh et al., 2003; Weston and Duke, 2003) including leaching (by dew and rain), residue decomposition (Putnum and DeFrank, 1983; Purvis et al., 1985) and exudation from living plants (Rice, 1984; Blum, 2011; Thorpe et al., 2011). Furthermore, the production and the release of biologically active compounds differ between species and between cultivars (Jeffery et al., 2003; Bennett et al., 2004; Keurentjes et al., 2006; Abdel-Farid et al., 2007), although relatively few have strong allelopathic properties (Bhomik and Inderjit, 2003; Khanh et al., 2005; Xuan et al., 2005). The potential role of crop allelopathy in weed control has been the focus of much research and has been extensively reviewed (eg. Einhellig and Leather, 1988; Purvis, 1990; Wu et al., 1999). Results from allelopathic assessment of canola cultivars against weeds in vitro and under field condition showed that canola allelopathy is genetically controlled (Asaduzzaman et al., 2014a; 2014b). Canola allelopathy also seems to be independent from the competitive traits in the above ground morphology growth and phenology of the crop (Asaduzzaman et al., 2014c; 2014d). However, there are no reports that holistically analyse the canola allelochemicals complex. Plant secondary metabolites are generally present in plant tissue but few are exuded into the environment (Weston and Duke, 2003; Badri and Vivanco, 2009). To establish the involvement of any root exudates in crop plant allelopathy, it is important to demonstrate their phytotoxic effect by direct release to the growth medium (Inderjit, 1996). The exudation of allelochemicals by plant roots is an active 139
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metabolic process (Overland, 1966) and seems to be universal in the plant kingdom (Martin, 1957; Fay and Duke, 1977; Abdul-Rahman and Habib, 1989; Einhellig and Souza, 1992). Brassicacae plants possess several groups of secondary metabolites including phenylpropanoids (hydroxycinnamates), flavonoids, as well as Brassicaeae-specific metabolites such as glucosinolates. The characterisation of these phytochemicals between strong and weak allelopathic cultivars is very important, as it will help to understand the chemical basis of canola allelopathy. Appropriate advanced tools, such as metabolomics, can be used for identifying and characterising the potential metabolites responsible for the allelopathic defences recently demonstrated in canola (Asaduzzaman et al., 2014a; 2014b). Metabolomics is an approach that allows a biochemical analysis of the total metabolite complement of a given plant tissue (Rinu et al., 2005; Kim et al., 2011). It is being used as an important procedure for identifying compounds involved in allelopathic interactions (D’Abrosca et al., 2013). Through mass spectral (MS) analysis of metabolomes in plant organs and principal component analysis (PCA), relative variability between organs can be explored. In addition, due to complex interactions, the field assessment of crop allelopathy is challenging (Inderjit and del Moral, 1997; Olofsdotter et al., 1999; Inderjit and Weston, 2000; Bertin et al., 2003; Bais et al., 2006) and difficult to separate from competition (Olofsdotter et al., 1999). Hence, laboratory screening of crop cultivars, coupled with advanced multivariate statistical analysis of metabolomes, offers new insights into the subterranean biology of plant allelopathy (Rinu et al., 2005). The present research aimed to determine the metabolite composition of different organs (namely shoot, root) and root exudates of canola by using time-of-flight (TOF–MS) analysis technique and to establish a platform for understanding canola allelopathy. 2.
Materials and methods
2.1.1. Plant materials Six canola (Brassica napus, rapeseed, oilseed rape) genotypes were selected for this study namely: Av-opal, Pak85388-502, Av-garnet, Barossa, Cb-argyle and Atr-409. Previous field and in vitro screening results showed that Av-opal and Pak85388-502 were strongly allelopathic against annual ryegrass in vitro, and against the background weed populations (over two years: 2012 and 2013) under field conditions, whereas, Atr-409 and Barossa were weakly allelopathic genotypes (Asaduzzaman et al., 2014a; 2014b). Two other genotypes were chosen based on a previous canola competitiveness field study conducted by Lemerle et al. (2014): Avgarnet was reported to be strongly competitive and Cb-argyle weakly competitive on weed species and associated total weed biomass. Seeds of these canola genotypes were obtained from the National Brassica Germplasm Improvement Program,
located at NSW Department of Primary Industries, Wagga Wagga, Australia. Agar (technical grade) was purchased from Sigma Aldrich (St. Louis, USA). 2.1.2. Sterilisation and germination Canola seeds were surface-sterilised by soaking in 2% sodium hypochlorite (NaOCl) for 5 minutes, then rinsed six times in sterilised distilled water. The seeds were transferred to a petri dish with one sheet of Whatman No. 1 filter paper, moistened with 5 ml sterilised distilled water, and sealed with parafilm. The surface-sterilised seeds of Brassica and ryegrass were kept in a 12-hour light/12-hour dark, 20 °C/15 °C controlled environment for 36 hours and 48 hours respectively. 2.1.3. General bioassay and growing conditions The equal-compartment-agar-method (ECAM), described previously by Wu et al. (2000a) was chosen for bioassay. The method was developed based on the plant box method and relay seedling technique and separates competition and allelopathy phenomena between two simultaneously growing species. In this method, each species was placed into separate regions in the same container, where each species received equal space for its root system development. Briefly, glass beakers (600 ml, 12 cm depth, 8 cm diameter) containing 30 ml of 0.3% agar-medium (no nutrients, 1.3 cm depth) were autoclaved. The previous bioassay of 70 canola genotypes showed that 30 seedlings/beaker allelopathically gave greatest inhibition of the root length of annual ryegrass (Asaduzzaman et al. 2014a). Hence for each genotype, 30 uniform seedlings per beaker were chosen and aseptically transplanted from the germination dish onto one half of the agar surface, with the embryo up. The beaker tops were sealed with parafilm to prevent contamination and evaporation from the agar surface, and the beakers were placed in a controlled growth incubator with a daily 12-hour light/12-hour dark, 20 °C/15 °C cycle. Canola plants were grwon for six days, 15 pre-germinated uniform seeds of annual ryegrass were aseptically sown on the other half of the agar surface at a distance of 4 cm from the canola seedlings. A piece of pre-autoclaved white paperboard was inserted across the centre and down the middle of the beaker with the lower edge of the paperboard kept 1 cm above the agar surface. The beaker was divided into two equal compartments to minimize competition for space and light between the canola and ryegrass seedlings. The roots of canola freely entered the ryegrass compartment so that any allelochemicals produced and released by the canola seedlings can diffuse throughout the entire agar medium to influence ryegrass root growth. After ryegrass sowing, the beakers were again wrapped with parafilm and placed back in the growth chamber for seven days. The receiver species, annual ryegrass, was also grown alone as a control. After seven days, each annual ryegrass and canola seedling was carefully removed from the agar to avoid root breakage, and the root and the shoot lengths of 10 randomly selected plants of both species were measured. 141
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2.1.4. Experimental design and statistical analysis A randomized complete block design with three replications was used for the experiment described. For each genotype, (1 control + 1 density) x 3 (replicates) = 6 experimental units were used in the growth chamber. Raw data for the root and the shoot length of annual ryegrass and canola genotypes were used separately for statistical analysis. Data (expressed as the percentage of the control root and the shoot growth) were subjected to analysis of variance using Genstat v13 (VSN International, Hemel Hempstead, UK) and the treatment means compared using the least significance difference (LSD) at a 5% level of probability. To evaluate the equivalence of shoot and root inhibition of ryegrass with root length of canola, Pearson correlation co-efficient values were calculated. A linear regression analysis (y=mx+c) was also performed between root length (mm) of canola (independent) and of annual ryegrass (dependent) to know their mutual relationship. Plots of residual versus fitted values were examined for all traits to ensure that the assumptions of analysis of variance were met.
