Phd Thesis Without Them

Imperial College London Department of Biology

Eﬀectiveness of prosulfocarb-based treatments for the control of sensitive and herbicide resistant Lolium spp. populations

Geraldine Charlotte Bailly

26th September 2011

Submitted in part fulﬁlment of the requirements for the degree of Doctor of Philosophy in Weed Science of Imperial College London and the Diploma of Imperial College London

Declaration

I herewith certify that all material in this dissertation which is not my own work has been properly acknowledged.

Geraldine Charlotte Bailly

Abstract

The rapid evolution of resistance to post-emergence herbicides in Lolium spp. (ryegrass species) has complicated weed management in cereals. En- suring good pre-emergence control is therefore increasingly important to protect yields. Prosulfocarb is a broad spectrum thiocarbamate herbicide that kills plants by disrupting the biosynthesis of very long chain fatty acids. This is the first report of resistance to prosulfocarb in Lolium species from farm sites and glasshouse selection. The recurrent selection process with prosulfocarb applied pre-emergence at its maximum labelled rate (4,000 gai/ha) on a susceptible Lolium multiflorum Lam. population showed that the evolution of resistance due to repetitive use was possible but slow. Over three generations, it resulted in modicum levels of resistance which were not significant at practical field rates. For the last progeny obtained, there was no evidence of either cross-resistance or increased sensitivity to an herbicide under-development with a mode of action similar to prosulfocarb (RF50 = 0.99, 95% CI = 0.77 - 1.27). Likewise, high and increasing levels of non-target-site based resistance to clodinafop-propargyl did not result in cross-resistance to prosulfocarb. Prosulfocarb exerted low levels of negative cross-resistance on LL1781, SS1999, GG2078 and RR2088, four different ACCase mutant L. multiflorum sublines (average RF50 = 0.67). In order to control susceptible and resistant populations in winter cereals, prosulfocarb was mixed with diflufenican, metribuzin, pyroxasulfone and the formulated mixture {iodosulfuron:mesosulfuron}. Over the 86 mixtures tested, 11 showed a high potential. Prosulfocarb + diflufenican at 2,400 + 32 gai/ha presented interesting levels of synergism (+20 points on average). A non-random survey in 34 farm sites from England showed that most Lolium samples (80%) were sensitive or only partially resistant to prosulfocarb. However, prosulfocarb efficacy was lower where other herbicides had been used intensively. Future research may now concentrate on the determination of prosulfocarb resistance pathways in Lolium spp.

A mouse is an animal that, when killed in suﬃcient quantities, under controlled conditions, produces a doctoral thesis. Woody Allen Also applicable to ryegrass species, plants.

Acknowledgments

From the newly graduated Master student to the Dr. to be, this PhD has really been quite a journey! Some would say, a roller coaster, I would rather say an initiatory journey.

I would not be there now without Deepak who chose me as his first PhD student, believed I could make it as a researcher and put together a Research Proposal that was in competition at Syngenta level for funding (BBSRC In- dustrial Case Award). I am really grateful to all the persons who supported the project from its drafting stage to the end, especially Jason Tatnell and Gael Le Goupil who were always here to advise on technical questions and to review publications. Warm thanks also go to Luc Flamant, from whom I learnt a lot, although he failed to honor his field trials visit promise and who should really consider quitting smoking. Finally, I do really appreciate the great opportunity I had to have been able to conduct all my experimental work at Jealott’s Hill. This would not have been possible without Simon Archer and Denis Wright’s approvals and without Mark Spinney’s flexibility. Giving me Bay 2 for three years was a big sacrifice. I really enjoyed the glasshouse work and I can now state that I master the way of growing grass. Quite a technical skill, isn’t it? My glasshouse time was that successful as I knew I could always count on Adam Stacey to cheer me up when I felt blue and to give me a hand when I needed strong arms. I’m particularly thinking of the excessively heavy green wheelie bins, the moist silver sand bags and the metal pieces that covered the glasshouse gully. Adam, we need to schedule another pub lunch! I also knew I could abandon my plants, as difficult as it may be, for some time and enjoy the (too few) holidays and conferences without any worries as Barry Elsdon was there to take care of my babies and trim them as needed. Thanks Barry. Thanks also to Sarah-Jane Hutchings. General thanks to Plant Production folks, Phil - keep your funky T-shirt collection, there are some I really liked; Peter

9 - try to keep the Resistance Seed Store tidy and for God’s sake, please stop stealing or hiding resistant seed batches; Diane - thanks for the rhubarb and please keep an eye on Peter; Lesley - thanks for the sugar cane courses and the transplanting help. Glasshouse is good, lab is better! Growing plants was one thing, but I also had to figure out what was really going on at a lower scale, yes man, at the enzyme scale and even worst, at the gene scale. Damn! How to do that? Calling 118 118 could have been a solution, but I opted for Richard Dale’s teaching skills. Poor Rich! He had no choice really and saying he was terrified when I refused to hold the multichannel pipette to load a gel is an understatement. Soon after this silver pipette became my best friend and I wouldn’t have lent it for anything. So, Rich thank you for your patience, your help and your knowledge. I’m glad it was you who taught me some tricks of the trade. I had an amazing, awesome (!) time in Lab 136 and I wish I had more molecular work to do. More thanks go to Rachael Blain who was my centrifuge buddy and the best labmate. Pauline may have already said it, but I say it again. A wink to John Ray and our Tour de France conversations. Quite a good one this year, and guess what, I saw the last stage! In this busy schedule, there was still some time left for enzymatic studies. It was the era of ACCase extraction, purification, fraction testing, western blotting. . . Mama Mia! Hopefully, Steve Elvidge and his magic fingers were there when the Akta misbehaved. Thanks Steve. Thanks to Samantha Hall for the radiochem training and to Sheila Atten- borough for the guidance on the protein identification work. All - your help was invaluable. A thought to Nathalie Dupen who ordered everything I needed and chased up the orders when required. Knowing your science consumables will arrive on time is a significant advantage. The icing on the cake was the statistical analyses. One cannot imagine a biology PhD thesis without them. For that, I am strongly indebted to Eddie McIndoe. The theoretical courses you get at the Uni are one thing, the reality of the experiments another. So, thank you Eddie for having taken time whenever needed. A final thought for the Bible that accompanied me during these years, I mean the R book, and huge congratulations to Michael J Crawley for having written it and introduced this black magic to the Silwoodians! As promised, a line to Linda Romain who managed to make Denis and Simon sign the paperwork and send it one month after the official deadline but two months before the informal one. That was a relief!. Last warm thanks

10 to David Brocklehurst for having scrutinised my thesis before the viva day, to Colin Turnbull and Stephen Moss for their helpful comments during the viva voce examination.

Exhausting research must work in tandem with relaxing time. Now, I wish to thank all the persons who accompanied and supported me during this long journey. First and foremost, thanks to my local family who pampered me and my little car for three years. Leaving with you was really enjoyable. Joe - you were right, I brought back my bike to France, but I still haven’t used it and the tyres are still flat; Saskia - keep going, you will do well at school and beyond. Les filles, Karine, Olivia, ¸cam’a fait un bien fou de vous savoir àmes côtés.On aurait quand mêmepu organiser plus de soiréesWii, on a mal gérélà; d’autant plus que la promise n’a toujours pas apparu àBry ! Iain, take care of The Management and stay as you are, always happy and relax on the surface. Pauline, on ne se sera malheureusement pas côtoyer longtemps, j’espòreque tu trouveras ton bonheur, en Suisse ou ailleurs ! Martina, Yael and Gabriel, thanks for your support, for the lovely dinners we had together, for all the postcards and letters I received from you. Rekha, I’m glad you moved on, hugs to Anjali and thanks for having initiated me to the Indian cuisine. Enfin, merci àMaman et àMarc David, inutile d’en dire plus, vous savez trèsbien ce que vous avez fait, faites et êtespour moi.

11 Contents

Abstract7

Acknowledgments9

List of Figures 17

List of Tables 21

List of Abbreviations 25

1 General Introduction 29 1.1 Ryegrass...... 29 1.1.1 General characteristics...... 29 1.1.2 Ryegrass species as a weed...... 30 1.2 Herbicides and ryegrass control...... 32 1.2.1 ACCase-inhibiting herbicides, HRAC A...... 35 1.2.2 ALS-inhibiting herbicides, HRAC B...... 36 1.2.3 Thiocarbamate herbicides, HRAC N...... 37 1.2.4 The evolution of herbicide resistance...... 40 1.3 Herbicide Resistance...... 40 1.3.1 Metabolic-based resistance...... 42 1.3.2 Target-site based resistance...... 43 1.3.3 Resistance in Lolium spp. populations...... 44 1.3.4 Overview of methods for detecting herbicide-resistance 48 1.3.5 Factors inﬂuencing resistance evolution...... 49 1.4 Project speciﬁc objectives...... 52

2 General Materials and Methods 55 2.1 Herbicide whole plant bioassays...... 55 2.1.1 Pot format...... 55

12 2.1.2 Soil type...... 55 2.1.3 Seed source and storage...... 56 2.1.4 Plant growth stages...... 56 2.1.5 Operating procedures for pre-emergence application. 57 2.1.6 Seed germination on agarose...... 57 2.1.7 Herbicide application...... 59 2.1.8 Herbicides and adjuvants list...... 59 2.1.9 Growth conditions...... 61 2.1.10 Herbicide injury scoring...... 61 2.1.11 Seed production...... 61 2.1.12 Dose-response analysis...... 63 2.1.13 Parameter interpretation...... 63 2.2 Molecular analysis...... 64 2.2.1 DNA extraction...... 64 2.2.2 Polymerase chain reactions (PCR)...... 66 2.2.3 Primers and Sequencing...... 66 2.2.4 Electrophoresis...... 66 2.2.5 dCAPS assays...... 67 2.3 Enzymatic studies...... 67 2.3.1 ACCase extraction and puriﬁcation...... 67 2.3.2 ACCase activity assays...... 68

3 Prosulfocarb behaviour under greenhouse conditions 73 3.1 Introduction...... 73 3.2 Pre-emergence prosulfocarb rates...... 74 3.2.1 Materials and Methods...... 74 3.2.2 Results and Discussion...... 75 3.3 Prosulfocarb performance over time...... 77 3.3.1 Materials and Methods...... 77 3.3.2 Results and Discussion...... 77 3.4 Prosulfocarb eﬃcacy as a complex function of soil characteristics...... 80 3.4.1 Materials and Methods...... 80 3.4.2 Results and Discussion...... 80 3.5 Prosulfocarb controls SLR31...... 85 3.5.1 Materials and Methods...... 85

13 3.5.2 Results and Discussion...... 85 3.6 Conclusions and Perspectives...... 88

4 Assessment of prosulfocarb-resistance evolution 89 4.1 Introduction...... 89 4.2 Materials and Methods...... 91 4.2.1 Recurrent selection...... 91 4.2.2 Resistance proﬁle...... 91 4.2.3 Data analysis...... 94 4.3 Results...... 95 4.3.1 Recurrent selection...... 95 4.3.2 Response to recurrent selection with prosulfocarb... 95 4.3.3 Cross-resistance evaluation with ‘Experimental Com- pound X’...... 102 4.3.4 Cross-resistance evaluation with ACCase and ALS inhibitors...... 102 4.4 Discussion...... 105 4.5 Conclusions and Perspectives...... 110

5 Prosulfocarb vs. ACCase non-target-site based resistance 111 5.1 Introduction...... 111 5.2 Materials and Methods...... 112 5.2.1 Seed source...... 112 5.2.2 Recurrent selection...... 113 5.2.3 ACCase resistance mechanisms...... 113 5.2.4 Resistance proﬁle...... 116 5.3 Results...... 119 5.3.1 UK225.G0 initial sensitivity proﬁle...... 119 5.3.2 ACCase resistance mechanisms determination..... 119 5.3.3 Response to recurrent selection with clodinafop.... 122 5.3.4 Response to prosulfocarb after the recurrent selection with clodinafop...... 123 5.3.5 Response to iodosulfuron after the recurrent selection with clodinafop...... 127 5.4 Discussion...... 136 5.5 Conclusions and Perspectives...... 140

14 6 Negative cross-resistance 141 6.1 Materials and Methods...... 144 6.1.1 Production of homozygote wild-type and mutant sublines...... 144 6.1.2 Prosulfocarb dose-responses...... 146 6.1.3 Detailed study for D2078G...... 147 6.1.4 Data analysis...... 148 6.2 Results...... 148 6.2.1 Prosulfocarb dose-responses...... 148 6.2.2 Detailed study for D2078G...... 152 6.3 Discussion...... 157 6.4 Conclusions and Perspectives...... 160

7 Prosulfocarb mixtures 161 7.1 Introduction...... 161 7.2 Materials and Methods...... 165 7.2.1 Mixture design...... 165 7.2.2 Evaluation of the prosulfocarb plus pyroxasulfone tank mix...... 166 7.2.3 Data analysis...... 169 7.3 Results...... 170 7.3.1 Potential of prosulfocarb mixtures with four diﬀerent partners...... 170 7.3.2 Evaluation of the prosulfocarb plus pyroxasulfone tank mix on chosen L. rigidum populations...... 178 7.4 Discussion...... 181 7.5 Conclusions and Perspectives...... 186

8 Prosulfocarb eﬃcacies on Lolium samples 187 8.1 Introduction...... 187 8.2 Materials and Methods...... 188 8.2.1 Seed source, herbicide history and prosulfocarb testing 188 8.2.2 Data analysis...... 189 8.3 Results...... 192 8.3.1 Pre-emergence screen...... 192 8.3.2 Pre-emergence/post-emergence comparison...... 194

15 8.3.3 Deﬁning sensitivity groups...... 195 8.3.4 Weed resistance mapping...... 195 8.4 Discussion...... 199 8.5 Conclusions and Perspectives...... 205

9 Summary, Discussion and Directions for further research 206

Bibliography 213

16 List of Figures

1.1 Lolium multiflorum Lam. from seed to flowering stage.... 30 1.2 World distribution of Lolium species...... 31 1.3 HRAC World of Herbicide 2010...... 34 1.4 Acetyl-CoA carboxylase isoforms in higher plants...... 36 1.5 Example of typical prosulfocarb injury symptoms on L. multiflorum ...... 39 1.6 Evolution of the number of reported herbicide-resistant monocotyledonous weed species from 1980 to 2010...... 41

2.1 Early phenological growth stages and BBCH-identiﬁcation keys of grass weed species...... 57 2.2 BBCH general scheme for grass weed species...... 58 2.3 Ryegrass seeds at BBCH05-07 on agarose plates...... 58 2.4 Fully ripe ryegrass seeds...... 62 2.5 Illustration of the parameters interpretation: ED50, resistance factor (RF) and relative potency (RP)...... 65 2.6 Schematic view of the overall reaction mediated by ACCase. 69 2.7 Structure of the malachite green dye...... 72 2.8 Example of a malachite green assay plate...... 72

3.1 Prosulfocarb structure...... 74 3.2 Dose-response curves for three herbicide-sensitive populations tested against a range of prosulfocarb rates...... 76 3.3 Example of typical prosulfocarb injury 21 days after application 79 3.4 Weed control distribution for prosulfocarb applied at 4,000 gai/ha on G0 seeds at BBCH03 over 11 distinct experiments carried out from May 2008 to March 2011...... 79

17 3.5 Dose-response curves for the susceptible standard population G0 following application of prosulfocarb on three diﬀerent soil types...... 84 3.6 Dose-response curves for the susceptible standard L. rigidum population PP1 and SLR31, the multiple-resistant population following application of prosulfocarb...... 87

4.1 Examples of injury scoring for ﬁve pre-germinated seeds per pot 21 days after a pre-emergence application of 4,000 g prosulfocarb/ha...... 93 4.2 Distribution of the weed control values for the plants that survived 4,000 g prosulfocarb/ha...... 97 4.3 Dose-response curves for the parental susceptible population G0 and the third prosulfocarb-selected progeny G3 against a range of prosulfocarb rates...... 99 4.4 Distribution of the weed control values for prosulfocarb applied at BBCH11 on the parental susceptible population G0 and the third selected progeny G3...... 101 4.5 Dose-response curves for the parental susceptible population G0 and the third prosulfocarb-selected progeny G3 against a range of ‘Experimental Compound X’ rates...... 102 4.6 Distribution of the weed control values for clodinafop and iodosulfuron on the parental susceptible population G0 and the third selected progeny G3...... 103

5.1 Survival data for the susceptible standard population G0 and the field population UK225.G0...... 121 5.2 Dose-response curves for the susceptible standard population G0, the field population UK225.G0 and the subsequent clodinafop-selected progenies against a range of clodinafop rates...... 123 5.3 Survival increase and vigour increase for the UK225 generations treated with 240 g clodinafop/ha...... 124 5.4 Boxplot of prosulfocarb efficacies on the susceptible standard population G0, the field population UK225.G0 and the two clodinafop-selected progenies...... 125

18 5.5 Prosulfocarb dose-response curves for the sand bioassay with the susceptible population G0, UK225.G1 and UK225.G3.. 126 5.6 Picture of the sand dose-response experiment, 23DAA.... 126 5.7 Iodosulfuron dose-response curves for the susceptible standard population G0 and the UK225 generations...... 128

6.1 Schematic representation of the biosynthesis of very long chain fatty acids...... 144 6.2 Prosulfocarb dose-response curves for the susceptible standard population G0, the homozygous mutant subline (LL1781 or RR2088) and the wild-type (II1781 or CC2088)...... 150 6.3 Dose-response curves obtained in the sand bioassay for the susceptible standard population G0, the homozygous mutant subline GG2078, the wild-type subline DD2078 against a range of prosulfocarb and napropamide rates...... 153 6.4 Hierarchical organization for the six herbicides tested in a dose-response experiment against the pure homozygote wild- type population DD2078, the corresponding pure homozygote mutant GG2078 population and the susceptible standard G0 population...... 156

7.1 Results for the prosulfocarb plus metribuzin mixtures experiment...... 174 7.2 Results for the prosulfocarb plus diﬂufenican mixtures experiment...... 175 7.3 Results for the prosulfocarb plus pyroxasulfone mixtures experiment...... 176 7.4 Results for the prosulfocarb plus ATL mixtures experiment. 177 7.5 Percentage of weed control for the 13 ryegrass populations assayed against pyroxasulfone applied pre-emergence at 64 gai/ha...... 179

8.1 Map of the origin of the 34 ryegrass samples harvested between 2000 and 2008 in England...... 190 8.2 Prosulfocarb eﬃcacy on the 34 ﬁeld populations and the standard susceptible population G0...... 193

19 8.3 Prosulfocarb efficacies applied PRE and POST at 2,400 gai/ha on the ‘resistant’ and ‘sensitive’ sub-sets and the susceptible standard population G0...... 196 8.4 Map of prosulfocarb efficacies for the 34 field populations harvested between 2000 and 2008 in England...... 197 8.5 Proportion of resistant, sensitive and partially resistant ryegrass samples per year of sampling and location...... 198 8.6 Wheat and ryegrass distributions...... 202

20 List of Tables

1.1 SNP known to confer target-site resistance to ACCase inhibitors in Lolium spp...... 46

2.1 List of primers and restriction endonucleases used in the dCAPS experiments...... 71

3.1 List of the 11 different experiments carried out between May 2008 and March 2011 with prosulfocarb...... 77 3.2 Combinations of soil type and prosulfocarb doses used in the soil comparison assay...... 82 3.3 Parameters and estimated values for the prosulfocarb dose- response experiments carried out on three different types of soils with the susceptible standard L. multiflorum population G0...... 83

4.1 Number of seedlings involved in the prosulfocarb recurrent selection process...... 96 4.2 Herbicide sensitivity at 4,000 g prosulfocarb/ha for the parental susceptible population G0 and the last selected progeny G3 across three distinct experiments...... 98 4.3 Kolmogorov-Smirnov and location tests outputs for the weed control data for the plants that survived 4,000 g prosulfocarb/ha...... 98 4.4 Parameters of the log-logistic model used to estimate the ED50 values for the parental susceptible population G0 and the third selected progeny G3...... 100 4.5 Herbicide sensitivity for clodinafop and iodosulfuron on the parental susceptible population G0 and the third selected progeny G3...... 104

21 4.6 Details of the ﬁve non-farm population selected after two consecutive applications of diclofop-methyl)...... 109

5.1 Number of seedlings treated for the recurrent selection process with clodinafop-propargyl...... 114 5.2 Number of seedlings tested per population and clodinafop rate at the end of the recurrent selection process...... 117 5.3 Number of seedlings tested per population and iodosulfuron rate...... 119 5.4 UK225.G0 initial sensitivity profile against selected ACCase and ALS inhibitors...... 120 5.5 IC50 values for the extracted ACCases from the susceptible standard population G0 and the clodinafop-selected survivors of UK225.G0...... 122 5.6 Nucleotide and amino acid substitutions in the sequenced fragment of the ACCase CT domain of the seven UK225.G0 selected plants compared to the wild type sequences of either G0 or 2005 UK 203...... 129 5.7 Estimated parameters from the log-logistic model used to fit the data set for the visual assessment after clodinafop application...... 130 5.8 Estimated parameters from the log-logistic model used to fit the data set for the mortality assessment after clodinafop application...... 131 5.9 Estimated parameters from the log-logistic model used to fit the data set for the visual assessment after prosulfocarb application...... 132 5.10 Estimated parameters from the log-logistic model used to fit the data set for the mortality assessment after prosulfocarb application...... 133 5.11 Estimated parameters from the log-logistic model used to fit the data set for the visual assessment after iodosulfuron application...... 134 5.12 Estimated parameters from the log-logistic model used to fit the data set for the mortality assessment after iodosulfuron application...... 135

22 6.1 List of herbicides applied on the susceptible standard population G0, the DD2078 and GG2078 sublines for the sand bioassay...... 147 6.2 Parameters and estimated/predicted values for the prosulfocarb dose-response experiments carried out with the pure homozygous wild-type and homozygous mutant sublines for substitutions at position 1781, 1999, 2078 and 2088 of the ACCase chloroplastic gene...... 151 6.3 Parameters and estimated values for the dose-response experiments carried out with the homozygous wild-type subline DD2078, the homozygous mutant subline GG2078 and the susceptible standard population G0...... 154 6.4 Estimated resistance factors and their corresponding conﬁ- dence intervals for each herbicide tested against the homozygous wild-type subline DD2078, the homozygous mutant subline GG2078 and the susceptible standard population G0. 155

7.1 List of the L. rigidum populations tested against the prosulfocarb plus pyroxasulfone tank mix, with their determined resistance proﬁles and origin...... 168 7.2 Herbicide sensitivity for the 13 L. rigidum populations tested against pyroxasulfone at 64 gai/ha, prosulfocarb at 3,200 gai/ha and the corresponding tank mix...... 180

List of Abbreviations

1-ABT 1-aminobenzotriazole a.i. active ingredient

ACCase acetyl-CoA carboxylase, EC 6.4.1.2

ALS acetolactate synthase, EC 4.1.3.18

ATL Atlantis R , brand name for the formulated herbicide mixture {iodosulfuron:mesosulfuron} at 1:5 w/w

BBCH Biologische Bundesanstalt, Bundessortenamt and CHe- mical industry

BIA Built In Adjuvant bp base pairs

CI Conﬁdence Intervals (at 95%)

CV Column Volume

D for KS-test: maximum diﬀerence in cumulative fraction

DAA Days After Application dCAPS derived Cleaved Ampliﬁed Polymorphic Sequence

DEN phenylpyrazoline

DIM cyclohexanedione

DTT dithiothritol

ED50 The Estimated herbicide Dose that is pharmacologically eﬀective for 50% of the population exposed to the herbicide or a 50% response in a biological system that is

25 exposed to the herbicide. 50% is taken halfway between the asymptotic upper and lower limits of the model ePOST early-post-emergence application, from BBCH09 to BBCH11

FOP aryloxyphenoxypropionate gai gram of active ingredient gai/ha gram of active ingredient per hectare

HGCA Home Grown Cereal Authority

HRAC Herbicide Resistance Action Committee

IMI imidazolinone

KCS 3-keto-acyl-CoA synthase

KS-test Kolmogorov-Smirnov test

LB Lysogeny Broth

LD50 Lethal Dose (see ED50)

M mol.L−1

MOA Mode Of Action

NRC Negative Cross-Resistance

NTSR Non-Target-Site based Resistance

P450s cytochrome P450

PCR Polymerase Chain Reaction

PCR-RFLP PCR-Restriction Fragment Length Polymorphism

Pi inorganic phosphate

POST post-emergence application, from BBCH12

PPFD Photosynthetic Photon Flux Density

PRE pre-emergence application, from BBCH00 to BBCH07

26 PSII PhotoSystem II

RF50 Resistance Factor at 50%. A ratio of the ED50 values for the putative resistant population by the sensitive population

RH Relative Humidity

RO Reverse Osmosis

RT Room Temperature

SNP Single Nucleotide Polymorphism

SU sulfonylurea

TBE Tris/Borate/EDTA buﬀer

TSR Target-Site based Resistance

UK United Kingdom

VLCFAs Very Long Chain Fatty Acids

WMW-test Wilcoxon Mann-Whitney test

X-gal 5-bromo-4-chloro-3-indolyl-β-D-galactopyranoside

1 General Introduction

1.1 Ryegrass

1.1.1 General characteristics

Ryegrass species belong to the genus Lolium. They are annual, biennial or perennial monocotyledonous plants of the Poaceae family (Figure 1.1). They are native to Europe, Asia and Northern Africa and have been introduced as agricultural species throughout the temperate regions of the world. Despite being the major causes of hay fever, ryegrass is the most widely grown cool- season grass in the world due to the numerous desirable agronomic traits [1,2] such as high digestibility for all types of ruminants. Ryegrass is also used in lawns, tennis courts, as cover crops in some arable rotations and in soil erosion programs [1]. There is no authoritative source for classification and nomenclature for the genus Lolium. Nevertheless about 10 distinct species are documented, including Lolium multiflorum Lam. (Italian ryegrass) and Lolium perenne L. (perennial ryegrass) for which more than 150 cultivars have been recognised [1,3–6]. Both species are very common in the United Kingdom and Europe [7]. Rigid ryegrass (Lolium rigidum Gaud.) is found in the European Mediterranean regions and is a predominant weed in Australia [7,8]. Discrimination between Italian and perennial ryegrasses at the vegetative stage is difficult as both species have very common morphological characteristics [reviewed in9, Chap. 1]. When they co-exist, they can hybridize to give fertile progeny (Lolium x hybridum Hausskn.) [10] making the characterisation even more problematic, sometimes requir- ing DNA-based diagnostic tests for correct identification [11]. In general, Italian and perennial ryegrass species are diploid (2n=14) but commercial cultivars can be tetraploid [3]. Ryegrass can grow in a wide range of soil types except in very poorly or excessively drained soils and at a lower pH limit of 4.5 [1,7]. A survey conducted in English arable fields showed that L. multiflorum seeds predominantly germinate between October and March

29 CHAPTER 1. General Introduction with the October peak accounting for more than 80% of the total emergence. The autumn-emerged plants were more vigorous and produced more seeds per unit biomass than the late-emergers [9, Chap. 4]. Ryegrass are wind pollinated plants that are propagated only by seeds. Although cross- fertilization is normal, it is possible for some Lolium multiflorum plants to produce seeds as a result of self-pollination [10]. However, the number of ca- ryopses tends to be small and the offspring unfit, e.g. albino or semi-dwarf forms [10, cited in]. Lolium multiflorum is a copious seed producer, and under cultivation, 1,500 kg of clean seeds per hectare can be obtained[10]. In the northern hemisphere, flowering starts around May and can extend to August. Seeds usually ripen within 4-5 weeks after flowering [12, 13].

Figure 1.1: Lolium multiﬂorum Lam. from seed to ﬂowering stage. BBCH growth stages refer to the decimal scale developed by Zadoks et al. [14], see section 2.1.4.

1.1.2 Ryegrass species as a weed

Lolium multiflorum and L. rigidum are the two main ryegrass species considered as weeds of arable crops, in other terms, a plant that grow where and when it is unwanted. In central Europe, L. multiflorum is present in a wide range of crops including cereals, sugar-beets, sunflowers, potatoes, vineyards and maize, with the notable exception of rice [7]. However, it has the potential to be a weed of any crop grown within its geographical range [15]. It is in cereal cropping systems that Lolium multiflorum control is the most critically required. Similarly, L. rigidum is an important weed in the southern Australian grain belt [8]. Throughout the world about 50 million hectares of cereal fields are significantly infested with grass weeds and rye-

30 1.1. Ryegrass grass are present in all the major cropping areas across the four continents [15] (Figure 1.2).

Figure 1.2: World distribution of Lolium species. The areas in blue denote the presence of Lolium species as a weed. The infested area is estimated between 12 and 14 millions of hectares. Map from K¨ottinget al. [15].

The weedy characteristics of the species result mainly from seed return to the soil from ryegrass seed crops. When present in a cereal field, L. multiflorum seeds are shed before harvest, and may persist in soil for up to seven years [12]. Consequently, if not successfully suppressed at the beginning of the new cropping season, seeds may lead to volunteer weeds in several successive arable crops. Australian surveys showed that L. rigidum germination was inhibited if seeds were buried deeper than 10 cm below the soil surface but this is rapidly overcome when seeds were brought up to a depth of 2 cm [reviewed in8]. This has to be taken into consideration in agronomic practices as seedling recruitment can be two to four-fold greater under minimum tillage than under no-till [16]. Overall, weeds are the most damaging organisms affecting crop productivity. It is estimated that they can cause up to 35% yield loss across crops worldwide if no control practices are implemented [17]. Four L. multiflorum plants per square metre in a winter wheat density of 100 plants/m2 were estimated to cause a significant yield reduction of 5% [9, Chap. 5]. This is close to the economic threshold

31 CHAPTER 1. General Introduction as deﬁned by Zanin et al. [18], i.e. the weed density at which the cost of treatment equals the economic beneﬁt obtained from it.

1.2 Herbicides and ryegrass control

Since early ages, several techniques have been developed for controlling weeds so that they cause minimal damage to crops and grains, thus im- proving crop productivity and helping feed the population more efficiently. These comprise control in the field before and at harvest. Pre-harvest control is achieved via physical, mechanical or chemical methods. Physical and mechanical methods include hand-weeding, control via tillage, straw burn- ing or delayed crop planting. Finally, chemical control refers to the use of synthetic organic molecules, commonly known as herbicides. These interfere with normal metabolic plant functions resulting in plant death. Effective ryegrass control requires a combination of different techniques, if not all.

The ﬁrst selective synthetic compound,namely 2,4-dichlorophenoxyacetic acid (better known as 2,4-D) for the selective control of broad-leaved weeds in monocotyledonous crops such as maize and wheat was introduced in the late 1940’s [19]. Since then, more than 300 single molecules, which cover 15 diﬀerent modes of action (MOA), are now listed as herbicides [20] (Figure 1.3). The most recent available pesticide consumption data in terms of metric tons of active ingredient applied to crops and seeds tend to show that of all pesticides, herbicides are globally the main source of expenditure for growers. In 2001, 64% of the total pesticide use in the Unites States was for herbicides products while insecticides represented 26%, fungicides 6% and other chemicals such as rodenticides only 4% [21]. European pesticide consumption over the last nine years (2001-2009) has been relatively stable with an average of 35% of the total volume allocated to herbicides, 41% to fungicides, 12% to insecticides and 12% to other pesticides [22]. It is noteworthy that there was a reduction of respectively 10% and 28% of herbicides and fungicides input between 2008 and 2009. Climatic conditions, the economic context (10% pesticide price increase between 2006 and 2008 in France) and new regulatory directives at the European and national levels may account for this reduction [23–25]

32 1.2. Herbicides and ryegrass control

Herbicides can be classified according to different parameters. The biological target is known in the majority of cases. The letter classification established by the Herbicide Resistance Action Committee (HRAC) has three main axes, (1) disruption of light process, (2) impaired cell metabolism and (3) impaired growth/cell division. Molecules are further grouped according to the enzyme inhibited or the function that they disrupt and the group is finally divided into chemical structures (Figure 1.3).

Selectivity Herbicides can be selective in which case they only kill the weeds with minimal damage to the crops or non-selective in which case they kill all plants.

Contact vs. systemic Contact herbicides destroy only the plant tissues that have been exposed to the herbicide. The meristematic regions or growing points are not always killed and the plant can grow out of the herbicide application. Conversely, systemic herbicides are absorbed by the leaves, the roots or the seeds and migrate through the plant via either a symplastic or an apoplastic route.

Application timings and techniques Herbicides can either be applied before the emergence of the weed (pre-emergence, PRE) or after (post- emergence, POST). In the majority of cases, pre-emergence herbicides are sprayed onto the soil surface as liquid formulations. In rare cases, they are mechanically incorporated to the soil as granules before or at crop planting (pre-plant incorporated).

Residual vs. foliar The primary uptake point of systemic herbicides can either be the leaves (foliar herbicide) or the roots/seeds/hypocotyls (residual herbicide).

Chemical ryegrass control in small grain cereal crops is currently achieved mainly with two single target-site post-emergence herbicides, namely the inhibitors of acetolactate synthase (ALS; EC 4.1.3.18) and acetyl-CoA carboxylase (ACCase; EC 6.4.1.2). Thiocarbamate and other pre-emergence herbicides help reduce weed pressure early in the season.