2.2. Biochemical analysis by metabolomics approach 2.2.1. Preparation of shoot and root extracts Canola seedlings of each genotype were grown alone at a density of 30 seedlings/beaker for 13 days, as described in the above laboratory bioassay. The roots and the shoots were cut from the canola seedlings and were immediately stored at -80 oC in a sealed container. The frozen tissue was then freeze-dried for 24 hours (Alpha 2-4 LD plus; John Morris). To extract metabolites, the freeze-dried tissue was then crushed to a fine powder using liquid nitrogen-chilled mortar and pestle. Sixty mg of the root and the shoot tissue of each canola genotype were placed separately into a 2 mL tube chilled in liquid nitrogen. The tube was filled with 400 µL 100% methanol solution containing internal standards 13C6-sorbitol (0.5 mg/mL); 13C515Nvaline (0.5 mg/mL); penta-fluorobenzoic acid (0.25 mg/mL) and 2-aminoanthracene (0.25 mg/mL) (Roessner and Dias, 2013). The tubes were vortexed for 30 seconds and centrifuged for 15 minutes at 13000 rpm at 4 C. The supernatant was transferred to a new pre-labelled 2 mL tube. An amount of 400 µL MQ water was added to the remaining pellet and vortexed, centrifuged and the supernatant was combined with the previous methanol containing supernatant. Three aliquots of each tissue containing 650 µL were prepared and stored at -80 oC until analysis. 2.2.2. Collection of root exudates Canola seedlings were carefully uprooted from their nutrient-free agar medium and the roots were rinsed twice with 5 mL portions of distilled water to remove any adhering agar and root exudates. The washings were pooled with the agar medium (30 mL). The agar medium was stirred carefully and extracted three times using 5
mL of 80% methanol. The extracted samples were vortexed and centrifuged and filtered through a 0.22 µm syringe filter into 2 mL labelled tubes. Three aliquots of 650 µL of each genotype were prepared and stored at -80 oC before analysis.
2.2.3. Metabolites profiling by LC-QTOF-MS To assess the metabolite composition differences among the organs of canola genotypes, non-targeted and targeted metabolite profiling of extracted material was conducted. The compounds of canola shoots, roots extracts and root exudates were separated on an Agilent 6520 LC-QTOF-MS system (Santa Clara, CA, USA, Agilent Mass Hunter Qualitative Analysis Build 6.0), with a dual sprayer ESI source, and attached to an Agilent 1200 series HPLC system (Santa Clara, CA, USA) consisting of a vacuum degasser, binary pump, with a thermo stated auto-sampler, column compartment, and diode array detector. The mass-spectrum (MS) was operated in the negative mode using the following conditions: nebuliser pressure 45 psi, gas flowrate 10 L/min, gas temperature 300°C, capillary voltage 3500 V, fragmentor 150 and skimmer 65 V. The instrument was operated in the extended dynamic range mode with data collected in mass-to-charge ratio (m/z), range 70–1700 amu.
2.2.4. Chromatography An Agilent Zorbax Eclipse XDB-C18, 2.1 x 100 mm, 1.8 µm (Agilent) column was used with a flow rate of 400 µL/min maintained at ambient temperature (35±1 °C), resulting in operating pressures below 600 bar with a 12 minutes run time. A gradient LC-QTOF-MS method (Table 1) was used with mobile phases comprised of (A) 0.1% formic acid in de-ionized water and (B) 0.1% formic acid in acetonitrile. The sample run was conducted first for the 5 minutes by using linear gradient from 5% solvent (B) to 30% solvent (B), followed by a 5 minute linear gradient to 30% solvent (B) to 100% solvent (B), then a 2 min hold at 100% solvent (B) and a 5 minute re-equilibration at 5% solvent (B). Total time = 17 minutes. Three replications were run for each category of samples of each genotype. 2.2.5. Mass spectrum data processing Relative qualitative analyses of the metabolites in the six canola genotypes were performed using Mass Hunter data analysis software (Agilent Technologies, USA). The extracted molecular features of each detected compound were matched with two different data bases (METLIN-AM-PCDL and HMDB-KEGG), plus the mass of the reference compounds from commercial standards. The individual compounds were also determined through assessing the outcomes of score (>70), hit count (total number of hits in the database) and mass differences (<5.0).
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Chemoassays using reference compounds
2.3.1. Preparation of the different concentrations Stock solutions (10000 µM) of sinapyl alcohol, p-hydroxybenzoic acid and 3,5,6,7, 8-pentahydroxy flavones were prepared separately. A mixture of these three compounds (10000 µM) was also made by using 1:1:1 ratio. The stock solutions of individual compounds and of their mixture were diluted to concentrations of 500 μM, 100 μM, and 50, μM in HPLC-grade methanol.
2.3.2. Annual ryegrass bioassay with reference compounds The modified chemical bioassay described by Seal et al. (2004b) was used to evaluate the phytotoxic effects of three reference compounds on annual ryegrass. One milliliter of each of the above concentrations (50 μM, 100 μM, 5000 μM and 10000µM) was added to 600 ml beakers lined with Whatman #1 filter paper (Micro science, grade: MS 2 85 mm, size: 85 mm, Quality: 100) at the base. For the control, 1 ml of pure methanol was added. After the methanol had completely evaporated using the method described by Seal et al. (2004b), 5 ml of sterile double distilled water was added. Ten annual ryegrass seeds were sown directly into the water and the beaker was covered with parafilm. Three replicates of each treatment were arranged in a randomized complete block design in a growth chamber described in 2.1.3. Seven days later the annual ryegrass seedlings were removed from the system and both their root and shoot lengths were measured to the nearest 0.5 mm. 2.3.3. Statistical Analysis All dose-response curves were subjected to two-way ANOVA using Genstat v13 (VSN International, Hemel Hempstead, UK). Annual ryegrass root length was taken as percentage of control and the treatment means compared using the least significance difference (LSD) at a 5% level of probability. Plots of residual versus fitted values were examined for all traits to ensure that the assumptions of analysis of variance were met. 3. Results 3.1. Laboratory bioassay
Genotypes differed significantly (P <0.001) in their ability to suppress the root and the shoot growth of annual ryegrass (Figure 1). Genotypes Atr-409, Cb-argyl and Barossa showed less inhibitory effects on annual ryegrass while Av-opal, Pak85388502 and Av-garnet were more inhibitive. In all collections, root growth (14% to 76%) of annual ryegrass was inhibited more than shoot growth (0% to 15%). The most suppressive genotype Pak85388-502 resulted in 76% root growth control of annual ryegrass followed by genotype Av-opal (74%) and Av-garnet (46%). The
weakest genotype cv. Atr-409 inhibited the root length of annual ryegrass by only about 14%.
Figure 1ǀ Laboratory bioassays (ECAM) of canola (Brassica napus) allelopathy on annual ryegrass (Lolium rigidum) seedlings. Data shown are the genotype means from ANOVA across three replicates for annual ryegrass root and shoot length (% of control). Experimental error is illustrated by using LSDs at P= 0.05(5%). The crossed indicator shows LSD in both the directions. The correlations between two parameters are presented by Pearson’s correlation co-efficient (r=0.89**, P= 0.001). The average root length of canola seedlings differed significantly (P<0.001) between genotypes (Figure 2). Genotypes Av-opal and Pak85388-502 produced the longest root; in contrast Cb-argyle and Atr-409 produced the shortest roots. The regression analysis (r = -0.67; y=0.392x +71.59) showed that annual ryegrass root growth (mm) was decreased with increased canola root growth (mm). 3.2. Metabolite profiling The different metabolite patterns were observed by simple visual inspection of the MS traces of the three different organs. A total of 2806 mass signals were recorded in three different sample types. The number of metabolites in the root and the shoot extracts varied between genotypes. Metabolites were highly enriched in root extracts followed by shoot extracts and root exudates (Table 2). Over 1807 compounds were
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found in roots, with Av-opal, Pak85388-502, Barossa and Atr-409 assigned 1586, 1532, 1471 and 1525 compounds respectively.
Figure 2ǀ The root length of canola (Brassica napus) and annual ryegrass (Lolium rigidum) seedlings when grown together in ECAM bioassay. Data shown are the genotype means from ANOVA across three replicates for annual ryegrass root length (mm). Experimental error is illustrated by using LSDs at P=0.05(5%). The crossed indicator shows LSD in both the directions. The negative correlations between the root growth of canola and of annual ryegrass two parameters are presented by Pearson’s correlation co-efficient (r=-0.67**, P= 0.001; y=0.392x+71.59). 3.3. Identification of phytochemicals in canola genotypes Fourteen secondary metabolites, including two internal signalling molecules, namely jasmonic acid and methyl-jasmonate, were detected across the samples of the six canola genotypes (Table 3). Only eight metabolites were identified in the root exudates. The three interested metabolites were only found in the root exudates of highlyallelopathic genotypes (Av-opal, Pak85388-502, and possibly Av-garnet). Five metabolites (or some mixture of these) were the most likely candidates for an allelopathic effect; sinapyl alcohol, p-hydroxybenzoic acid, quercitin, 3,5,6,7,8pentahydroxy flavones, and methyl-jasmonate. Of these five, quercitin was formed
only in the exudates of Av-garnet, and sinapyl alcohol was found only in the exudates of Av-opal and Pak85388-502.
Figure 3ǀ The sole and combined effect of sinapyl alcohol, p-hydroxybenzoic acid and 3,5,6,7,8-pentahydroxy flavone on the root growth of annual ryegrass (% of control). Data shown are the means of the root length (% of control) of annual ryegrass from ANOVA across three replicates. Experimental error is illustrated by using LSDs at P= 0.05(5%). The bar shows LSD for interaction (compounds x concentrations) effect of chemical treatments. 3.4. Chemoassays using reference compounds The root growth of annual ryegrass seedlings differed significantly (P<0.001) between compounds and their concentrations (Figure 3 and 4). Among the compounds 3,5,6,7,8- pentahydroxy flavones showed greater toxicity, while sinapyl alcohol was less toxic in all tested concentrations. When all tested compounds were considered together in mixture, the root growth of ryegrass was inhibited more compared to the individual effect of each compound, even in medium concentrations. Under the mixture of three compounds at, medium-to-high concentrations (100µM-10000µM) the germination ability of most of the ryegrass seeds was restricted.