33 CHAPTER 1. General Introduction n O OH O As) Cl 3 m H CH m O H N F N LCF O Propha Flamprop- V Alkylazines Carbamates

O NH 3 m N CH F N H N O N Inhibition of Inhibition s m m C H N Inhibition of Inhibition 3 N H H 2 Chlorpropha s iazifla NH N Tr Indazifla Cl cellulose synthesis cellulose NN O Semicarbazone Benzamide Phthalamate F (inhibition of of (inhibition Other C F 3 microtubule organisation microtubule H N H Inhibition of cell divisio cell of Inhibition O F Other m e O N H O O N 2 O N H azolocarboxamide + N Cl l O -sodiu 3 i O O Na O N N H O n L H N S O N Carbetamid N H Tr O K N H O s N O 2 Naptalam O e K O N Isoxaben Flupoxam Arylaminopropionic acid Arylaminopropionic H O N S P O F O O O Inhibition of cellulose synthesis Unknown mode of action Inhibition of lipid synthesis (not ACCase) Inhibition of lipid synthesis (not Inhibiton of glutamine synthetase Inhibition of DHP Inhibition of microtubule organisation Inhibition of cell division (VLCFA) Uncoupler of oxidative phosphorylation Auxin transport inhibition Inhibition of microtubule assembly Synthetic auxin O S S Diflufenzopyr H O F F Benazolin-ethy Cl F O N Quinolinecarboxylic acids Quinolinecarboxylic F F Piperophos O F F Pyroxasulfon

N N

Cl F N O

F O OH Cl Cl l

n N S 2 2 N

m N l N N S CN O NO NO O (10) (18) (3) (23) (15) 21) (20, (24) 26) (8, (4) (19) 25,) (17, buta iflurali N O O 2 Tr Te H Dichlobeni O N

Chlorthiamid Cl Cl

1 2 3 N Benzamides Quinclorac

Quinmerac MCPB

OC N N Dinitroaniline O H I K K K L M N O P Z O O enylchlor H H F F S Th Cafenstrole F O Cl Cl OH Cl O OH O OH O Cl N 2 N 2 2 2 H O N n O NO NO OH N H NO NO O l 2 r 2 acglobal.com P S O Cl O O A NO NO S O Oryzali A TB ndimethalin iclopy Ethalfluralin O Pe inhibition Tr N s MCP O S

O O OC N Cl Cl Cl Cl F F N Nitriles Propyzamide = Pronamide Anilofos F N 2 Auxin transport Auxin Propisochlor .hr A Cl Cl H Mecoprop = MCPP CMPP s O F O O Cl Cl F O OH O N 2 OH 2 P e N H Cl Cl 2 2 NO NO O Cl n Cl O Cl H N O NO l NO a N O OH 2 l N hiazopyr Butrali O N Cl T NH N O Growth/Cell Divisio Growth/Cell 2 P Dinitramin Cl O Cl H Dicamb Picloram F N Cl O Clomeprop F F OCN s F S F F O O O OC N Dichlorprop=2,4-D Cl Cl Cl Chlorthal-dimethyl = DCP Mefenacet N Propachlor Pretilachlor S Cl F S Acetamide www OH Cl Oxyacetamide 2 O OH F O O OH 2 O NO OH F N 2 2 Cl NH Cl O Inhibition of Inhibition r NO NO l N OH O O Cl O O D O S P e N O Dithiopyr Cl d N Butamifos O t N 2 N O 2,4- O O O N H Cl F O Fluroxypy Cl NH N Clopyralid Chloramben N Benefin = Benfluralin F S OC N F N microtubule assembly microtubule 2,4-DB F O Cl F thoxami O trazolinone Cl ntrazamide F Flufenace NN O O Pe N Metolachlor F N Fe Napropamid Cl S Cl N Te Cl Inhibition of photosynthesis PS II Inhibition of pigment synthesis (bleaching) Inhibition of PDS Inhibition of DOXP synthase Inhibition of DOXP amino acid synthesis) Unknown target Lipid synthesis inhibition (inh. of ACCase) of Lipid synthesis inhibition (inh. ALS (branched chain Inhibition of PS I electron diversion Inhibition of protoporphyrinogen oxidase Inhibition of 4-HPPD Inhibition of EPSP synthase Cl 2 s F NO F OH Benzoic acid Benzoic F 1 d s CI Cl O Cl l l O N

e r 2 d N H K N O O P S O O NH N

N N Amiprofos-methyl CI Aminopyrali

N H OC N O OC N N O N 12) ( (1) (2) 7) 6, (5, (22) (14) (27) 13) (11, (9) Cl Auxins Pyridine Metazachlor Naproanilide O Dimethachlo N Ipfencarbazon S Dimethenami F

1 2 3 4

A B C D E F F F F F G ( ) WSSA Group 2010 Syngenta by produced and Designed www.hracglobal.com from downloaded be can poster this of copy free A F l Cl O O N O l Benzoic acids Benzoic d r r O O N OC N Alachlo OC N Synthetic Synthetic Butachlo Acetochlor Diphenami O Pyridine-carboxylic acids Pyridine-carboxylic O Phenoxy-carboxylic acid Phenoxy-carboxylic e O O Phosphoroamidates O N N O n N Ethofumesat H N N O -triazolinones N O + Benzofuranes Cl O H N Na O S N O S O N O S ase) O O N O C Propyrisulfuro O N O Sulfonylamino-carbonyl Sulfonylureas e Carbamate O F Propoxycarbazone-sodium N F AC F F O F O rnolate N O N O O O O N N F O N O S Ve O O O Benfuresat N Chloroacetamides + O O N N S n N N N N N N N N H Na O Thiocarbamates O (not (not S O Phosphorodithioate N O H O N O N H O H H N N F S O O O S F N H itosulfuro N H OO O N O O O S Asulam O SO + F Tr S F S O O F Na O iflusulfuron-methyl iencarbazone-methyl O O ifloxysulfuron-sodium O N Tr P N S Flucarbazone-sodium F l Tr Th N F F O O S F N DHP-inhibition DHP-inhibition Lipid synthesis inhibition synthesis Lipid O 2 S N O H O O O N O N S O i-allate ocarbazi Tr Phenylpyrazoline (DEN) Phenylpyrazoline Bensulide O Ti N H N N N N N N Cl N N N O n S + Cl O N N O N H H OO O N O N Na O N H OH 3 N Cl Cl O S H N N CH N H N H O I O iasulfuro b NH O SO N H O SO O O S O O Tr O SO Pyrimisulfan O Sulfosulfuron S ibenuron-methyl O O ifensulfuron-methyl Pyrimidinyl (thio) benzoates (thio) Pyrimidinyl S Tr O N Pyrithiobac-sodium N O n O O O O m Th O F F b O

O O S Cl N xydi O O SN O O O O O ko F F F F O O O O bulate O al O l Pinoxade SN l O N N N N N O Tr SN Pe N N O O N N O Prosulfocar N N N Quizalofop-P-tefuryl n N N O N N N O N H N Glutamine Glutamine O N H O O 3 N iobencarb = Benthiocar H O N O O O N H O N H S O O Th CH Cl H 3 N O Cl O F O N H Cl O S O O O O N H F S CH O O Pyriftalid O N H N H O S Prosulfuron Rimsulfuro S O O O O O S F O O O S O O N O N O Pyriminobac-methy Pyrazosulfuron-ethyl N O Primisulfuron-methy Sulfometuron-methyl N Cl N O O synthetase inhibition synthetase O O N O O N Cl O S O O A O O S O O N O N O O praloxydim O O O O O O TC H

l + N Te N Sethoxydim O N N N N Propaquizafop N O Molinate N N N N N Orbencarb N n N N Na N N N N Quizalofop-P-methyl H O N O O N H H Cl O H O N S O N H O O O N H O O O N F Cl O N H O O N H O S O H O N Cl S O O H N Cl O S O N H O Cl O S Phosphinic acids Phosphinic O O N S O OH O O 3 N H O Oxasulfuron Nicosulfuron O Pyribenzoxim Inhibition of Inhibition O O O N CH OH Orthosulfamuro O O N N Bispyribac-sodium EPSP synthase EPSP m N Metsulfuron-methy 3 N O N O O Mesosulfuron-methyl O O N O O OH O b N H N CH H S O N O F O O N C H N O O N O 2 SN O O O 3 N O O O O F O Metamifop O EPT O l O O Cycloxydi Profoxydim acids NH O H CH O Esprocar F O N N F N N . . n m N Flupropanate N N N N N N N H S F O F S 2 O O H N O N H O Bialaphos H N O N H N H O O N H NH H S O O O O O S Cl + H N O H 4 N 3 P O O N O O F N O O Cl O S O + N S N S O N H O S G Na O O CH ramsulfuron NH S Glufosinate-ammonium Pyroxsulam Na + Iodosulfuron O N Flupyrsulfuro OH P Fo O Imazosulfuron N O -methyl-sodium -methyl-sodiu O N O O N N OH Cl N C O Glycines O N F m 3 Halosulfuron-methy m N I H N N O H F N O O F N Cl O O N O OH O OH H Cl O O O S O O O N N H O O Clethodi Cl O O O O Butroxydi O Cycloate O Dalapon O F F N N S N N N Cl Cl O Dimepiperate n Haloxyfop-P-methyl N N N Chlorocarb O N m F N N m N H O F H O N S S H O N F F S H H O N H O N H Cl O H N H O N F F O O O S+ O O N H 3 O Sulfosate N H O O 3 O H Glyphosate N S ) noxsula N H O N H S N N F O O 3 O S N N O CH S S O F O Metosula Pe H 3 H N PN O O F Flazasulfuro PN O H OH N O H O Ethoxysulfuron O Flucetosulfuron (C O N Cyclosulfamuron N F CH O N O O O m O O O N O O Ethametsulfuron-methyl O H H e N N O N O O Cl O O O O O N Alloxydi O O O O N O O O Butylat noxaprop-P-ethyl O N N 2 N N N S Fluazifop-P-butyl F N N F F ase) F Fe n N N N N N OO O NO H O O N m H O N N H N H C O N H O S F O H N O S O O N H O 2 N H O H N F F O O O O S O S O O Cl OH NO N H O H N N N N H S O O N N O S Florasula AC N N Dinoterb S l 3 l Cinosulfuron Flumetsulam Azimsulfuron Chlorsulfuro O H O N O N N N CH O Chlorimuron-ethyl Cl O Bensulfuron-methyl F O N O N O N O N O Cl O O O O O l O O 2 Diclofop-methy Cyhalofop-buty Cl Cl Cl O F 2 NO O N H Cell Metabolism Cell N N H N N H O H N H N m S NO N S O 2 O N N b O N H N O 2 N OH NO Cl N O N O N N N N O l Imazapyr OH NO DNOC Imazaquin Diclosula d Dinose O 3 N Imazethapyr N H N O Amidosulfuron O SO O O CH H O O Cloransulam-methy H H O O O N N N SO S (inhibition of of (inhibition O F F O O largonic aci N H Pyributicarb Lipid synthesis inhibition synthesis Lipid Pe O N F O O O H NN N H Clodinafop-propargy N s N H N O Cl N + O N O Cl N O Cl O H Imazapic Uncoupler Uncoupler + 2 3 Imazamox A a O N H O N H CO CH A O N 7 7 ) ) H O 2 2 Acid ON Imazamethabenz-methyl O N H H N H MSM orld of Herbicides of orld O (C (C O O - Oleic As Methyldymron Cyclohexanediones (DIMs) Cyclohexanediones O Oxaziclomefone H (membrane disruption) (membrane O Cl + Na Dinitrophenol S O M riazolopyrimidines S Metam T Indanofan O O ALS (branched) ALS N H Cl Aryloxyphenoxy (FOPs) propionates H N Imidazolinones Cl O d O OH P samine O Fo O of action of Etobenzani O chain amino acid synth.) acid amino chain O N 2 Inhibition of of Inhibition H Unknown mode Unknown 3 N O S + s O Na H N C O N H Cl s B O Nitriles Phenyl-pyridazines + O Na N H DSMA As Z O O Cl O Saflufenacil F N Other Dymron = Daimuron Thiadiazoles Pyrimidinediones N O Br F CN O F F H N O NN O The W The CN OH l O l Cl O O O O H Pyridafol N N n N t n H N S N Cl O Propani N O Bromoxynil (also M) SS + Br O O F N H N Cl F S Dazome Amides idiazimi N Cumyluro N Cinmethylin Cl Metilsulfate Difenzoquat NN N Pyraclonil S Butafenacil Th N O - O 4 O 2 N O N N Cl Fluthiacet-methy N Diphenyl ether Diphenyl SO 3 NO N I N N Cl O N CH According to HRAC classification on mode of action 2010 O O Cl Cl F e F F + O S O O O N Cl + S O N Cl NO S O CN OH O 2 N O O OO O l H Br O N O Pyridat + OH N H O Cl O O H N O N O l O O Ioxynil (also M) 2 O I -ethyl O ntanochlor O F N H O Pe Bromofenoxim (also M) Br Br O Cl O N O O O Lactofen C O Cl O F O Chlorflureno Bromobutide N Profluazo Halosafen O O H Oxyfluorfen H N Cl O N Benzfendizone Flufenpyr H N Cl F N O H F N F O F F e F O S O F F F N + F F F F F O F F N O F O O O n H N S O O N N 3 O N H N O O H N H CH + Bentazon O O O O N n H N O O Cl O O buthiuro Siduron F S Neburon Cl H N O Te O

NN N-Phenyl-phthalimides O N mesafen O O O Cl O Fo Cl Flumioxazi Cl O F Cl O Ethoxyfen-ethyl N O O Flumiclorac-pentyl Cl Fluoroglycofen-ethyl 4-HPPD O F F H N O F F F O + F F O N + F N O Inhibition of Inhibition F F H N N N F O F O N O O O N O N O F Cl N O Cl O O N H N O Cl O Cl N H N F O N S O O F S N O O F Metoxuron O F Monolinuron Oxazolidinedione F Metobromuron O O Cl Cl Bifenox ntoxazone Ureas Methabenzthiazuron O N O O N Pe O Cl Sulfentrazone O O Cinidon-ethyl 2 N H Pyraflufen-ethyl Cl O Chlomethoxyfen Cl Cl Cl S ON O Br N Cl SO Diphenylether O O O F O O F Benzobicyclon Bicyclopyrone F O N N N O F Benzothiadiazinone + Cl O O Cl O N OH H N O O l O Br O H N O m F Cl O H N N H N N Cl N Cl F F O F S O N N enuron O O Isouron Linuron O F Inhibition of Inhibition O Light Processes Light N Isoproturon Cl S N H O O O + Cl e O

Phenylcarbamates Cl S O Na O O Fluazolate Fluometuron (also F3) Oxadiazon F Cl O N N F Cl Uracils O Cl N Cl Cl O F O F Acifluorfen-sodiu Cl O N Carfentrazone-ethy O N O mbotrione O O N H pramezone N N N Pyrazoxyfen F Sulcotrion O Te photosynthesis at PS II PS at photosynthesis To O N Aclonifen OH F O N O H N O F Cl F H N O F

N O 2 2 O S O N H XP synthase XP e O NH O Cl H N O N H N O O N F 2 Cl H O N F NH O O N F S O N N Inhibition of of Inhibition N S N O S Cl O Cl DO H O N O O O Dimefuron O N O H N N Ethidimuron Chloroxuron N O erbacil O Chlorotoluron O T O Chlorobromuron Pyrazolynat N C + S F Cl O N O O Cl S S Oxadiargyl O N O O Cl O O O Phenmedipham H N N Bencarbazone l OO Cl O S Cl S Cl Br O F N O O efuryltrione O Isoxaflutole T Mesotrione (also C) O Isoxachlortole O N 4 F O OC O Fluometuron O F N O N O N F OO F N H H N N H O O N H H Inhibition of Inhibition N N Cl e s F N F F O F N N O Cl N F Diuron S H N O O O F N S N Cl O N Cl m N Cl NN F O O rbutryne H N O rietazine Lenacil F S T rbuthylazin N Te N Cl Metribuzin O N Azafenidin N O N 2 N F Te O H Cl Phenylpyrazoles H N H N N n N N O Cl N H H O N O N Pyrasulfotole N Desmedipha Amitrole N N protoporphyrinogen oxidase protoporphyrinogen N O 2 OH of lycopene cyclase) Cl O O H N N N 2 Picolinafe Benzofenap Norflurazon N H H N H N H N H N (Inh. N N N Cl O Clomazone Oxadiazole e N N N N 1 N H AFFECTING: F O N N F F S N Cl F N N O N Cl F E ON F H N O F Cl Cl C Simazine N erbumeton Simetryne Propazin N N N Bromacil T Metamitron H N H N F N H N H F O F Br O O Diflufenican N F H N H N Fluridone O O N O Flurtamone Cl N H Flurochloridone N H n F H N O N H e + N riazolinones n N N N F F T N N O N F t S N N O F N N O F S N N N

N H Prometo N Prometryn Desmetryne raqua Hexazinone NN N Dimethametry N Pa N H Cl N N H Chloridazon/Pyrazon H N S N N 2 H O + H 2 N CN NH O Cl Beflubutamid N H Br N O N H H N F N Unknown target Unknown e + N FF N N N N N Cl F Cl N O

NH N Atrazin N Ametryne Cyanazine Amicarbazone N Diquat N H N + N H N 3 H N S HERBICIDES HERBICIDES riazines T F Br riazinones synthesis (bleaching) synthesis T Inhibition of pigment of Inhibition PS-I-electron diversion PS-I-electron Inhibition of PDS of Inhibition Pyridazinone Bipyridyliums 1 F D F

riazolinone T

Figure 1.3: The World of Herbicide according to HRAC classiﬁcation on mode of action, 2010. Source: http://www.hracglobal.com/Portals/5/moaposter.pdf

34 1.2. Herbicides and ryegrass control

1.2.1 ACCase-inhibiting herbicides, HRAC A1

ACCase-inhibiting molecules are selective, systemic, post-emergence herbicides that kill grass weeds only. They act by inhibiting the enzyme acetyl- CoA carboxylase that catalyses the first committed step for the de novo biosynthesis of plant fatty acids. This involves the ATP-dependent carboxylation of acetyl-CoA into malonyl-CoA in a two-step reversible reaction. The ACCase enzyme has three different functional domains including the structural biotin carboxyl carrier (BCC) domain and two catalytic domains, namely the biotin carboxylase (BC) and carboxyl transferase (CT) domains. Each catalytic domain catalyses one step. In higher plants ACCase is found in plastids and in the cytosol. In Poaceae, the three domains are fused into a single peptide in the following linear arrangement NH2-BCC-BC- CT-COOH. The active ACCase is composed of two of these peptides and is called homomeric isoform. Conversely, two different isoforms are found in the majority of non-Poaceae plants, including a homomeric form located in the cytosol and a heteromeric form in the chloroplast. The heteromeric form is composed of four distinct subunits. Two of these constitute the CT domain (α-CT and β-CT subunits), and the other two the BC and BCC domains (Figure 1.4). ACCase inhibitors are more potent against the chloroplastic homomeric form than the cytosolic homomeric form of the enzyme. The heteromeric form is insensitive to ACCase inhibitors at the usual recommended field rates and is the basis of selectivity between monocotyledonous and dicotyledonous plants. The CT-domain is the primary target of ACCase inhibitors [29].