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Figure 4ǀ Comparison of the seedlings growth of annual ryegrass affected by (A) control, (B) sinapyl alcohol, (C) p-hydroxybenzoic acid, (D) 3,5,6,7,8pentahydroxy flavone and (E) their mixture. The beakers in the bottom were treated with low concentration (50 µM), while beakers on the top were treated with high concentration (10000 µM). Discussion
Different inhibition activities against ryegrass seedlings were observed among the tested canola genotypes. This is in accordance with previous observations in rice (Seal et al., 2004a), wheat (Wu et al., 2000b) and rapeseed (Uremis et al., 2009), leading to the general conclusion that allelopathy is genetically controlled. The most allelopathic genotypes in this study were Av-opal and Pak85388-502, then competitive genotype Av-garnet. This suggests that root exudation from Av-opal and Pak85388-502 might also have played a significant role for its allelopathic activity in the bioassay. These two genotypes were previously characterised as highly allelopathic in vitro testing (Asaduzzaman et al., 2014a) and were also highly weed suppressive in the field (Asaduzzaman et al., 2014b). The negative relationship between the root length of canola and annual ryegrass suggests that long roots of canola seedlings might produce more allelochemicals than short roots. Hence, despite vigorous shoot growth, Barossa and Av-garnet showed less root-exuded allelopathic activity, whereas the short vegetative growth but longer root growth of Av-opal still inhibited the root growth of annual ryegrass to a greater
extent. Such findings also infer that the inhibition effects on the receiver plant were due to chemical interactions between the roots and that such chemicals were exuded into the agar by the canola roots. It seems possible that the allelopathy potential of any particular genotype depends upon firstly, the chemical composition of the root exudates, and secondly, the amount of chemical exuded which may be a function of root system length or surface area.
The biochemical analysis of canola organs and root exudates showed differences between genotypes in the production of their total metabolomes. It is to be expected that different canola genotypes will produce varying types and amounts of phytotoxic compounds since this has been shown to occur in various other crop species (Guenzi and McCalla, 1966; Wu et al., 2001; Fang et al., 2012; Farag et al., 2012; Jeffery et al., 2003; Fay and Duke, 1977). Gardiner et al. (1999) reported that the roots of rapeseed (Brassica napus L) contained more compounds than did the shoot. The root also contributed more to the total chemical pool for allelopathic activity (Gardiner et al., 1999). Similarly, in this study, the number of metabolites was generally higher in the root than in the shoot and in root exudates. Allelopathic research findings have also revealed that the allelochemical concentrations were higher in the roots than in the shoots of wheat (Wu et al., 2001). It is not clear whether the higher amounts of these allelochemicals in the roots result from their direct synthesis in situ, from their translocation from the shoots to the roots, or both. The presence of chemicals in the root exudates does not infer that they play any role in the observed phytotoxicity. However, it suggests that roots and shoots contain many compounds but only some are released as root exudates, depending upon particular conditions in the rhizosphere (Badri and Vivanco, 2009). In previous Brassica allelopathy research, glucosinolates and their derivatives were proposed as potential allelochemicals of the crop’s residue (Gardiner et al., 1999). These compounds were detected only in the root and the shoot extracts of three genotypes in this study. Possibilities for their non-detection in root exudates include: they remained locked inside the vacuole of fresh tissue of living plant; or they could not be detected due to their complex volatile nature. Glucosinolates were not detected in the root exudates from living tissue of any genotypes showing high allelopathy in our study. Therefore it seems unlikely that they are responsible for allelopathy. This conclusion is most striking when comparing the consistent results from the three replications of the tested genotypes, including Av-opal and Pak85388502. Both are highly allelopathic but Av-opal is low in glucosinolates in the seed while Pak85388-502 is high in glucosinolates in the seed. Glucosinolates and their breakdown products are significant in the phytotoxic effects observed for canola stubble and stubble leachates after harvest (Boydston and Hang, 1995; Brown and Morra, 1996; Al-Khatib et al., 1997). It may be that senescence (aging) and fallen leaves may make a contribution to weed suppression during the life cycle of the crop but this has not been specially recorded. The cut and green manure rapeseed 149
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Canola allelopathy
suppressed weeds (Boydston and Hang, 1995) but this may be due to physical smothering rather than chemical effects. Several potential allelopathic compounds were found in the root and the shoot tissue in this study but were not detected in root exudates. This suggests that the expression of the allelopathic effect not only depends on particular compounds being synthesised but also on the ability of the genotypes to actively exude these into their rhizosphere. For instance, Barossa and Atr-409, the two weakly allelopathic genotypes, contained potential phytotoxic metabolite in the roots and the shoots but their inhibitory effect on annual ryegrass was weak. Dicarboxylic malonic acid was found only in the root exudates of these two weakly allelopathic genotypes and this compound may act as a buffering agent to reduce the threshold levels of other potential allelochemicals in the rhizosphere. Similar results have been also reported in rice (Seal et al., 2004b), where the amounts of dicarboxylic acids was high in root exudates of non-allelopathic rice cultivars. Sinapyl alcohol, p-hydroxybenzoic acid and 3,5,6,7,8-pentahydroxy flavone were isolated from root exudates of the two strongly allelopathic canola genotypes, suggesting that they were at least partly responsible for the observed allelopathic activity. The detection of two signal molecules (jasmonic acid and methyljasmonate) in the allelopathic genotypes also supports the proposition that they are also involved in canola allelopathy. Jasmonic acid and methyl-jasmonate act as secondary messengers in signal transduction events in the cell and have inhibitory effects on many plant physiological processes (Sembdner and Parthier, 1993). Abdel-Farid et al. (2007) reported that the accumulation of these signal molecules is connected with demand or synthesis of the secondary metabolites sinapyl alcohol and p-hydroxy benzoic acid in Brassica rapa. Furthermore, 3,5,6,7,8- pentahydroxy flavone was also detected previously in root exudates of another member of the Brassicaceae, Brassica alba (Ponce et al., 2004). p-hydroxybenzoic acid has been reported as a potential allelochemical in other crops including, Glycine max (Barkosky and Einhellig, 2003), Camelina alyssum (Grummer and Beyer, 1960), and several members of the genus Althaea (Gude and Bieganowski, 1990). Some of the reduction in root and coleoptile growth of wheat seedlings caused by wild oat (Avena fatua) root exudates is attributed to this compound (Perez and Ormeno-Nunez, 1991). It has been postulated that allelopathic effects are most likely due to the combination and interaction of a complex mixture of compounds (Rizvi and Rizvi 1992; An et al., 2003). The chemobioassay results of the present study revealed that, the allelopathic activity of canola cultivars resulted from the synergistic effects of sinapyl alcohol, p-hydroxybenzoic acid and 3,5,6,7,8-pentahydroxy flavones. It is possible that multiple compounds present at low concentrations can have pronounced allelopathic effects through their joint action, though evidence for this elusive. Joint allelopathic interactions between compounds have also been reported in several
Table 1ǀ Gradient of LC Method for 6520-QTOF Time (min) 0.00 5.00 10.00 12.00 12.10 17.00.
A% 95.0 70.0 0.0 0.0 95.0 95.0
%B 5.0 30.0 100.0 100.0 5.0 5.0
Table 2ǀ Total numbers of metabolites identified in root and shoot extracts and root exudates of six canola genotypes Number of metabolites Genotype
Root extracts
Shoot extracts
Root exudates
Av-opal
1586
1494
908
Pak85388-502
1532
1496
951
Av-garnet
1436
1498
774
Barossa
1471
1402
920
Cb-argyle
1525
1524
888
Atr-409
1479
1479
957
Mean
1505
1480
899
LSD, P<0.001
29
33
71
tested species including rice (Chou et al., 1991; Seal et al., 2004b) and vulpia (An et al., 2003). The phytotoxicity observed among the tested canola genotypes indicates that allelopathy plays a role in inhibiting the annual ryegrass weed species. Field experiments (Asaduzzaman et al., 2014b) support this conclusion. The comprehensive chemical analysis reported here revealed that sinapyl alcohol, phydroxybenzoic acid and 3,5,6,7,8-pentahydroxy flavones in most suppressive genotypes (cv. Av-opal and Pak85388-502) are likely allelopathic agents via root exudates in canola. Furthermore, the exudation of these compounds is an important criterion of any allelopathic canola genotypes. 151
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Original Research
Table 3ǀ Phytochemicals identified in shoot and root extracts and root exudates of six canola genotypes using LC-QTOF-MS in negative mode and matched with data from two data bases.
SL 1 2 3 4 5
Name Malonic acid Isocitric Acid 2-hydroxy-3,4-dimethoxybenzoic acid Sinapyl alcohol Rutin
6 7 8
p-hydroxybenzoic acid Vanillic acid trans-3-hydroxycinnamic acid
9 10 11 12 13 14
Dimethoxy-4-hydroxycinnamic acid 2-phenylethyl glucosinolates Quercitin 3,5,6,7,8 pentahydroxy flavone Jasmonic acid Methyl jasmonate
Formula
RT (min)
Mass
Score
C3 H4 O4 C6 H8 O7
0.696 0.931
104.011 192.0259
73.64 97.45
C9 H8 O4 C11 H14 O4 C27 H3 0 O16
4.857 4.987 5.002
180.043 210.087 610.1559
76 94.06 78.19
C7 H6 O3 C8 H8 O4 C9 H8 O3
5.348 5.59 6.356
138.0303 168.0414 164.0458
78.37 81.29 73.8
C11 H12 O5 C9H9NS C15 H10 O7 C15H10 O7 C12 H18 O3 C13 H20 O3
6.631 6.832 7.159 7.50 8.224 9.541
224.0693 163.24 302.046 302.205 210.1224 224.1386
98.34 90.03 69.87 70.05 81.95 72.05
Shoot extracts*
Root extracts*
Root exudates*
3, 4, 6 1, 2, 3, 4, 5, 6
4, 6 1, 2, 3, 4, 5, 6
4, 6 1, 2, 3, 4, 5, 6
1, 2, 3, 4, 5, 6 1, 2, 3, 4, 5, 6 1, 2, 3, 4, 5, 6
1, 2, 3, 4, 5, 6 1, 2, 3, 4, 5, 6 1, 2, 3, 4, 5, 6
1, 2 -
168.04225 164.0473
1, 2, 3, 4, 5, 6 1, 2, 3, 4, 5, 6
1, 2, 3, 4, 5, 6 1, 2, 3, 4, 5, 6 -
1, 2 -
224.06847 163.04556 302.04265 302.04265 210.12559 224.14124
2, 4,5 1, 2, 3, 4, 5, 6 -
1, 2, 3, 4, 5, 6 2, 4, 5 1, 2, 3, 4, 5, 6 1,2 1, 2, 3, 5 1, 2
1, 2, 4, 6 3 1, 2 1, 2
m/z 104.01095 192.0210 180.04225 210.08920 610.15338 138.03169
*Number indicates whether the compound is found in the tissue of the six genotypes: 1= Av-opal, 2 = Pak85388-502, 3 = Av-garnet, 4 = Barossa, 5 = Cb-argyle and 6 = Atr-409. “-” = not present.
152
Frontiers in Plant Science Original Research Acknowledgement
The senior author is grateful to Charles Sturt University for an International Postgraduate Research Scholarship, an Australian Postgraduate Award, and Writing Up award. We are also grateful to Metabolomics Australia, University of Melbourne for their technical supports. We thank to Nusrat Subhan for providing information of chemical standards. Conflict of Interest Statement The authors declare that they have no conflict interests.
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Mass
Retention time (min) Appendix VII Total numbers of aligned compounds (2806) in all tissue and root exudates of six canola genotypes (RT vs Mass).