There are three diﬀerent chemical families of ACCase inhibitors, i.e. the aryloxyphenoxypropionates (FOPs), the cyclohexanediones (DIMs) and the phenylpyrazolines (DENs). FOPs molecules are formulated as esters to better penetrate the leaf surface and are rapidly converted into free acids once absorbed [30]. ACCase inhibitors have been reported to either be competitive, uncompetitive or mixed inhibitors depending on the herbicide and the species studied [31, 32]. Since their introduction in the mid 1970’s, ACCase inhibitors have been the favourite compounds for grass weed control

1This section is mainly based on work published by Nikolau et al. [26], D´elye [27], Sasaki and Nagano [28].

35 CHAPTER 1. General Introduction in dicotyledonous crops due to the natural tolerance of the heterodimeric plastidic ACCase isoform. Selectivity of ACCase inhibitors in cereals is based for some, but not all, compounds on diﬀerential metabolism enhanced by the use of safeners, which are compounds that protect the grass crop from herbicide injury without reducing herbicide activity in target weeds [33].

Figure 1.4: Acetyl-CoA carboxylase isoforms present in higher plants. The transit peptide (TP) enables the ACCase homomeric isoform to be directed into the chloroplast and is cleaved after migration. BCC: biotin carboxyl-carrier, structural domain; BC: biotin carboxylase and CT: carboxyl transferase are the catalytic domains. In diploid grasses, the homomeric isoform is encoded by a single nuclear gene. Source: D´elye [27].

1.2.2 ALS-inhibiting herbicides, HRAC B2

ALS inhibitors are generally more versatile compounds than ACCase inhibitors. They can be either selective or non-selective, applied post-emergence or pre-emergence. They are systemic and control a wide spectrum of weeds including monocotyledonous and dicotyledonous plants. They act by inhibiting the enzyme acetolactate synthase (ALS) which is located in the chloroplast. ALS catalyses the ﬁrst committed step in the synthesis of the branched-chained amino acids leucine, valine and isoleucine [37]. ALS is also

2This section is mainly based on work published by Tranel and Wright [34], Duggleby et al. [35], McCourt and Duggleby [36].

36 1.2. Herbicides and ryegrass control found in bacteria and in the mitochondria of fungi but is absent in animals resulting in low mammalian toxicity. The enzyme consists of one functional subunit and one regulatory subunit. The functional unit is of about 60 kDa depending on the species and is catalytically active. The regulatory subunit enhances the catalytic activity of the first subunit and is essential for negative feedback. ALS is encoded by a single nuclear gene. There are five different chemical classes of ALS inhibitors, i.e. the sulfonylureas (SUs) that were marketed first (approx. 1980’s), the imidazolinones (IMIs), the sulfonylamino-carbonyl-triazolinones (SCTs), the pyrimidinyl (oxy/thio) benzoates (PBs), and the triazolopyrimidines (TPs). The mechanisms of inhibition of SUs and IMIs have been clearly elucidated with crystal models and enzymatic studies with ALS from yeast and Arabidopsis thaliana (L.) Heynh [35, reviewed in]. Herbicides bind preferentially but not exclusively to the enzyme-bound hydroxyl-thiamine diphosphate intermediate within the substrate channel of the functional subunit and inhibit the enzyme by blocking the access of the substrate to the active site. At the enzyme level, SUs are more potent than IMIs.

1.2.3 Thiocarbamate herbicides, HRAC N

Thiocarbamate herbicides were introduced to markets as early as the 1960’s. They are broad-spectrum systemic selective compounds used in a wide range of cropping systems including rice and cereals. They are usually soil incorporated like triallate but can be soil applied at pre-emergence or even post-emergence like prosulfocarb. Contrary to ACCase and ALS inhibitors, the precise molecular target of thiocarbamate herbicides remains unknown and they are often said to have multiple sites of action. They are pro- herbicides, i.e. a bioactivation phase is required to reveal a more toxic sulfoxide group [38]. However, due to the need for soil incorporation for most thiocarbamates and the changing patterns in crop management, their usage has globally decreased over the past 20 years (Dr. Shiv Shankhar Kaundun, personal communication).

Indications of thiocarbamate primary target are provided by research on the chloroacetamide herbicide family (HRAC group K3). These two dissimilar classes of herbicides result in similar injury symptoms, i.e. stunting,

37 CHAPTER 1. General Introduction shortened and thickened leaves, coleoptile swelling, failure of leaves to correctly unfurl, leaf darkening and root damages (Figure 1.5). It is now clearly established that both N and K3 compounds interact with the biosynthesis of very long chain fatty acids (VLCFAs, C20-C36) [39–42]. VLCFAs are associated with very different cellular functions; cell proliferation, differentiation and death [reviewed in 43]. In higher plants, VLCFAs are synthesized by the sequential addition of two carbons on precursor molecules originating from the plastids via four successive enzymatic reactions within the endoplasmic reticulum membrane-bound multi-protein complex named elongase. The first step is the condensation of a long chain acyl-CoA with a malonyl-CoA by a 3-keto-acyl-CoA synthase (KCS or condensing enzymes) [44]. The product is then reduced by a KCR enzyme, dehydrated by a HCD enzyme and further reduced by an ECR enzyme to yield a two-carbon elongated acyl-CoA. The latter is incorporated into different lipid classes comprising triacylglycerols (TAGs), epicuticular waxes, suberin, phospholipids and sphingolipids. TAGs are not involved in plant development but constitute a reserve of energy for germinating seeds. The reduced availability of epicuticular waxes and membrane lipids required for cell wall and membrane integ- rity explain the symptoms observed after herbicide treatment (Figure 1.5). The condensation activity of the acyl-CoA elongase complex is encoded by a very large gene family in A. thaliana whereas only few sequences encode the other components of the same multi-protein complex [45]. Finally, the KCS enzymes are thought to determine the substrate and tissue specificities of fatty acid elongation whereas the three other enzyme families are thought to have a broad substrate specificity and are shared by all tissues exhibiting VLCFA biosynthesis [46].

It is hypothesised that a covalent bond with K3 and N herbicides at the highly conserved cysteine reactive site (thiol site) of the KCS blocks VLCFAs biosynthesis [47]. This implies the availability of an electrophilic C-atom in the herbicidal molecules. For chloroacetamides, after the split of the chlorine, the α-C atom presents an electrophilic reactive site. Similarly, the bioactivation of the thiocarbamates into their sulfoxide form generates an electrophilic reactive carbon. Investigations on elongase speciﬁcity and herbicidal spectrum were carried out via elongases expression in yeast [48]. Out of the 21 genes known at that time to encode KCS enzymes in A.

38 1.2. Herbicides and ryegrass control

Figure 1.5: Injury symptoms photographed 21 days after a pre-emergence application of prosulfocarb on L. multiflorum. To be noted, (1) coleoptile swelling, (2) failure of first leaf to unfurl correctly (3) leaf darkening. thaliana, 17 were expressed in yeast and six were enzymatically active with endogenous fatty acid and/or externally supplied unsaturated substrates. A range of K3 and N chemicals was tested including alachlor (chloroacetamide) and triallate (thiocarbamate). In the presence of herbicide in the growth medium a reduction and a change in elongated products were observed. Ala- chlor inhibited four of the six KCS tested, flufenacet (K3, oxyacetamide) all six, and triallate only one. These results confirmed the inhibition of KCS enzymes by K3 molecules and re-enforce the concept that these herbicides have multiple sites of action. The low level of inhibition conferred by triallate may be explained by the use of the non-activated form. Considering the diversity of KCS enzymes in A. thaliana, it can also be hypothesised that the actual target(s) of thiocarbamates were unfortunately not present in that particular experiment.

The plant enzyme set(s) responsible for thiocarbamates sulfoxidation has yet to be identiﬁed. NADH-dependent enzymes have been shown to metabolise thiocarbamates in mammals and soil microorganisms [49–51]. There- fore, it is legitimate to hypothesise that a similar route exists in plants. However, the use of piperonyl-butoxide as a P450 inhibitor failed to reverse resistance in a triallate-resistant wild oat population, suggesting that they might not be responsible for thiocarbamates sulfoxidation in plants [52, 53]. As P450s are a large isomorphic family, evidence for their contribution to sulfoxidation should be further investigated. Although the thiocarbamate

39 CHAPTER 1. General Introduction sulfoxide results in enhanced herbicidal activity, this functional group is also suitable for conjugation with the glutathione thiolate anion (GSH) which may account for herbicide degradation in plants [38]. For instance, the safener dichlormid applied with EPTC is thought to increase glutathione conjugation by elevating the level of GSH [33].

1.2.4 The evolution of herbicide resistance

The overreliance over the past 30 years on ACCase and ALS inhibitors for ryegrass control has resulted in the evolution of resistance. Resistance is defined as the inherited ability of a plant to survive and reproduce following exposure to a dose of herbicide normally lethal to the wild type [20]. This feature is not limited to ryegrass species and by end of 2010, 42 different monocotyledonous weed species were reported resistant to ALS inhibitors, 40 to ACCase inhibitors and 13 to both ([54], Figure 1.6). It is noteworthy that only five monocotyledonous weeds were recorded as resistant to thiocarbamate herbicides or K3 compounds (Figure 1.6). Ryegrass species are listed as the most important resistant weed species in the world [54]. After the revolution brought by chemical control, weed management practices are evolving in order to limit the development and spread of herbicide resistance and to ensure that crops can be grown sustainably.

1.3 Herbicide Resistance

It is now accepted that herbicide resistance most often results from repeated applications of the same chemical or mode of action (MOA) in a given field. The lack of integrated weed management practices such as limited crop and/or herbicide MOAs rotation, absence of fallow and no-till systems, increase the risk of herbicide resistance evolution and spread. Resistance mechanisms can be grouped into two categories; (1) the modification of the site of action itself also termed target-site resistance (TSR) and (2) any other mechanism that does not affect the target, known as non-target-site resistance (NTSR). In the latter case, the most common mechanism is the enhanced metabolic degradation of the herbicidal molecules. The toxicant undergoes chemical modifications mediated by several enzyme sets that lead to an inactive molecule. Detoxification rate is rapid enough to prevent plant

40 1.3. Herbicide Resistance

40 ALS ACCase ALS+ACCase thiocarbamates 30 K3

10 number of reportednumber resistant species 0 1980 1985 1990 1995 2000 2005 2010 years

Figure 1.6: Evolution of the number of reported herbicide-resistant monocotyledonous weed species from 1980 to 2010. ‘ALS+ACCase’ denotes weed species that have evolved herbicide resistance to both classes. Data from Heap [54].

death. Other mechanisms include impaired translocation from the point of uptake to the biological target. Conversely, for target-site based resistance, the herbicide does reach its target but cannot bind to it properly. This results from either the overproduction of the site of action causing a ‘dilution’ eﬀect of the herbicide or a mutated target resulting in site insensitivity. Weeds have evolved resistance to more than one particular herbicide (e.g. Figure 1.6). Cross-resistance occurs when a weed population is resistant to two or more herbicides (related or unrelated chemistries) due to the presence of a single resistance mechanism. Conversely, multiple-resistance refers to situations where resistant plants possess two or more distinct resistance mechanisms, e.g. target modiﬁcation and enhanced metabolism [55]. Finally, although relatively rare, negative cross-resistance (NCR) arises when the resistant trait acquired causes greater sensitivity to other herbicide classe(s) than susceptible populations [56].

41 CHAPTER 1. General Introduction

1.3.1 General comments on enhanced metabolic-based resistance3

Herbicide metabolism is usually divided into three steps; (1) phase I or activation step or functionalisation when the molecule is oxidised, reduced or hydrolyzed to introduce or reveal a functional group, (2) phase II; the activated molecule is conjugated to either glutathione or glycosyl moieties by the respective transferases and (3) phase III; the conjugate is eliminated from the cytosol via sequestration in either the apoplast or the vacuole.

The metabolic attack starts directly after herbicide penetration through the epicuticular waxes and involves the multigenic family of cytochrome P450 mono-oxygenases (P450s, EC 1.14.14.1). More than 60 isoforms have been identiﬁed in A. thaliana [58]. P450s are haeme-thiolate membrane- bound enzymes of about 55 kD located in the endoplasmic reticulum. The sequence around the haeme of ten or so amino acids is highly conserved within species. The rest of the protein sequence is extremely variable. The main reaction takes place at the haeme and consists of a NADPH-dependent mono-oxygenation reaction. One atom of molecular oxygen is incorporated into the herbicide, while the second is reduced to form water. The most common reactions are the hydroxylation of aromatic rings or alkyl groups and + the release of heteroatoms. The overall reaction is: XH + O2 + NADPH,H + → XOH + H2O + NADP , where X represents the herbicide backbone. Conjugation is mediated by either glutathione S-transferases (GSTs, E.C 2.5.1.18) or glycosyltransferases (GTs, E.C 2.4.1.-). The diversity of GSTs isozymes allows the proteins to detoxify a wide range of chemicals and to be involved in the synthesis of various secondary plant metabolites. GSTs are homo or heterodimeric cytosolic proteins with subunits of just less than 30 kD each. They can be divided into several classes according to sequence sim- ilarities and catalytic functions, but only the φ- and the τ-classes of enzymes are responsible for herbicide metabolism in plants [59]. GSTs catalyse the attack of the glutathione thiolate anion (GSH) on an electrophilic substrate, which is either the herbicide itself or a derivative activated by P450s. The complex so formed is more polar and less toxic. The overall reaction is: XZ + GSH → XSG + HZ where Z is a halogen, a phenolate or an alkyl

3This section is mainly based on the review published by Yuan et al. [57]

42 1.3. Herbicide Resistance sulfoxide and X the herbicide backbone.

Glycosyltransferases (GTs) conjugate a sugar to the herbicide or its metabolites. GTs are soluble membrane-bound enzymes composed of one or two polypeptides of around 50 kD. They are also multigenic families. They require a molecule of uridine-diphosphate-glucose (UDP-glucose) as a sugar donor. Single or multiple glycosylations can occur at -OH, -COOH, -NH2 or -SH groups [60]. Similar to GSH conjugation, the addition of a sugar renders the molecule more polar, less toxic and prevents its free movement across the membranes of intracellular compartments. Glycosyltransferases are classed into O-glycosyltransferases (O-GT) or N-glycosyltransferases (N-GT) according to the lipophilic acceptor group. The overall reaction is: UDP- glucose + X-OH → glucose-O-X + UDP, where -OH can also be -COOH, -NH2 or -SH. The conjugated metabolites might still exert some biological activity. To avoid any interference with the plant metabolism, they are excluded from the cytosol and transferred to the apoplast or stored in the cell vacuole. Glutathione conjugates are sequestrated into the vacuole via speciﬁc ATP-dependent transporters also called ATP-binding cassettes or ABC transporters [61, 62]. It is a directly energized mechanism that uses the energy produced by the hydrolysis of a free ATP molecule. The case of glycosyl conjugates is less clear. It is hypothesised that two types of transporters intervene. If structural analogues to the conjugate are endogenously present in the plant/cell the conjugate would be taken up by an antiport mechanism and excluded into the vacuole. If not, speciﬁc ABC transporters would be used [63, 64].

1.3.2 General comments on target-site based resistance

Non-synonymous substitutions or deletions in the nucleotide sequence of the target enzyme may cause structural modiﬁcations that result in the inca- pacity for the herbicide to bind to its usual niche. Codon deletion has been reported for only one class of herbicide, the protophorphyrinogen oxidase inhibitors in waterhemp (Amaranthus spp.) populations [65]. Target-site resistance trait can be dominant or recessive, maternally inherited or not, and results in high or low levels of resistance depending on the herbicide

43 CHAPTER 1. General Introduction classes affected and the species (e.g. [66, 67]). On the other hand, the overproduction of the target alters the ratio of available binding sites to herbicide molecule causing a ‘dilution’ effect. When more sites are available the targeted biochemical pathway is not totally impaired resulting in herbicide resistance. Target overproduction refers to two types of mechanisms. Firstly, the gene itself may be amplified meaning that there is a higher number of copies in the resistant plant compared to the suceptible plant. This results in the overproduction of mRNA and therefore the overproduction of the target. This mechanism has recently been revealed in Amaranthus palmeri S.Wats. populations from Georgia that have evolved resistance to glyphosate [68]. Target overproduction may also occur with a single copy of the gene. In that case, there may be overproduction of mRNA due to induced transcription or enhanced stability of the mRNA itself. This mechanism was also reported for glyphosate resistance but in a L. ridigum population [69].

1.3.3 Resistance to thiocarbamate herbicides, ACCase and ALS inhibitors in Lolium spp. populations

Thiocarbamates

Documented cases of thiocarbamate resistance in ryegrass species are limited to the multiple-resistant L. rigidum population SLR31. This population was collected in 1987 from a field near Bordertown, South Australia [50]. Since then, SLR31 has been studied at great length indicating resistance to several modes of action including ACCase, ALS, and microtubule assembly inhibitors [70–73]. SLR31 seed stocks have been maintained and bulked in the absence of herbicide selection in Australia and are now commercially available through the seed company Herbiseed (Twyford, UK). Tardif and Powles [50] reported a small but significant shift towards resistance to triallate in SLR31. Interestingly, triallate was never applied in the field where SLR31 was harvested [73]. The P450 inhibitor malathion had no synergistic effect on triallate suggesting that (i) P450s may not be involved in triallate degradation or (ii) the activity of the specific P450s was not suppress by malathion [73]. Interestingly, a post-emergence mixture of chlorsulfuron, against which SLR31 is highly resistant, with triallate showed rather interesting and intriguing synergistic effects that lead to the control

44 1.3. Herbicide Resistance of SLR31 with 20 g chlorsulfuron/ha supplemented with 750 gai/ha triallate [74]. Further work is critically required to unravel the complex interactions between these two molecules and their ability to suppress multiple herbicide resistance in SLR31.

ACCase inhibitors

Resistance to ACCase inhibitors was first reported in the early 1980’s in L. rigidum populations from Australia [75, 76]. Since then 40 grass weed species have evolved resistance including Echinocloa spp. in rice cropping systems and Phalaris spp. in India [77–79]. Target-site resistance is due to a single nucleotide change in the coding sequence of the nuclear gene of the chloroplastic ACCase isoform. Resistant alleles are often dominant over the sensitive ones at doses applied in the range of field rates [27]. To date, seven point mutations, all located in the CT domain, have been reported to confer resistance in Lolium spp. populations and are Ile1781, Trp1999, Trp2027, Ile2041, Asp2078, Cys2088 and Gly2096, (numbering according to residue position in Alopecurus myosuroides Huds., see Table 1.1). The occurrence and evolution of these mutations seem to depend on the location. A 10-years survey across South Australia showed that Ile2041 was the most common mutation (50% of the resistant samples in 1998 and 35% in 2008), followed by Asp2078 (17% in 1998 and 23% in 2008) and Ile1781 (9% in 1998 and 20% in 2008) [80]. This contrasts with a British survey that reported Asp2078 as the most frequent mutation present in 57% of the resistant samples collected between 2006 and 2008, followed by Ile1781 while Ile2041 represented only 4% of the resistant plants [9, Chap. 7]. Lastly, the Ile1781 mutation was the most frequent in France (31% of the resistant populations sampled between 2006 and 2009) and Asp2078 the least frequent (6%) [81]. Differences in herbicide usage and selection history between South Australia, the United Kingdom and France could explain the distributions observed. The 1781-Leu allele is fixed in the grass species Poa annua L., Poa supina L. and Festuca rubra L. [82]. Natural tolerance to ACCase inhibitors has been confirmed for P. annua and F. rubra [reviewed in 27], but P. annua (annual meadow grass) is the only species considered as a weed in cereal cropping systems.

45 CHAPTER 1. General Introduction eeoe,ie 0FP,8DM n E n u oovoslgsi esn o l ebcdswr sae o ahadevery and each for assayed were herbicides all been not have reasons inhibitors logistic ACCase obvious Nineteen to due assays. and plant DEN whole inhibitor(s) 1 ACCase in and the DIMs identified on 8 were dependent reported. are FOPs, patterns mutation and 10 resistance involved substitution stated, i.e. acid otherwise developed, amino the Unless to according studied. vary patterns Resistance populations. 1.1: Table ,Kudn[ 91 ] Kaundun [ 89 ], al. et Yu prepara- (under al. et Kaundun with Association diclofop-methyl. to resistance Confer detail. myosuroides in ( investigated Not G2096A DIM FOP, DEN DIM, FOP, G2096? Association (FOP). C2088R diclofop-methyl to resistance Confer D2078G resistance detail. confer in May I2041V investigated substitution. Not 1781 with 7] I2041N Associated Chap. [ 9 , detail. Alarcón Reverte in investigated Not May W2027C substitutions. 2096 or DEN. 2078 DIM, or FOP, 2041 with W2027C Associated detail. in investigated Not (DEN). pinoxaden W1999S system gene-replacement least yeast at a via to with determined resistance resistance occur (FOP) confer Fenoxaprop-P-ethyl can detail, residue in W1999L leucine investigated a Not to isoleucine an from change The W1999C DEN. DIM, FOP, W1999C I1781L substitution acid Amino ito h igencetd oyopim SP nw ocne agtst eitnet Caeihbtr in inhibitors ACCase to resistance target-site confer to known (SNP) polymorphisms nucleotide single the of List A. 92 ] [ al. et Petit Délye [ 27 ], is but in pinoxaden. reported documented potentially not as and was alanine FOP acid an amino be substitute to The likely described. not substitutions other only FOP reported. not substitutions other References with (DIM). clethodim to pinoxaden. to resistance confer gene. ACCase plastidic wheat mutated a in using position first the at cytosine a or 84 ]. thymine [ 83 , a codon either cognate by adenine the the of substitution a resistance by affected inhibitors ACCase of Class .myosuroides A. ouain sebelow). (see populations aoee l [ 80 ] al. et Malone [ 89 ] al. et Yu [ 90 ] al. Délye et [ 80 ] al. et Malone ue l [ 89 ] al. et Yu tion) [ 88 ] al. et Scarabel [ 87 ] al. et Liu [ 86 ] al. et al. White et [ 85 ], Zagnitko [ 84 ], al. Délye et Lolium spp.

46 1.3. Herbicide Resistance

Less detailed mechanistic data are available for non-target-site based resistance to ACCase inhibitors in ryegrass species. Studies often target single herbicides which does not permit any generalization. To date, resistance to FOP herbicides appears to be due to enhanced P450 and GST activities. Diclofop-methyl resistance in a L. rigidum population from Australia was significantly decreased by the addition of 1-ABT or amitrole, suggesting the implication of P450s in the resistance mechanism(s) [93]. This feature was also reported in resistant ryegrass populations from Italy [94]. GSTs were also described as potentially involved in diclofop-resistance in UK populations [95]. The resistant populations presented increased levels of constitutive GSTs compared with the susceptible ones. Contrary to insecticide resistance, few biochemical studies have been conducted to characterise precisely the P450s or the GSTs involved in herbicide detoxification [96]. Fischer et al. [97] identified 16 P450 genes belonging to six different P450 families from SLR31, but no linkage to herbicide metabolism could be established. GST-associated resistance has been best studied in A. myosuroides but relies on either total GST extracts or the identification based on antisera raised against the θ-type GST from maize which may not account for all the types of resistance observed [98–100].

ALS inhibitors

Resistance to ALS inhibitors in ryegrass species was first reported in the early 1980’s in an Australian population [75]. Since then 110 weed species have evolved resistance to ALS inhibitors including 42 grasses for which target-site resistance was identified in only nine species [54, 101]. Amongst the eight point mutations documented, only two are documented in L. rigidum biotypes and are namely Pro197 and Trp574 (A. thaliana amino acid equivalent) [101, 102]. Up to six different substitutions have been reported at position 197 in Lolium spp., i.e. alanine, arginine, glutamine, leucine, serine and threonine [103, 104]. Only a leucine substitution has been documented at codon position 574 [103–105]. Substitutions at position 197 seem to predominantly affect sulfonylurea herbicides while the substitution at position 574 confers resistance to both sulfonylurea and imidazolinone herbicides. Unfortunately, cross-resistance patterns with the other three classes of ALS inhibitors were not studied. Nevertheless, dicotyledonous

47 CHAPTER 1. General Introduction species carrying a W574L substitution showed a broad-spectrum resistance pattern affecting the five classes of ALS inhibitors, suggesting that Lolium species may be affected in a similar manner [101]. Likewise, pyroxsulam, the first TP to have been developed for grass control in cereals was reported to be affected by a P197S substitution [106]. The Pro197 and Try574 mutations were predominantly found in populations originating from Australia. To date, only one L. rigidum population from France was reported to carry a P197T substitution at low frequency [107].

Resistance to ALS inhibitors due to enhanced metabolism was confid- ently documented for only five grass species including L. rigidum [108]. Detailed roles of P450s and/or GSTs and/or GTs have not been described. Nevertheless, the identification of chlorsulfuron metabolites in the resistant population SLR31 and wheat; and the synergistic effects of malathion in another chlorsulfuron-resistant population lead to hypothesise the implication of at least some P450s [108, 109]. Unfortunately, enhanced metabolism diagnosis often relies on the invalidation of target-site resistance to ALS inhibitors - as easier to identify - resulting in sparse information on precise degradation pathways.

1.3.4 Overview of methods for detecting herbicide-resistance

The whole plant bioassay is probably the most commonly employed method for detecting herbicide resistance and is required for registering new resistance cases [110]. Seeds are collected at maturity in the ﬁeld, plants are subsequently gown in potting media under controlled environment (greenhouse, phytotron) or outside and treated with a single discriminating herbicide rate or a range of doses. Susceptible and resistant standards are included for comparison. Herbicide resistance is then determined by recording mortality or by visually estimating the biomass reduction/injury or measuring the fresh and/or dried plant biomass. An alternative is to directly collect plants in the ﬁeld and produce vegetative clones [111]. With this approach it is possible to trace an individual over several treatments and provide a more precise resistance pattern. Whole plant assays are relatively time-consuming, a minimum of four weeks is generally needed for completion of the experiment, labour-intensive and only applicable to ma-

48 1.3. Herbicide Resistance terial collected after herbicide application, i.e. at the end of the growing season. However, these tests are essential for detecting resistance. Once resistance is confirmed, the underlying biological mechanisms can be investigated. Numerous DNA tests have been developed to quickly determine whether a specific point mutation known to confer herbicide-resistance is present in a given individual [reviewed in 112]. The most popular assay for ACCase and ALS target-site resistance identification relies on the derived Cleaved Amplified Polymorphic Sequence (dCAPS) technique [83] (see section 2.2.5). This approach is simple, economical, very often transferable between grass species and provide accurate measures of the frequency of the resistant allele in the population studied. Enzyme methods based on the extraction and purification of the herbicide-target can determine how the modifications endowed by amino-acids substitutions affect herbicide binding. These two approaches can be extended to enzymes and genes responsible for metabolic-based resistance. However, very few GSTs or P450s gene/enzymes have been elucidated in ryegrass species. An alternative is to use radiolabelled herbicide to either determine the translocation patterns between susceptible and resistant individuals or to compare the nature and the production rate of the metabolites, or to use herbicide synergists [113]. A synergist does not have by itself any lethal properties, but does significantly increase toxicity when mixed with herbicides. They are used as a tool to determine whether the critical detoxification step resulting in resistance is caused by GSTs or P450s. The number and selectivity of the synergists is still an open question [53, 114]. Tetcyclasis, piperonyl butoxide, amitrole, 1-aminobenzotriazole (1-ABT) and the organophosphate insecticides malathion and terbufos have demonstrated some activity against plant P450 mono-oxygenases [94, 109, 115–119].

1.3.5 Factors inﬂuencing resistance evolution

Putwain [120] defined the selection pressure as the product of selection efficacy and selection duration, in other terms, herbicide efficacy and soil persistence. In 1978, Gressel and Segel [121] were concerned by the slow development of herbicide resistance by contrast with antibiotic, insecticide and fungicide resistance that had rapidly evolved following their introduction. The few reported cases of herbicide resistance were regarded as the excep-

49 CHAPTER 1. General Introduction tion rather than the rule and were considered as laboratory curiosities like the Senecio vulgaris L. population that was the first species not to be controlled effectively by simazine [122]. Their concerns did not last for very long as resistance to ALS and ACCase inhibitors evolved with dramatic rapidity from the 1980’s (Figure 1.6,[54]). To date there are 360 confirmed cases of resistant biotypes worldwide including 197 species (115 dicotyledonous and 82 monocotyledonous weeds) that cover more than 450,000 fields [54]. This is most likely to be an underestimation as the WeedScience.org database does not always include the resistant populations identified during the large weed surveys conducted in the countries. Herbicide resistance evolution is weighted by the evolution of herbicide chemistry itself. The first generation of herbicides, i.e. phenoxy, auxin-mimicking herbicides (HRAC group P) had low efficacy compared to the new generation of ALS and ACCase inhibitors and exerted low residual activity resulting in an overall low selection pressure. Nevertheless, resistance to phenoxy herbicides started to appear in the 1980’s. The resistant individuals were often highly unfit and lacked strong apical dominance showing dramatic fitness costs associated with resistance that probably explain its slow evolution [reviewed in 123]. Conversely, the first ALS inhibitors like chlorsulfuron (introduced in 1982 in the USA) were highly efficient and soil persistent resulting in carry-over concerns for the next crop. Weed control in American winter wheat moved from the use of 2,4-D (phenoxy herbicide) to chlorsulfuron. Target-site resistance to chlorsulfuron evolved 4 to 5 years later in prickly lettuce and Kochia [124–126]. Clearly, herbicide selection pressure has an important influence on resistance evolution and may significantly hamper management strategies since a given toxicant can exert differential selection pressure on the weed species present in the field. There are many other essential factors that rule the resistance evolution process and its spread, including:

• Genetic variation: Mutations are always present whether or not a herbicide is used. To be selected and fixed, the ideal herbicide resistance mutation should provide a significant competitive edge under situations of herbicide selection and be neutral in the absence of herbicide pressure, in other terms, not present fitness costs. The higher the initial frequency, the quicker the resistance may evolve. Stud- ies conducted with L. rigidum populations had estimated the initial

50 1.3. Herbicide Resistance

frequency of ALS target-site resistant individuals in susceptible populations between 10−5 and 1.2 × 10−4 depending on the herbicide used a selector [127]. Triazine resistance is conferred by a recessive mutation on the psbA gene located in the chloroplast [128, 129]. Chloroplastic mutations are thought to occur at lower frequencies than nuclear mutations, and were estimated to be near 10−20 potentially explaining the slower resistance evolution as compared to ALS inhibitors [cited in 130].

• Herbicide use: Resistance has evolved most rapidly in monoculture situations where only one herbicide chemistry has been used. Con- versely, mixtures have proved to have a positive effect on delaying the evolution of resistance [126]. One of the best field example is the use of the triazine/chloroacetamide mixtures that were continuously applied over 20 years in maize monoculture in the USA. The main weed targets, i.e. Chenopodium spp. and Amaranthus spp. had evolved resistance to triazines when they were used alone but have never been reported to evolve resistance where the mixtures were used [130]. Cur- rently, the weed control programs that are implemented in Europe for grass control in winter cereals recommend an autumn application with a combination of different residual herbicides, such as prosulfocarb, to suppress as many weeds as possible as early as possible in order to relieve the pressure put on the post-emergence herbicides; and a spring application that sometimes includes a residual to target any secondary weed flushes that may occur. Emphasis has also to be put on herbicide ‘labelled-rates’. The Aus- tralian agriculture is known to recommend rates that are around half those used in Europe. Besides, as Australian agriculture is not subsid- ised, growers often used below-labelled rates resulting in sub-optimal weed control. It may be no coincidence that ryegrass resistance is by far more important in Australia than in Europe. The link between sub-lethal herbicide doses and resistance evolution has clearly been established by many studies [131–135], thus encouraging growers to follow the recommendations.