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Chapter 9 General Discussion and Conclusions
Key contents •
Discussion
•
Conclusions
•
Future directions
159
Chapter 9 General Discussion and Conclusions
Allelopathy is an important mechanism of plant interference caused by the release of secondary metabolites from the plant into the soil environment. Active metabolites or allelochemicals are present in all type of plants and tissues and are often released into the environment in sufficient quantities to affect neighbouring plants (Weston, 1996; Mariagiovanna et al., 2013). Crop allelopathy causing weed suppression can occur during crop vegetative growth and from stubble post-harvest. At the post-harvest stage, crop residue allelopathy could be used for weed suppression, especially during the establishment period of the following crop. Crop residue allelopathy for weed suppression has been extensively studied (Rice, 1984; Barnes & Putnam, 1986, Rice, 1995, Weston, 1996; An et al., 1998; Wu et al., 2001). Research has also been directed to the utilisation of crop seedling allelopathy at the early vegetative growth stage, a critical stage in crop and weed interaction. Crop plants that successfully suppress weeds through seedling allelopathy will gain an advantage. However, understanding the role of allelopathy in the field requires knowledge of the complex outcomes of the soil-plant interaction. A crucial step in this endeavour is to establish the allelopathic potential in the crop species in laboratory and field settings, and to determine whether other factors such as plant morphological traits are involved. In this study, the evaluation has been performed through an initial observation of canola stubble extract toxicity and then the biological screening of diverse canola genotypes for their seedling allelopathy in vitro. A correlation study between
the laboratory score and two years field
experiments was also undertaken to determine canola allelopathy in the field. 160
Finally, the determination of the allelochemicals involved was performed by a systematic metabolomics approach using an advanced powerful analytical tool (LCQTOF-MS). Observations have also been made on how roots of a receiver weed species (annual ryegrass) responds in their growth pattern to the root exudates of donor canola seedlings present in the same growth medium. Canola genotypes differed in phytotoxicity of their stubble residues. The aqueous extracts of mature canola stem significantly inhibited the root growth of ryegrass at concentration of 7.5% (7.5 g residues/100 mL water). The inhibition of root growth of annual ryegrass ranged between 13% and 65% of the control depending on canola genotype. This preliminary observation (with a small number genotypes) indicates that the canola extracts contained inhibitory compounds, that could prevent the growth of annual ryegrass. This inhibition may be casued by one or more phytotoxic organic substances. The type and the amount of phytotoxic chemicals in plants does vary among crop cultivars and tissues (Guenzi & McCalla, 1996; Fay & Duke, 1977; Fang et al., 2012); in rapeseed Uremis et al. (2009) demonstrated that extract phytotoxicity of rapeseed shoots varied between cultivars. In the present study, ryegrass was used as a test weed species to sucessfully screen the differential phytotoxicity of canola extracts. It is possible that multiple applications of canola residues from strong allelopathic genotypes would be of particular value for weed control in the following crop but this hardly seems practical in Australian circumstances. There may be limitations to using canola residue allelopathy in weed management because those residues might also be toxic to the following crop during its early establishment stage (chapter 3). Artificial extracts of ground plant materials in either water or in organic solvents may lead to
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the release of chemicals that are not naturally released to the environment (Liu & Lovett, 1993). Furthermore, the process involved in the preparation of aqueous extracts could result in the release of certain enzymes, salts, amino acids and nitrogen compounds, any of which may not be released under natural field circumstances (Chou & Muller, 1972). So, a bioassay using ground plant material has little ecological relevance, as the extraction procedure causes qualitative and quantative changes in the phytochemical profile (Inderjit & Dakshini, 1995). Therefore, it is more important to study the natural root exudates from live crop seedlings for allelopathic activity as these can be actively produced by the crop in the presence of neighbouring weeds. Various laboratory screening techniques have been developed to measure crop plant allelopathy without the complication of resource competition (Leather & Einhellig, 1986; Fujii, 1992; Navarez & Olofsdotter, 1996; Kawajuchi et al., 1997; Wu et al., 2000). Designing a new screening technique or optimisation of an existing method, for a new crop species is challenging as several requirements must be met. These include defining the most suitable crop growth stage, the donor crop sowing pattern in the growth medium, choice of receiver test weed species, sowing density of both donor and receiver species, and their placement. Here the method used for evaluating allelopathy in canola root exudates was modified from Wu’s equal compartment agar method (ECAM) (Wu et al., 2000). The results from the optimisation of the ECAM protocol indicated that allelopathic activity of canola seedlings was associated with canola seedling age, density and the sowing distance between the donor canola and the receiver annual ryegrass (Chapter 4).
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Laboratory results showed that a high density of canola enhanced allelopathy activity against annual ryegrass (Chapter 5). Although the canola density used in the bioassay was much higher than in any typical field sowing density, the bioassay needs a minimum density of the small seedling roots to enable the allelopathic effect to be quantified. The allelopathic activity of canola root exudates was increased with sowing density for most of the genotypes. Previously, Seal et al. (2004a) assessed rice seedling allelopathy and found increased density of rice enhanced the allelopathic activity against weeds. Belz et al. (2005) reported that densitydependant crop allelopathy is determined by the quantity of the responsible compounds, which depend upon the cultivar and can be parameterised by the slope of density-dependent curves. Furthermore a single responsible compound can affect a specific biochemical site of the receiver plant; compounds in a mixture might affect several molecular sites (Streibig, 1988). Crop genotypic variation may allow local adaptation to be increased via breeding which would favour increased allocation to allelopathy in some environments (Meiners et al., 2012). Such variation was observed in many crops (Putnum & Duke, 1974; Dilday et al., 1994; Olofsdotter & Navarez, 1996; Dilday et al., 1998; Wu et al., 2000; Seal et al., 2004a). Canola allelopathy reported here could be a quantitative trait because it is normally distributed across the test genotypes. However, this hypothesis needs experimental confirmation using a segregating population from a cross between extreme parents. The production and exudation of a small number of active metabolites may be under relatively simple genetic control but the expression is blurred by the genetic background in the various genotypes. A detailed genetic analysis will answer these questions. Lankau (2008) found that genetic variation in the production of allelopathic chemicals in Brassica nigra 163