• Gene flow: Resistance may spread within a field and from field to field via pollen gene flow or seed movement via contaminated ma-

51 CHAPTER 1. General Introduction

chinery. Once established, the dynamics of the soil seed bank inﬂu- enced by the tillage practices will determine the release rate of resistant seeds and may modify the resistance pattern within the ﬁeld.

1.4 Project speciﬁc objectives

Considering (1) the lack of new herbicide modes of action for ryegrass control, (2) the tightening European regulations on herbicide use and the re- gistration of new products, (3) the numerous ACCase and ALS resistant biotypes of ryegrass across the world and (4) the relatively low occurrence and risk of resistance evolution to thiocarbamates in ryegrass, the current project uses an integrated biological, biochemical and molecular approach to investigate the potential of prosulfocarb-based treatments for the control of sensitive and herbicide-resistant Lolium spp. populations. The speciﬁc objectives were:

• To succinctly (i) determine the limitations of greenhouse-based experiments with prosulfocarb and (ii) present why prosulfocarb is a useful tool for controlling sensitive and herbicide-resistant ryegrass populations (Chapter3).

• To investigate whether resistance to prosulfocarb could evolve over time in a known susceptible L. multiﬂorum population using a recurrent selection process at the recommended ﬁeld rate of 4,000 gai/ha (Chapter4).

• To determine whether high levels of non-target-site based resistance to the ACCase inhibitor clodinafop-propargyl can confer cross-resistance to prosulfocarb in L. multiﬂorum over time (Chapter5).

• To study negative cross-resistance between prosulfocarb and other lipid synthesis inhibitors on wild-type and pure homozygote ACCase target-site resistant L. multiﬂorum sublines (Chapter6).

• To evaluate binary mixtures of prosulfocarb with other herbicides for the control of sensitive and herbicide-resistant ryegrass populations with respect to (i) toxicity on winter wheat and winter barley and (ii) synergism (Chapter7).

52 1.4. Project speciﬁc objectives

• To examine prosulfocarb sensitivity across almost a decade of ryegrass sampling in England (2000-2008) (Chapter8).

The overall output is to gain a better understanding of the usefulness of prosulfocarb for ryegrass management in small grain cereal crops.

2 General Materials and Methods

2.1 Herbicide whole plant bioassays

2.1.1 Pot format

Four types of containers were used:

• Trough: plastic trough of 55 x 8 x 9.5 cm (LxWxH) from Syngenta’s stock (supplier unknown). This format allowed diﬀerent plant species/populations per experiental unit. Seeds were sown in a 6 x 8 cm area.

• 4” pots: 10.16 cm diameter plastic pots from Richard Sankey and Son Ltd., Nottingham, UK.

• 3” pots: 7.6 cm diameter plastic pots from Richard Sankey and Son Ltd., Nottingham, UK.

• EPS punnets: 36.2 x 22.7 x 5 cm (LxWxH) plastic strips from Fargro Ltd, Littlehampton, UK.

2.1.2 Soil type

Three types of soil were used:

• TMA soil: sandy loam compost supplied by East Horticulture, Swan- ley, UK. The compost was regularly analysed by Natural Resource Management Ltd, Bracknell, UK. The composition remained substantially the same throughout all the batches received and was as follows: pH=7.6; organic matter 1.5% w/w; sand (2 mm-50 µm) 61% w/w; silt (2 µm-50 µm): 25% w/w; clay (< 2µm): 14% w/w, cation exchange capacity (meq/100g): 10.4. The soil was not sterilised and therefore probably contained indigenous and undetermined microﬂora.

55 CHAPTER 2. General Materials and Methods

• JIP compost: mixture of John Innes potting compost number 3 with peat at 1:1 v/v ratio. This mix was prepared by the supplier, East Horticulture, Swanley, UK.

• sand: Humax silver sand from Richardson House, Gretna, UK. Grade 1 ﬁlter papers were placed to cover the holes at the base of the plant containers when tests were carried out on sand.

2.1.3 Seed source and storage

Seeds of the susceptible standard populations were commercially obtained from Herbiseed (Twyford, UK). These include a Lolium multiflorum Lam. population referred as G0 and a Lolium rigidum Gaud. population referred as PP1. The same batch of seeds was used throughout the course of this research programme. G0 and PP1 are known to be sensitive to all herbicides registered for ryegrass control. The L. rigidum multiple-resistant population SLR31 was also obtained from Herbiseed. All other ryegrass populations either originated from the field where they were hand-collected by Syngenta technical staff during the cropping season or from seed production carried out at Jealott’s Hill under controlled environment or at Herbiseed (Twy- ford, UK) in field conditions. Despite numerous morphological and genetic analyses, the species classification within the genus Lolium is still under debate [reviewed in9, Chap. 1]. Therefore, no attempt was made to precisely determine from which species the collected seeds belonged. Based on known distributions and occurence, seeds from plants harvested in the UK were labelled as L. multiflorum and L. rigidum was used for seeds harvested in Australia. Unless otherwise stated, seeds were stored in cotton bags in a dark room maintained at 15◦C/15% RH. The winter wheat cultivar Here- ward (Triticum aestivum, cv. Hereward) was obtained from RAGT Seeds Ltd (Ickleton, UK) and the winter barley cultivar Suzuka (Hordeum vulgare, cv. Suzuka) from Syngenta Seeds Limited (Guildford, UK).

2.1.4 Plant growth stages

The growth stages identiﬁcation of the monocotyledonous plants used in this study, i.e. cereals and weeds follows the BBCH-scale [136] which is a revised version of the decimal code developed by Zadoks et al. [14] (Figures 2.1 and 2.2)

56 2.1. Herbicide whole plant bioassays

Figure 2.1: Early phenological growth stages and BBCH-identiﬁcation keys of grass weed species. BBCH00: dry seed; BBCH01: beginning of seed imbibition; BBCH05: radicle emerged from seed; BBCH07: coleoptile emerged from caryopsis; BBCH09: emergence, coleoptile breaks through the soil surface; BBCH10: ﬁrst true leaf emerged from coleoptile; BBCH12:two leaves unfolded and BBCH13: three leaves unfolded. Picture source: http://www.fsl.orst.edu/forages/projects/ regrowth/print-section.cfm?title=DevelopmentalPhases.

2.1.5 Operating procedures for pre-emergence application

Unless otherwise stated, a spoon measure of Lolium seeds (approx. 0.5 g) was sown in pots previously ﬁlled with appropriate compost in order to obtain a suﬃcient number of plants per control pot. This number was usually between 15 and 50 depending on seed availability and pot size. Pots were covered with compost and regularly hand-watered to ensure rapid and good seed imbibition. Pots were herbicide-treated at BBCH03, i.e. about 2 days after sowing on a moist but not wet soil surface. Pots were then hand-watered a minimum of 4 hours after application.

2.1.6 Seed germination on agarose

Ryegrass seeds were allowed to germinate in Nunc Bio-Assay dishes (243 x 243 x 18 mm; Fisher Scientiﬁc UK Ltd, Loughborough, UK) containing 1% w/v agarose (BPE1356-100, Fisher BioReagents, Loughborough, UK) dissolved in water ﬁltrated by reverse osmosis (RO water). Plates were incubated in a phytotron cabinet at a constant temperature of 22◦C

57 CHAPTER 2. General Materials and Methods

Figure 2.2: BBCH general scheme grass weed species. From [136]. with a photoperiod of 12 hours (300 µ mol.m−2.s−1 PPFD) at 60% RH. Seeds at BBCH05-07 growth stage were individually transplanted into pots with tweezers (Figure 2.3). Pots were ﬁlled with appropriate compost and watered before transplanting in order to ensure good surface moisture. Seeds were then covered with the same soil and watered. Herbicide application was performed two days after transplanting. None of the seedlings had emerged from the soil surface at the application time.

Figure 2.3: Example of ryegrass seeds at BBCH05-07 on agarose plates.

58 2.1. Herbicide whole plant bioassays

2.1.7 Herbicide application

Commercial formulations and herbicides under-development were suspended in RO water. Recommended adjuvants were added when required. Herbi- cides were applied in a spray cabinet at 20◦C mounted with a single mobile Teejet ﬂat fan nozzle (11002VS) calibrated to deliver 200 L.ha−1 at 200 kPa. Early-post (ePOST, usually BBCH 10) and post-emergence (POST, BBCH10-11) treatments were applied 30 cm above plant canopy while pre- emergence (PRE, BBCH03-07) treatments were sprayed 30 cm above soil level. Control plants/pots were not sprayed.

2.1.8 Herbicides and adjuvants list

The herbicides used in the whole plant greenhouse bioassays are detailed as follows: the active ingredient in bold font is followed by the chemical class, the HRAC group, the trade name and the type of formulation used, the supplier (in parenthesis), the recommended adjuvant in percentage of spray volume and the phytotoxicity proﬁles with respect to wheat and barley when they are known:

• prosulfocarb, thiocarbamate, HRAC goup N, applied as Defy 800 EC (Syngenta), safe to wheat and barley.

• clodinafop-propargyl later referred as clodinafop, aryloxyphenoxypropionate, HRAC group A, applied as Topik 100 EC (Syngenta) with 0.5% v/v Score, safe to wheat and barley.

• iodosulfuron-methyl-sodium later referred as iodosulfuron, sulfonylurea, HRAC group B, applied as Hussar 5 WG (Bayer CropScience) with 1%v/v Hasten, safe to wheat and barley.

• ‘Experimental Compound X’ from Syngenta, applied as 100 EC (formulation A17474A).

• pinoxaden, phenylpyrazoline, applied as Axial 100 EC (Syngenta) with 0.5% v/v Adigor, safe to wheat and barley.

• cycloxydim, cyclohexanedione, HRAC group A, applied as Laser 200 EC (BASF) with 0.5% v/v Actipron, unsafe to cereals.

59 CHAPTER 2. General Materials and Methods

• sethoxydim, cyclohexanedione, HRAC group A, applied as Poast 213 EC (BASF) with 0.5% v/v Actipron, unsafe to wheat and barley.

• haloxyfop-P-methyl later referred as haloxyfop, aryloxyphenoxypropionate, HRAC group A, applied as Gallant Super 108 EC (Dow AgroSciences) with 0.375% v/v Output, unsafe to wheat and barley.

• sulfometuron-methyl later referred as sulfometuron, sulfonylurea, HRAC group B, applied as Oust 75 WG (DuPont) with 0.25% v/v Agral, unsafe to wheat and barley.

• imazapyr, imidazolinone, HRAC group B, applied as Arsenal 240 SL (BASF), unsafe to wheat and barley.

• pyroxasulfone, pyrazole, HRAC group K3, applied as 050 EC (Syn- genta label EXC709), safe to wheat.

• diﬂufenican, carboxamide, HRAC group F1, applied as Brodal Op- tions 500 SC (Bayer CropScience), safe to wheat.

• metribuzin, triazinone, HRAC group C1, applied as Sencor 70 WG (Bayer CropScience).

• iodosulfuron+mesosulfuron-methyl, mixture of two sulfonylureas, HRAC group B, applied as Atlantis 3.6 WG (Bayer CropScience) with 0.5% v/v Biopower, safe to wheat, unsafe to barley.

• chlorotoluron, urea, HRAC group C2, applied as Dicuran 500 SC (Syngenta), safe to some wheat varieties.

• ﬂufenacet, oxyacetamide, HRAC group K3, applied as Tiara 60 WG (Bayer CropScience), safe to wheat and barley.

• triﬂuralin, dinitroaniline, HRAC group K1, applied as Treﬂan 480 EC (Dow AgroSciences), safe to wheat and barley

• EPTC, thiocarbamate, HRAC group N, applied as Eradicane 720 EC (Zeneca).

• napropamide, acetamide, HRAC group K3, applied as Devrinol FL 45 FL (United Phosphorous).

60 2.1. Herbicide whole plant bioassays

• S-metolachlor, chloroacetamide, HRAC group K3, applied as Dual Gold (Syngenta), safe to wheat.

2.1.9 Growth conditions

Unless otherwise stated, experiments were carried out in a greenhouse with a photoperiod of 14 hours at 20◦C/14◦C day/night (± seasonal variations) supplemented by 600W HPS lamps (Master GreenPower, Philips) that de- livered an average of 195 µ mol.m−2.s−1 PPFD at bench level. Relative humidity was maintained at about 65%. Plants were hand-watered and fertilised as needed.

2.1.10 Herbicide injury scoring

Symptomatology was visually recorded when the maximum level of control was achieved on the susceptible standard population, typically 21 days after application. Scoring depended on the type of herbicide applied, e.g. post- emergence vs. pre-emergence; bleacher vs. growth inhibitor. A 1-step scale from 0 to 100 was used with untreated pots as reference; 0 being for pots/individual plants showing no characteristic symptoms of herbicide damage and 100 for complete control, e.g. necrosis, bleaching, ﬁrst leaf failing to emerge.

2.1.11 Seed production

Jealott’s Hill seed production The L. multiﬂorum individuals selected for seed production were transplanted into 4” pots containing JIP compost. They were trimmed, tillered, re-potted and fertilised as required and grown to maturity. As soon as heading was observed (BBCH51), pots were either placed at one corner of a greenhouse bay or isolated in individual growth chambers. For the greenhouse production extreme care was taken to avoid cross-pollination with foreign pollen from other bays or from outside. How- ever, plants were not protected with a pollen-proof cloth as previous observations showed that it increased risk of mildew and aphid contamination and reduced further heading. Random mating was allowed in the greenhouse and the growth chambers. Fruit development was visually monitored. When ripening was at an advanced stage, i.e. BBCH85 (grain content soft but dry) the amount of water was reduced to one watering every other day.

61 CHAPTER 2. General Materials and Methods

When grains were fully ripe (Figure 2.4), plants were laid horizontally and allowed to dry for at least two weeks. Seeds were then hand-harvested and hand-cleaned using various sizes of screens to remove chaff and husks and finally winnowed to remove flower remains and any other impurities. Seeds were put in pierced plastic bags and placed in a drying room (18◦C, 15% RH) for two weeks. They were finally stored in cotton bags at 15◦C, 15% RH until further use.

Figure 2.4: Fully ripe ryegrass seeds. Picture: Sarah-Jane Hutchings, Syngenta, Jealott’s Hill.

Herbiseed seed production The L. multiflorum populations selected for seed production at Herbiseed (Twyford, UK) were grown under greenhouse conditions in 3” pots containing JIP compost; trimmed, tillered and fertilised as needed. As far as possible, 252 pots for each population were produced. They were given to Herbiseed staff in January-February 2009. Pots were then stored outside under an unheated polytunnel to ensure ac- climatization from controlled greenhouse temperature to natural external conditions. Plants were planted into the ground once the cumulative average temperature from January 1st had reached 200◦C. Watering, fertilisation and pest control was entirely managed by Herbiseed. Pollen contamination was prevented by the use of mesh and plastic sheets erected by Herbiseed staff. Seed harvest and cleaning was also entirely managed by Herbiseed. After collection of the so-produced seeds, the purity of the batches for the trait of interest was investigated at the whole plant level with a greenhouse herbicide experiment and at the molecular level with dCAPS assays for specific mutations detection.

62 2.1. Herbicide whole plant bioassays

2.1.12 Dose-response analysis

The datasets from the dose-response experiments were ﬁtted to a non-linear log-logistic regression model as described in Equation 2.1

di − ci f(x) = ci + (2.1) 1 + expbi(log(x)−Li) where f(x) is the response variable, e.g. visual biomass reduction or plant survival, ci and di the lower and upper asymptotic limits of f(x) for ryegrass population i, x the herbicide rate in gai/ha, bi the slope at the inﬂexion point halfway between ci and di for population i in other terms at the ED50 value (the herbicide dose resulting in 50% of the eﬀect) and

Li = log(ED50) for population i. Model reduction was evaluated with analysis of variance (α=0.05) in order to choose the simplest model that best described the dataset. The signiﬁcance test was ruled out if and only if the best model did not make biological sense, e.g. estimating negative asymptotic lower limits. Analyses were performed using the open-source software R [137] supplemented with the drc package [138].

2.1.13 Parameter interpretation - ED50, resistance factor (RF) and relative potency (RP)

ED50 values and resistance factors help to evaluate the magnitude of the shift towards resistance/sensitivity when comparing two weed populations. ED50 were estimated from the best model fit with their corresponding confidence intervals at 95%. As shown in Figure 2.5(a), they may be estimated at different absolute f(x) values as they depend on the asymptotic limits. A resistance factor (RF value) is the ratio of ED values estimated at a given level of control, e.g. at 50%. For non-parallel curves (different b values) the RF was estimated at 50% level of control. It has to be noted that the magnitude of the shift may greatly differ depending on the en- dpoint (Figure 2.5(b)). RF is independent from the level of control for parallel fitted curves (Figure 2.5(c)). When comparing a putative resistant weed population to the susceptible population of reference, the RF value can either be (i) greater than one suggesting a shift towards resistance or (ii) less than one, suggesting that the test population was better controlled than the susceptible population, indicating possible effects of negative-cross

63 CHAPTER 2. General Materials and Methods resistance. The statistical significance of the computed RF was evaluated by reporting the confidence intervals at 95%. Estimated RF values have to be interpreted with care regardless of statistical significance. Small values, e.g. 0.5-2 can occur between known susceptible populations of a given weed species due to natural genetic variability. In that case, weed control at a discriminating rate, such as herbicide field rate, should be preferred for assessing resistance magnitude and or significance (Figure 2.5(c)). Relative potencies (RP) are used when comparing (i) two compounds applied against a given weed population or (ii) the same compound applied under different conditions. In essence, relative potencies are similar to resistance factors.

2.2 Molecular analysis

2.2.1 DNA extraction

DNA analyses were conducted on leaf fragments that were sampled either prior to herbicide application or after assessment. Leaf pieces were put into Costar 96-Well assay blocks (1 mL round bottom, from Fisher Scientiﬁc) containing one stainless steel grinding ball (5/32 inch ≈ 3.9 mm) per well. Blocks were stored at -80◦C for a minimum of 2 hours before use. Plant samples were ground to a dry powder using a ball-mill tissue grinder (Gen- ogrinder 2000, SPEX CertiPrep, USA) for 30 seconds at 1,184 strokes/min (one stroke = one complete up and down movement), then centrifuged at 4,800g for 5 minutes. Total genomic DNA was extracted using the Wiz- ard Magnetic 96 DNA Plant System from Promega (Southampton, UK). Extraction was either carried out manually or with the automatic platform Biomek R FX Workstation (Beckman Coulter, High Wycombe, UK). In both cases, the protocol was as follows:

• Cell lysis: 300 µL of plant lysis buﬀer A was added to the ground tissues; the reaction mix was homogenized for 30 seconds at 1,184 stokes/min, and ﬁnally centrifuged for 15 min at 4,800g.

• DNA binding: 125 µL of the supernatant was transferred into a U-bottom 96-well plate containing 50 µL of plant lysis buﬀer plus 10 µL of MagneSil R paramagnetic particles per well. The solution was

64 2.2. Molecular analysis (c) (b) (a) Parameters interpretation: ED50, resistance factor (RF) and relative potency (RP). These figures aim to clarify the Figure 2.5: importance of the ‘horizontal’given assessment, dose. i.e. ∆d ED50details refers and can to RF50 be difference determination found between and in two ‘vertical’ section herbicide assessment,2.1.13 . doses. i.e. percentage ∆wc of refers control to at the a difference between two weed control values. More

65 CHAPTER 2. General Materials and Methods

mixed by repeated pipetting and incubated for 5 minutes at room temperature (RT). The U-plate was then transferred onto the MagnaBot R separation device and the liquid was discarded.

• DNA purification: the U-plate was removed from the magnetic pod, 150 µL of wash buffer was then added and mixed to the paramagnetic particles. The U-plate was then transferred onto the magnetic pod and the liquid discarded. The wash step was repeated one more time with 100 µL of wash buffer.

• DNA elution: the U-plate was left on the MagnaBot R pod for 10 minutes to allow the paramagnetic beads to dry. The plate was then removed from the pod, 100 µL of elution buffer (1X TE + BSA at 10 mg/L - New England BioLabs, Hichin, UK) was added per well, thoroughly mixed and incubated for 5 minutes at RT. The U-plate was finally put back onto the magnetic pod, and the purified DNA was transferred into a fresh plate. Only 80 µL was transferred when the manual extraction was performed. Plates were stored at -20◦C until use.

2.2.2 Polymerase chain reactions (PCR)

All PCR reactions were performed in a thermal cycler Mastercycler gradient (Eppendorf, UK). PCR cycling parameters of the diﬀerent programs used are described in the respective sections.

2.2.3 Primers and Sequencing

All primers were synthesised by Euroﬁns MWG Operon (Ebersberg, Ger- many). Sequencing was performed by Beckman Coulter Genomics (Takeley, UK).

2.2.4 Electrophoresis

PCR and PCR-RFLP products were run on TBE-agarose gels containing 75 nM of ethidium bromide with 1X TBE as running buﬀer and visualized with a GeneSnap-GeneGenius system (version 4.01.00, Syngene, Cambridge, UK).

66 2.3. Enzymatic studies

2.2.5 dCAPS assays

Several dCAPS (derived Cleaved Amplified Polymorphic Sequence) assays are available to detect polymorphisms in the chloroplastic ACCase gene at positions known to confer resistance to ACCase inhibitors. The dCAPS assay is a modification of the PCR-RFLP technique (PCR-Restriction Frag- ment Length Polymorphism) for the detection of single nucleotide polymorphisms (SNP). One or more bases in either the forward or the reverse primer are deliberately modified in order to create a restriction site for either the wild type or mutant DNA sequences. Suitable dCAPS primers were identified using the dCAPS Finder software developed by Neff et al. [139]. The primer pairs and companion restriction endonucleases used were as described in Table 2.1. PCRs were carried out using puReTaq Ready- To-Go R PCR beads (GE healthcare, Little Chalfont, UK) in a final volume of 25 µL consisting of 0.3 µM of each primer, 5 µL of purified DNA (see section 2.2.1) and sterile water. The thermocycler was programmed with an initial denaturation step at 94◦C for 2 minutes followed by 40 cycles of 10 s at 94◦C, 30 s at 60◦C and 1 min at 72◦C. A final extension step of 10 min at 72◦C was added and the PCR products were kept at 4◦C until use. The PCR products were then restricted at 37◦C for 2 hours in a final volume of 40 µL consisting of 1X enzyme buffer, 5 U of enzyme for the 1781 and 2078 assays and 2.5 U of enzyme for the 1999 assay, 5 µL of PCR product and sterile water. The dCAPS patterns were visualized in 2% agarose/1X TBE gels. For each dCAPS experiment, controls were added to detect any unreliable digestion from the restriction enzyme, i.e. (i) known wild-type individual for 1781 assay and (ii) known mutant based on sequencing analyses for the 1999 and 2078 assays.

2.3 Enzymatic studies

2.3.1 ACCase extraction and puriﬁcation

All buffers were kept at 4◦C. Fresh leaf materials were sequentially ground in liquid nitrogen with a mortar and pestle, homogenised in buffer A in a 1:3 ratio weight:volume (buffer A: 50 mM Tris-HCl, pH 8, 1 mM EDTA, 0.5% v/v Triton X-100, 20% v/v glycerol, 1 mM benzamidine-hexahydrate, 10 mM MgCl2, 20 mM β-mercaptoethanol) and kept on ice until use. The ho-

67 CHAPTER 2. General Materials and Methods mogenate was filtered through two layers of cheesecloth. The crude extract was centrifuged at 34,000g at 4◦C for 30 minutes. The supernatant was then applied to a HiTrap Q FF 5mL ion-exchange column (GE healthcare, Little Chalfont, UK) that had been equilibrated with 10 column volumes (CV) of buffer A. Unbound sample was washed with 5 CV of buffer A. ACCase was eluted with a linear gradient of buffer B (0%-100%; buffer B is buffer A supplemented with 1M NaCl; gradient over 45 CV) and 2 mL fractions were collected in a 96-well plate. Fractions were subsequently tested for ACCase activity using the radiolabelled assay described below. ACCase fractions having not less than 70% of the highest activity were pooled together, beaded in liquid nitrogen and stored at -80◦C until use.

2.3.2 ACCase activity assays

Radiolabelled substrate assay ACCase activity was assayed by the 14 ATP-dependent incorporation of H CO3 (bicarbonate) into the heat-stable product [14C]malonyl-CoA using a methodology derived from Sasaki et al. [140]. Assay components were prepared in buﬀer C (100 mM Tris-HCl, pH

8.4, 15 mM KCl, 3 mM MgCl2, 1 mM DTT, 0.01% w/v BSA). The radiola- 14 belled solution contained 40mM NaHCO3, 4 mM ATP, 40 µM NaH CO3 (Moravec Biochemicals, Inc., Brea, CA, USA, stock at 20 MBq/mmol). Re- agent AC contained 6.51 mM of acetyl-CoA (sodium salt, Sigma Aldrich, Gillingham, UK). An aliquot of 50 µL of each fraction was transferred into 7 mL glass scintillation vials. Then, 50 µL of buﬀer A was sampled as negative control and 50 µL of a known in-house active ACCase extract from maize1 was added as a positive control. The reaction was started by adding 25 µL of the radiolabelled solution followed by 25 µL of reagent AC. The reactions were incubated at 30◦C for 20 minutes in a dry block heating system and terminated by the addition of 25 µL of 6 M HCl. The acid reacts with any remaining cold and radiolabelled bicarbonate depriving the system of its ◦ substrate and releasing CO2. The so-acidiﬁed solution was dried at 90 C for at least 1 hour to accelerate the evaporation of CO2. A schematic view of the overall reaction is presented in Figure 2.6. The dried samples were then dissolved in 150 µL of 50% v/v EtOH and 3 mL of liquid scintillation cock- tail was added (Optiphase HiSafe 3 from Perkin Elmer, or Scintisafe from

1The maize ACCase enzyme was extracted by Steve Elvidge, Syngenta, Jealott’s Hill.

68 2.3. Enzymatic studies

Fisher Scientiﬁc depending on availability). Radioactivity was quantiﬁed in a Perkin Elmer liquid scintillation analyzer Tri-Carb 2900TR (PerkinElmer, Waltham, MA, USA).

Figure 2.6: Biotin (in yellow) covalently binds to the biotin-carboxyl carrier protein (structural domain in blue) thanks to an amide linkage at the amino acid lysine. This ﬂexible arm allows the biotin to move between the two catalytic centres, i.e. the biotin carboxylase subunit (BC domain, on the left) and the carboxyltransferase domain (CT domain, on the right). The BC domain catalyses the ATP-dependent − carboxylation of biotin with CO2 provided by the bicarbonate molecule (HCO3 ). The CT domain transfers the activated CO2 molecule from biotin to acetyl-CoA resulting in the formation of malonyl-CoA (scheme on the right). ACCase inhibitors bind in the CT domain inducing conformational changes that reduce the produc- − tion of malonyl-CoA. Overall reaction: step 1: HCO3 + ATP biotin biotin-CO2 + ADP + Pi; step 2: biotin-CO2 + acetyl-CoA malonyl-CoA + biotin. Picture from http://web.virginia.edu/Heidi/chapter25/chp25frameset.htm.

Spectrophotometric assay2 The inhibition of L. multiﬂorum ACCase activity by FOP, DIM and DEN molecules was assayed using a malachite green assay [141, 142]. Malachite green is an organic compound (Figure 2.7) that is traditionally used as a dye. The ﬁrst pKa of malachite green is about 1.2 and the second about 12. A solution of the dye is blue-green for pH between 2 and 13 and yellow below 0.5. The reaction catalyzed by ACCase results in the formation of an inorganic phosphate (Pi) molecule from ATP. Under acidic conditions (pH < 0.5, yellow), the simultaneous presence of Pi and molybdate in the solution results in the formation of a phosphomolybdate complex and the solution turns blue-green. This colour change is due to the electrostatic binding of the blue-green form of the malachite green to the anionic phosphomolybdate complex. Therefore, in

2The experimental work was carried out by Rebecca Stevens, Syngenta, Jealott’s Hill.

69 CHAPTER 2. General Materials and Methods the presence of a sensitive and active ACCase isoform, the colour becomes blue-green (production of Pi). If an ACCase inhibitor is added to a concentration high enough to result in complete inhibition, the solution remains yellow as no Pi is produced. Solutions will stay blue-green in presence of an ACCase isoform carrying mutation(s) that confer resistance to ACCase inhibitors. The colour intensity is proportional to the amount of Pi generated by the catalytic reaction and, therefore, to the amount of ACCase inhibitor present in the solution. An example of a test plate is presented in Figure 2.8. Colour change was detected at 630 nm with an Infinite M200 PRO plate reader (Tecan UK Ltd, Reading, UK). The enzyme activity (inhibition) was expressed as a percentage of untreated control (DMSO). IC50 values were estimated by fitting the percentage of inhibition to a log-logistic model using software developed at Syngenta. Clodinafop-propargyl, pinoxaden acid and tralkoxydim were tested for their ACCase inhibitory effect. Assays were carried out in V-bottom microtitre plates. Herbicides (analytical grade, synthesised at Syngenta) were dissolved in DMSO. Serial dilution (dilution factor 4) was performed in order to obtain 8 rates for each herbicide tested. Each rate was duplicated and the whole experiment was repeated twice in time. Top rate for clodinafop-propargyl was 128 µM, 142 µM for pinoxaden acid and 136 µM for tralkoxydim. Lowest rate for each compound was ap- proximately 8 nM. Blank consisted of DMSO only at a final concentration of 0.9% v/v (0% enzyme inhibition, 4 wells). Complete enzyme inhibition was ensured by pinoxaden acid at 285 mM on the maize ACCase enzyme (4 wells). 70 µL of enzyme extracts were added to each test well and the plate was incubated for 20 minutes at 30◦C. This allowed the herbicide to bind to its target. Subsequently, 20 µL of a solution of 2.195 mM ATP plus

130.5 mM NaHCO3 in Buﬀer C (see above) were added. The plate was incubated at RT for 2 minutes. Finally, 20 µL of acetyl-CoA (1.62 mM in buﬀer C) were added and the plate was incubated at 30◦C for 12 minutes (production of Pi). The reaction was then quenched by the addition of 25 µL 5.5 M HCl; 200 µL of the dye solution was added (6.74 mM ammonium molybdate tetrahydrate, 0.45 mM malachite green oxalate salt, 5.5M HCl). The absorbance was measured at 630 nm after 5 min.

70 2.3. Enzymatic studies Kaundun and Windass [ 83 ] Kaundun et al. under preparation Kaundun [ 91 ] fragment size aftergestion (in di- bp) Wild type Mutant Reference TTG) 178 147 9 (CCAN (GTAC) 181 147 (ATGCAT) 130 165 (5’-3’ site) NsiI RsaI XcmI Huds. (EMBL accession AJ310767). Nucleotides in bold are modiﬁed in G GGC CA C . myosuroides A A TA C C G AGA GAC CTTGG TTT GAA GAT CTG GATTG TTA TCT TAT GGC CG AAT AGC AGCATG ACT TCC TTC CTC GT AAT AGC AGCATG ACT TCC AAG TC forward CTG TCT GAA GAA GAC reverse AGA ATA CGC ACT GGC forward CCC ATG AGC GGT CTG reverse AGA ATA CGC ACT GGC forward TTC TCT GGT GGG CAA reverse CAT AGC ACT CAA TGC List of primers and restriction endonucleases used in the dCAPS experiments. Amino acid positions are derived from the 2078 Polymorphism Primer Sequence 5’-3’1781 Restriction enzyme 1999 Table 2.1: full length chloroplastic ACCase gene from A order to create aOnly the recognition longest site fragment for is the reported appropriate for the restriction digested enzyme. products. Nucleotides in italics belong to the enzyme restriction site.

71 CHAPTER 2. General Materials and Methods

Figure 2.7: Structure of the malachite green dye.

Figure 2.8: Example of a malachite green assay plate. Picture: Karine Lecoq, Syngenta, Jealott’s Hill.

72 3 Insights into prosulfocarb behaviour under greenhouse conditions

3.1 Introduction

Prosulfocarb was introduced as ‘a new selective herbicide for use in winter cereals’ in 1987 [143]. It is a broad-spectrum compound that controls major grass and broad-leaved weeds. Prosulfocarb is a neutral molecule with a thiocarbamate functional group (Figure 3.1) and belongs to the group N of the HRAC herbicide mode of action classification [20]. Prosulfocarb symptoms include stunting, shortened and thickened leaves, coleoptile swelling, failure of leaves to correctly unfurl, leaf darkening and root damage (Fig- ures 3.3 and 1.5). The exact biological target of prosulfocarb is yet to be elucidated. Prosulfocarb is thought to inhibit the large family of elongases that are located in the endoplasmic reticulum and synthesise the very long chain fatty acids (reviewed in Chapter1). Thus, to some extent, prosulfocarb can be considered as a ‘multi-site’ herbicide. In Europe, field applications of prosulfocarb are pre or early-post weed emergence between 2,000 and 4,000 gai/ha. These are very high rates compared to the newer residual compounds such as flufenacet that is effective at 240 gai/ha in the United Kingdom. In Australia, prosulfocarb is soil incorporated by sowing, which requires less neat compound than a traditional soil application. To date, resistance to prosulfocarb has not been documented in ryegrass [54].