resulted in both inter-specific and intra-specific interference. Further research is needed in canola to understand the underlying tradeoffs that may constrain allelopathy. The results for the bioassay used here showed that a large range of allelopathic potential exists in canola genotypes. Av-opal and Pak85388-502, ranked as the most allelopathic, originated from different countries suggesting that their allelopathic ability may be associated with genes from unrelated landraces. Strong or weak allelopathic genotypes appear to be found within all countries and are probably spread worldwide. If this is true, one way to improve canola genotype allelopathy could be to pyramid genes from such unrelated landraces, or cross cultivars where different landraces are already combined. Previously a similar opportunity was found by Bertholdsson (2004) during observation of the variation in allelopathy over 100 years of barley selection and breeding. In the current study, some genotypes were non-napus but their species origin did not appear to greatly influence their allelopathic ranking. The number of non-napus genotypes tested in our study was small and further investigations are needed with larger collections before general conclusions can be made about the effect of Brassica species an allelopathy. Allelochemicals are released from crop roots into the surrounding soil, where there is a complex and heterogeneous environment, with continual interaction occurring with the roots of neighbouring plants (de Kroon, 2003; Semchenko et al., 2007). In the rhizosphere, roots are able to detect their neighbours in different ways (Krannitz & Caldwell 1995, Maina et al., 2002, de Kroon et al., 2003, Falik et al., 2003). If a plant does detect and respond to its neighbours, those interactions may be regulated by resource availability (Callaway, 2002) combined with other
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mechanisms such as allelopathy (Hodge, 2009). Known plant communication and identity recognition systems involve multiple types of signals including root-secreted chemical signals (Mahall & Callaway, 1991; Bais et al., 2006). The present study has echoed past results and also demonstrated that during co-growth of canola and annual ryegrass, roots of ryegrass are able to recognise the roots of non-self canola and adopt avoidance behaviour. Such active root behaviour of annual ryegrass seems to be a response to density-dependent allelochemicals from neighbouring canola. Previous studies suggested that roots usually avoid other roots of the same plant (self) to maximise the use of the soil volume (Gersani et al., 2001; Holzapfel & Alpert, 2003; Falik et al., 2003). It has long been hypothesised that chemical signals between roots exist (Lund, 1947; Cohen, 1970) and evidence has accumulated for the effects of chemical signals on interaction among plants and roots (Aphalo & Ballare, 1995; Bruin et al., 1995). The plant–plant root interaction via chemical signals is complex and may involve both toxic and non-toxic mixed compounds which appear to be influenced by the level of relatedness between neighbours. The results of this study show that the weed species annual ryegrass has developed a plastic root growth response to enhance tolerance in mixed plant communities. The field evaluation of postulated crop cultivar allelopathy is vital to confirm that laboratory observations have real significance. Stressful growth conditions generally result in enhanced levels of allelochemical production (Inderjit & Keating, 1999). However, allelopathy does not occur independently in a field situation, and other mechanisms of plant interference come into play (Olofsdotter, 2002). It seems likely that if a crop genotype has no distinguishing competitive traits
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but still causes strong weed suppression then allelopathy is responsible (Belz 2007). In this study, a large number of short (dwarf) genotypes achieved very high weed suppression (Chapter 7). Generally, increased plant height did increases competitive ability so short genotypes must be employing other mechanisms to suppress weeds. This was also reflected in the grain yield results, where some genotypes were clearly quite poorly-adapted to the local conditions in Wagga Wagga and they had low grain yields, and yet they still produced plots with very low weed numbers. Such findings suggests that canola plant allelopathy exists under field conditions and that plant morphological traits, such as tall plant height or early vigour, are not exclusively causing interference but likely act in addition to allelopathy. The field experiment in year 2 (2013), showed that genotypes Av-opal, Pak85388-502, Av-garnet and Barossa produced very similar plant biomass and grain yield but the weed infestation levels differed greatly between them. The first two genotypes had good field performance for weed suppression, in agreement with their positive allelopathy score in the laboratory screening (Chapter 7). It is clear weed-suppressing cultivars have great potential in broad-acre agriculture and that further work is needed to produce genotypes with both competitive ability and allelopathy (Olofsdotter et al., 1999; Seal et al., 2008). The ability of plant to produce defensive chemicals is often constrained by the environment (Coley et al., 1985) that may affect the crop allelopathic expression (Dilday et al., 1998; Olofsdotter et al., 1999). In the late sowing many weeds had obtained a head-start over the crop and the crop plants were less able to compete, even if they were highly allelopathic. Thus the weed suppressive performance of canola genotypes across multiple environments needs to be investigated. An
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environment-allelopathy link might suggest a specific triggering mechanism for allelopathy expression. Many rice lines scored as allelopathic in Arkansas did not significantly affect weed growth when grown in the Philippines (Olofsdotter et al., 2002). The rice cultivar, Dular, previously described as allelopathic against barnyard grass (Echinochloa crus-galli) and small flower flat sedge in Egypt (Hassan et al., 1994) was non-allelopathic against ducksalad in Arkansas (Dilday et al., 1991). However, Seal and Pratley (2010) found that Dular had intermediate allelopathic effects against the Alismataceae species but poor allelopathic potential against barnyard grass in Australia. The interaction between canola and Paterson’s curse was examined as part of the 2013 field trial (Chapter 7). The plant interference ability of Av-opal, Pak85388502 and Av-garnet significantly reduced the rosette diameter of Paterson’s curse and suggested that canola interference had an effect on the phasic development of Paterson’s curse. Such an effect can be very important in directly or indirectly reducing the amount of viable weed seeds that contribute to the seed bank. Seedlings of various crop species possess allelopathic potential and generally the allelochemicals are a mixture rather than a single compound (Putnam & Duke, 1974; Fay & Duke, 1977; Williams & Hoagland, 1982; Dalton, 1983; Dilday et al., 1994; Kim et al., 1999). Any allelochemicals present at a concentration below their individual threshold level may still contribute to a significant effect by their joint action (Einhellig, 1986; Rice, 1987). A metabolomics approach allows the measurement of a wide range of compounds involved in the plant–plant interaction (D’Abrosca et al., 2013). In addition, such an approach provides advantages to highlight synergistic or additive effects which are proposed but very difficult to
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demonstrate (D’Abrosca et al., 2013). To the author’s knowledge this study is the first to report the determination of the chemical basis for observed canola allelopathy by using a metabolomics approach. This analysis has resulted in the identification of a range of root exudates, some of which are likely to be responsible for the observed allelopathic effects. The identified allelochemicals accumulated to higher concentration in plant root tissue than in shoot tissue. It is not clear whether the higher amount of metabolites present in the roots is derived from their direct biosynthesis in the roots or from the translocation of these compounds from the shoots to the roots, or both. However, metabolite distribution recorded in this study indicated that plant tissue of the strongly allelopathic canola genotypes generally contained higher amounts of metabolites than those of poorly-allelopathic ones. Presumably, a higher number of metabolites in the root tissue means that greater numbers and amounts are secreted into the surroundings. In rapeseed, more metabolites in residues were found in roots, and contributed more to the total allelopathic pool than shoots (Gardiner et al., 1999). However, the presence of metabolites in tissue does not itself imply that the plant can exude them into the surrounding soil or growth medium. Plant may only become allelopathic when active allelochemicals are exuded by living intact roots or possibly by the movement of volatile signalling molecules. Furthermore, a small and specific number of active secondary compounds show herbicidal activity (Einhellig & Leather, 1998). In rice, Seal et al. (2004b) found high concentrations of abietic acid in non-allelopathic rice cultivars and suggested that perhaps this compound has a buffering role in the sense that the presence of a larger amount of abietic acid in the exudates counteracts or neutralises the effects of potential allelochemicals. Wu et al., (2001) found that the amount of phenolics quantified in the exudates of allelopathic 168
wheat cultivars was poorly correlated with the amount detected in roots and shoots, thereby stressing the need for exudate studies to fully understand the allelopathy phenomenon. Allelopathic compounds of plant origin such as root exudates are often very complex, and more likely to occur at very low level (An et al., 2001). Identification and quantification of multiple allelochemicals from such a complex chemical mixture represents an analytical challenge. In this study the author used an advanced and sensitive analytical tool LC-QTOF-MS. A total of eight root-exuded compounds were identified and, among them, sinapyl alcohol, p-hydroxybenzoic acid, 3,5,6,7,8pentahydroxy flavones and methyl jasmonate were isolated solely from strongly allelopathic canola genotypes. Previously, p-hydroxybenzoic acid (Barkosky & Einhellig, 2003) and 3,5,6,7,8-pentahydroxy flavone (Ponce et al., 2004) were found in soybean (Glycine max) and white mustard (Brassica alba) respectively, and they showed inhibitory effects on other species. This suggests that these three major compounds, either singly or in combination, are playing a role in canola allelopathy. It also possible that weakly allelopathic canola genotypes also contain these active compounds but their biosynthesis controlling gene(s) might be absent or greatly down-regulated. Several attempts have been made to understand the genetic basis of crop allelopathy and to locate the genetic markers linked to the production of allelochemicals (Niemeyer & Jerez, 1997; Dilday et al., 1998). It is evident that more advance techniques such as DNA microarrays and proteomics could be used for identifying and characterizing the biosynthesis pathway responsible for the allelopathic defences found in canola. The results of such a systems biology
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approach will lead to the identification of genes involved in canola allelochemicals. The model plant Arabidopsis thaliana is closely related to the Brassicas. There is now well detailed understanding of the genetic control of the biochemistry and physiology of A. thaliana and all its genes sequences are known. The strong DNA similarity between Arabidopsis and Brassica means that markers developed in Arabidopsis can be used to track the same genes in Brassica. Eventually the integration of all these results will lead to a recommendation for breeding for new commercial canola cultivars. The outcomes described here suggest there is sufficient information to plan a genetic cross between a highly allelopathic plus poorly competitive genotype and a poorly allelopathic plus highly competitive genotype to study the genetic control of these traits (Chapter 7) and to assess their relative importance to overall weed interference. The presence of soil microbes can be a factor influencing the overall effect of allelochemicals on plants. Pseudomonas is particularly adapted for rhizosphere colonisation by their ability to utilise diverse carbon sources present in root exudates (Kiemer, 2003). The interaction between the plant allelopathic activity and soilmicrobes can be either positive (increase allelopathy) or negative (decrease allelopathy). The composition of root exudates can influence the types of microorganism which populate a neighbourhood (King & Wallace, 1956). Tactics and approaches for manipulating the field environment to enhance survival, physiological behaviour and performance of these microbes might improve allelopathic activity of a crop in the field (Newman et al., 1998).
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Overall project conclusions
1. Canola stubble extracts show phytotoxicity on root growth of annual ryegrass; the phytotoxicity depends upon the canola genotype and the extract concentration. Furthermore, canola stubble extracts are also toxic to canola itself (as seen in inhibition of germination and in root and shoot growth of seedlings). 2. Canola seedlings show allelopathic activity against seedlings of annual ryegrass under laboratory conditions, and the allelopathy trait is likely an inherited character. The plant density of canola plays a major role in allelopathic activity against annual ryegrass seedlings.
3. Canola allelopathy in the field can only be predicted from laboratory screening because in the field a myriad of other factors come into play (eg. plant height, soil microbes). It is therefore essential to undertake both laboratory and field evaluation of canola cultivars to demonstrate their allelopathic potential. 4. Canola competition and allelopathy are likely independent characters and allelopathy is probably not linked with plant morphological characters such as plant height and early vigour, although both of these are very important characters for suppressing weeds in the field via competition. 5. Sowing time influences weed dynamics but more research is needed to understand in relation to understand it.
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6. Of the large number of metabolites found in canola root and shoot tissues only a small number are released into the environment as root exudates. 7. Sinapyl alcohol, p-hydroxybenzoic acid, 3,5,6,7,8-pentahydroxy flavone and methyl jasmonate are the most abundant chemicals in the root exudates of the strongly-allelopathic canola genotype (cv. Av-opal), and are probably responsible for canola seedling allelopathy against annual ryegrass. 8. Annual ryegrass roots can actively distinguish the presence of roots of canola without physical contact with them and can adjust their growth to avoid canola roots, presumably to minimise negative allelopathic effects.
Future research From this thesis the following recommendations for future research can be made: •
Strongly allelopathic canola genotypes against annual ryegrass may not act against all weed species. Further in vitro screening of canola germplasm is required using other common weed species which have agronomic importance in farmers’ fields. These include wild radish (Raphanus raphanistrum), shepherd's purse (Capsella bursa-pastoris), Indian hedge mustard (Sisymbrium orientale) and barley grass (Hordeum leporinum). If strongly-allelopathic canola genotypes do not express their allopathic activity against other weed species, it means that allelopathic activity is selective and specific allelochemicals have specific modes of action. However, before conducting such future research, the bioassay methodology has to be
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considered very carefully, as any particular screening method may not be suitable for all test species. •
Canola roots may only exude certain allelochemicals in response to the presence of certain weeds. This possibility requires further investigation.
•
Field screening better predicts the performance of cultivars when deployed in an agricultural setting, provided that the experiments are conducted carefully. Thus research efforts should occur in both laboratory and field, and should be conducted concurrently to achieve improvements in allelopathic activity in canola.
•
It is really important to know to what extent allelochemicals accumulate in the soil and interact with the abiotic and biotic environmental conditions.
•
Further study is necessary to determine other active but unknown metabolites responsible for canola seedling allelopathy. Once a relatively comprehensive array of allelochemicals is determined, there will also be a need to investigate the combined effects of allelochemical mixtures using similar concentrations to those detected in root exudates.
•
Brassica napus is a close relative of A. thaliana, a model species of plant science. Considerable knowledge of this model species has been accumulated. These resources will permit a much quicker analysis of the biochemistry and possible genes controlling of canola allelochemicals. Once the genes controlling allelopathy have been identified, breeding of canola cultivars with both strong allelopathy and good agronomic characteristics can
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commence, preferably using DNA markers for a small number of genes responsible for the main allelochemicals.
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