Over 20 years after its introduction and despite the ever stricter environmental regulations, prosulfocarb is still registered for use in Europe (annex I inclusion until 2018). In the UK, under optimal ﬁeld conditions, it does not always provide 100% weed control on susceptible ryegrass populations even

73 CHAPTER 3. Prosulfocarb behaviour under greenhouse conditions at the highest recommended pre-emergence rate of 4,000 gai/ha. Therefore, particular importance was attached to the factors that may affect prosulfocarb efficacy under a greenhouse environment. In this respect, a prosulfocarb dose-response bioassay was firstly carried out to determine whether 4,000 gai/ha was appropriate for use under a greenhouse environment maintained at 20◦C/14◦C day/night (± seasonal variations). Then, the distribution of prosulfocarb efficacies at 4,000 gai/ha to control the susceptible standard L. multiflorum population G0 was investigated over time. As the efficacy of soil applied herbicides is dependent on the soil characteristics, the performance of prosulfocarb on three different soil types was compared.

Prosulfocarb is regarded as a key compound for delaying or overcoming herbicide resistance in ryegrass species. The Lolium rigidum Gaud. population SLR31 has been extensively studied over the past 20 years and has naturally evolved resistance to several modes of action including ACCase, ALS, and microtubule assembly inhibitors [70–73]. The suitability of prosulfocarb as a tool to control herbicide-resistant ryegrass populations was then tested against SLR31.

Figure 3.1: Prosulfocarb structure.

3.2 Pre-emergence prosulfocarb rates for ryegrass control under greenhouse environment

3.2.1 Materials and Methods

Seeds of the Lolium multiﬂorum Lam. populations 2005 UK 238 and 2005 UK 203 were harvested in 2005 from ﬁelds respectively located in Bedford- shire and in Kent (United Kingdom). Preliminary herbicide testing showed

74 3.2. Pre-emergence prosulfocarb rates that these two populations were sensitive to the main ACCase and ALS inhibitors used for grass control in cereal crops (Jason Tatnell, data not shown). G0 is the susceptible standard L. multiﬂorum population used throughout this research programme and is commercially available from the company Herbiseed (Twyford, UK). A spoon of G0, 2005 UK 238 and 2005 UK 203 seeds was sown in troughs containing TMA soil. Growth conditions were as detailed in section 2.1.9. Three replicate trough units were produced and sprayed at BBCH03 with 500; 1,431; 2,048; 2,930; 4,193 and 8,000 g prosulfocarb/ha. Control troughs were left untreated. Herbicide injury was visually recorded 14 days after application. Dose-response curves were analysed with a log-logistic model as described in section 2.1.12.

3.2.2 Results and Discussion

Parallel curves were fitted with common upper and lower asymptotic limits fixed at 100 and 0 respectively. Figure 3.2 shows that there was no difference between the three susceptible populations tested, suggesting minimal natural variability between these populations. Weed control at 4,000 gai/ha was estimated between 93% and 99% for the three samples. The ED90 values fell between 2,162 and 3,526 gai/ha. This suggested that the outdoor rate of 4,000 gai/ha was also a good discriminative rate for the control of susceptible ryegrass under glass and in the TMA soil system. This may also allow direct comparison between field and greenhouse experiments. It contrasts with some of the more recent foliar compounds such as ACCase and ALS inhibitors for which rates as little as one-twentieth of the field rate can be used under greenhouse conditions to provide full control of susceptible grass weed populations (personal observation).

75 CHAPTER 3. Prosulfocarb behaviour under greenhouse conditions

100 ● ● ●

80 ●

● 60

20 ● G0 weed control (visual percentage) weed 2005 UK 238 0 ● 2005 UK 203 0 1000 10000 prosulfocarb rate in gai/ha

Figure 3.2: Dose-response curves for three herbicide-sensitive populations tested against a range of prosulfocarb rates.

76 3.3. Prosulfocarb performance over time

3.3 Prosulfocarb performance over time

3.3.1 Materials and Methods

Data from a total of 11 diﬀerent experiments carried out between May 2008 and March 2011 have been amalgamated in this section. In each experiment, a spoon measure of G0 seeds was sown in pots or troughs previously ﬁlled with TMA soil in order to get about 30 emerging seedlings per untreated pot (Table 3.1). The units were sprayed at BBCH03 with 4,000 g prosulfocarb/ha. Herbicide injury was visually recorded 21 days after application.

Table 3.1: List of the 11 diﬀerent experiments carried out between May 2008 and March 2011 with prosulfocarb applied at 4,000 gai/ha on BBCH03-05 seeds of the susceptible standard L. multiﬂorum G0 population. Experiment No. Month Year Pot format Nb. replicate 01 May 2008 Trough 12 02 May 2008 Trough 5 03 June 2008 Trough 10 04 November 2009 Trough 6 05 November 2009 Trough 3 06 September 2009 4” 2 07 August 2009 4” 2 08 January 2010 Trough 2 09 February 2011 4” 3 10 February 2011 4” 3 11 March 2011 4” 3

3.3.2 Results and Discussion

Figure 3.3 shows an example of three diﬀerent levels of weed control achieved on G0 with prosulfocarb applied pre-emergence (PRE) at 4,000 gai/ha. Figure 3.4 presents the results obtained over the 11 experiments. Variations within and between experiments are obvious, highlighting some diﬃculties in working with prosulfocarb under greenhouse conditions. Overall, the mean weed control was 83% and the median 85%. Over the years, it seems that experiments carried out during summer periods tended to provide less and more variable control than experiments carried out in winter months

77 CHAPTER 3. Prosulfocarb behaviour under greenhouse conditions

(average 75% in summer months vs. 92% in winter months, Figure 3.4). Volatilisation of soil-adsorbed herbicide is a multi-factorial problem that mainly depends on (i) the compound’s physical properties, e.g. vapour pressure, solubility, adsorption coefficient, reactivity; (ii) the soil properties, e.g. moisture, organic matter and clay content, temperature, pH and (iii) the application/growth conditions, e.g. air temperature and humidity, solar ra- diations. To volatilise, a chemical must first desorb from the soil and move to the interstitial soil water from which it may exchange to the stagnant layer of air above the soil. Studies have shown that, in general, volatilisation is correlated with vapour pressure [144]. Moreover, the vapour pressure of a liquid increases as temperature increases (Clausius-Clapeyron’s law). The greenhouse complex tended to be warmer during summer time due to the absence of air-conditioning system. Therefore, other factors being constant, differences in efficacy between summer and winter may be explained by a higher volatilisation rate of prosulfocarb due to higher temperatures. Pre-emergence experiments with outdoors containers better mimic field conditions and allow more precise herbicide efficacy comparisons [145]. How- ever, this is only valid for experiments carried out during the autumn/spring periods, but it (i) dramatically increases the time allocated for a single experiment (often greater than two months compared to less than one under greenhouse conditions), (ii) suffers from the same drawbacks regarding the summertime conditions and (iii) does not allow full year-to-year comparisons between tests. The last important point raised by these data is the fact that prosulfocarb very rarely provided full control (100% weed control) of the susceptible G0 population. This feature may lead or contribute to the development of prosulfocarb-resistance and is therefore investigated in a subsequent chapter (Chapter4).

78 3.3. Prosulfocarb performance over time

Figure 3.3: Example of typical injury and visual weed control values allocated 21 days after application of prosulfocarb at 4,000 gai/ha on G0 seeds at BBCH03.

100

80 n=2 n=3 n=3 n=3

60 n=10 n=6 n=3 n=2 n=2

n=12 n=5 20 weed control (visual percentage) weed

0 exp.01 exp.02 exp.03 exp.04 exp.05 exp.06 exp.07 exp.08 exp.09 exp.10 exp.11

Figure 3.4: Weed control distribution for prosulfocarb applied at 4,000 gai/ha on G0 seeds at BBCH03 over 11 distinct experiments carried out from May 2008 to March 2011. The median is represented with a solid line, outliers are represented with a cross, whiskers extend to the minimum and maximum values in the absence of outliers.

79 CHAPTER 3. Prosulfocarb behaviour under greenhouse conditions

3.4 Prosulfocarb eﬃcacy as a complex function of soil characteristics

3.4.1 Materials and Methods

Three soils were evaluated in this study, i.e. TMA soil, sand and a sand:TMA mixture at 1:1 v/v (hereto referred as 50:50). One sheet of grade 1 filter paper was put inside each 4” pots to avoid sand leakage. Seeds of the susceptible standard L. multiflorum population G0 were sown onto moist soil. Pots were covered with the appropriate soil and directly watered. Three replicate pot units were produced per treatment including the untreated control. Different dose-ranges were applied at BBCH03 according to the soil composition (Table 3.2). Herbicide efficacies were visually recorded 21 DAA.

3.4.2 Results and Discussion

Non-parallel curves were fitted with common upper and lower asymptotic limits respectively fixed at 100 and 0. Figure 3.5 clearly shows that prosulfocarb was more potent on sand than on TMA soil. The efficacy of prosulfocarb on the 50:50 mixture was halfway between the sand and the TMA soil at 50% level of control (Table 3.3). Relative potency at 90% for the TMA/sand pair was estimated at 25 (95% CI = 10-39). Therefore weed control achieved with 4,000 g prosulfocarb/ha in TMA soil would be obtained with only 160 gai/ha on sand. This experiment highlighted the differences in prosulfocarb bioavailability between the three soil systems.

Gennari et al. [146] demonstrated that microbial activity is essential for prosulfocarb dissipation in treated soils. Indeed, less than 5% of prosulfocarb was abiotically degraded in an autoclaved loamy soil incubated at 25◦C in the dark during 38 days. About 50% of the applied prosulfocarb was degraded by the indigenous microﬂora present in the same but unsterilized soil under the same experimental conditions. This ability of microorganisms is exploitable for the bioremediation of herbicide contaminated soils, e.g. atrazine metabolism by an Agrobacterium radiobacter strain [147] and for herbicide biosafening, e.g. the breakdown of EPTC by a Rhodococcus sp. strain [51]. Unlike the sand used in this study, the TMA soil was not

80 3.4. Prosulfocarb efficacy as a complex function of soil characteristics sterilised and probably contained indigenous microorganisms that could use prosulfocarb as their carbon source resulting in its biodegradation and so in a loss of herbicide available for weed control. The microflora composition in the TMA soil was not determined and so its influence on prosulfocarb degradation was not further investigated.

Another important factor influencing weed bioavailability is the proportion of soil-adsorbed prosulfocarb. As sand is chemically inert, prosulfocarb adsorption is virtually non-existent which maximises its bioavailability and the resulting weed control. This is also seen in the field, especially under sandy soil situations as in Saudi Arabia where prosulfocarb gives extremely reliable ryegrass control of over 95% (Shiv Shankhar Kaundun, personal communication). Nègreet al. [148] showed that prosulfocarb was adsorbed at 95% by humic acid, which is an important constituent of organic matter. A strong positive correlation was also observed between organic carbon content in soils and prosulfocarb adsorption. The potential of clay mineral adsorption was then demonstrated with montmorillonite, a phyllosilicate of high cation exchange capacity. Prosulfocarb adsorption was negatively correlated to pH and around 35% were adsorbed by the montmorillonite at neutral pH. Finally, a hydroponic bioassay suggested that efficient ryegrass control would be achieved with rates as low as 30 gai/ha [148].

To conclude, prosulfocarb eﬃcacy in soil is likely to depend on (i) the presence of soil microorganisms, (ii) the organic matter content and (iii) the clay content.

81 CHAPTER 3. Prosulfocarb behaviour under greenhouse conditions h ucpil standard susceptible the 3.2: Table obntoso oltp n rsloabdssue ntesi oprsnasy rsloabwsapido ed of seeds on applied was Prosulfocarb assay. comparison soil the in used doses prosulfocarb and type soil of Combinations TMA 50:50 Sand 53 69 6 0 8 2 ,5 ,1 ,1 ,8 ,8 8,000 4,782 2,780 1,811 1,410 1,052 721 486 300 165 93 56 30 15 X X X X X X X X .multiﬂorum L. X X X X X X X X 0pplto tBBCH03-05. at population G0 X X X X X X X X rsloabrt ngai/ha in rate prosulfocarb

82 3.4. Prosulfocarb efficacy as a complex function of soil characteristics population G0. ED50, ED70, ED90 refer to estimated doses that result of 50%, 70% and L. multiflorum (slope) ED50 ED70 ED90 RP50 RP90 b Parameters and estimated values for the prosulfocarb dose-response experiments carried out on three different types of soils Sand -3.04 45 (40-51) 60 (51-69) 93 (68-118) 50:50 -3.83 120 (108-133) 150 (129-171) 213 (158-269) TMA -1.14 337 (239-434) 707 (553-862) 2,307 (1,116-3,499) 50:50/sand 2.65 (2.23- 3.08) 2.28 (1.43-3.14) TMA/sand 7.43 (5.11- 0.76) 25 (10-39) TMA/50:50 2.79 (1.93- 3.65) 11 (4.56-17) Table 3.3: with the susceptible standard 90% of visual biomass reduction. RP50, RP90 are relative potencies at 50% and 90% levels of control.

83 CHAPTER 3. Prosulfocarb behaviour under greenhouse conditions

100 ● ● ● ● ● 80

● 60 ● ●

20 ● TMA weed control (visual percentage) weed 50:50 sand 0 10 100 1000 10000 prosulfocarb rate in gai/ha

Figure 3.5: Dose-response curves for the susceptible standard population G0 following application of prosulfocarb on three diﬀerent soil types, i.e. TMA soil, sand and a 1:1 v/v mixture of TMA:sand.

84 3.5. Prosulfocarb controls SLR31

3.5 Prosulfocarb controls SLR31, a multiple-herbicide resistant L. rigidum population

3.5.1 Materials and Methods

Seeds of the susceptible standard L. rigidum population PP1 and the multiple- herbicide resistant population SLR31 were obtained from Herbiseed (Twy- ford, UK). Seeds were sown in 4” pots containing TMA soil. Three replicate pot units were produced per treatment including untreated. The experiment was conducted a total of three times. Prosulfocarb was applied at BBCH03 at 250; 500; 1,000; 2,000; 4,000 and 8,000 gai/ha. Dose-response curves were ﬁtted to a log-logistic model as described in section 2.1.12. Data sets from three experiments were pooled.

3.5.2 Results and Discussion

Parallel curves were ﬁtted with common upper and lower asymptotic limits respectively ﬁxed at 100 and 0. Figure 3.6 shows that there was no shift towards resistance in SLR31. This was corroborated with the estimated RF50 value of 1.03 (CI 95% = 0.71-1.36). Estimated ED50 values were respectively 802 (CI 95% = 687-917) and 831 (CI 95% = 669-994) for PP1 and SLR31. At the labelled rate of 4,000 gai/ha the percentage of visual weed control was estimated at 96% (CI 95% = 93%-99%) for both PP1 and SLR31 populations. SLR31 was therefore as well controlled as the standard susceptible population despite the reports of triallate resistance in this population. [50, 72, 73, 76].

As mentioned in the General Introduction (Chapter1), chloroacetamide and thiocarbamate herbicides share the same mode of action. Based on LD50 values a resistance factor of 5.4 was estimated between SLR31 and a susceptible population of reference treated with the chloroacetamide metolachlor applied pre-emergence [73]. The authors concluded that metolachlor resistance occurred in SLR31 and predicted its possible rapid spread should the herbicide be used repeatedly. Metolachlor is still registered in several Australian states for L. rigidum control. Between 542 and 720 gai/ha are allowed in barley and oats while 2,160-2,880 gai/ha can be applied on cab-

85 CHAPTER 3. Prosulfocarb behaviour under greenhouse conditions bages. More than 50% survivors were observed for SLR31 at 600 gai/ha while the susceptible population was fully controlled, confirming that chloroacetamide resistance in ryegrass may be an issue in cereal crops [73]. On the contrary, less than 10% of SLR31 survivors were observed at 1,200 g metolachlor/ha, suggesting that resistance may not be significant in cabbages. Metolachlor is a racemic mixture of the active enantiomer S-metolachlor and the inactive R-metolachlor [149]. S-metolachlor is also registered in Australia for the same usage as metolachlor with rates between 360 and 480 gai/ha for barley and oats, and 1,440 to 1,920 gai/ha for cabbages. S-metolachlor at 480 gai/ha equates to 960 gai/ha of the racemic mixture. From Burnet et al. [73] data, about 25% of SLR31 seedlings would have withstood that rate, suggesting a smaller magnitude of resistance. Alto- gether, this clearly demonstrates that the evaluation of herbicide resistance should not only be based on the estimation of RF values. The same observation was drawn for putative triallate resistance in SLR31. Tardif and Powles [50] claimed a 2.4-fold shift towards resistance between the susceptible population VLR1 and SLR31. The Australian field rate of triallate is 1,500 gai/ha and SLR31 was fully controlled at rates above 1,000 gai/ha [74]. This may suggest that only minor mechanisms, including natural population variability, may account for the sensitivity shift observed. With the exception of SLR31, no other case of putative resistance to chloroacetamide or thiocarbamate herbicides has been reported in Australia confirming the value of prosulfocarb for the control of resistant ryegrass populations [54].

86 3.5. Prosulfocarb controls SLR31

100 ● ● ●

● 80 ●

● 60 ●

● 20

weed control (visual percentage) weed ● ● PP1 ● ● 0 SLR31 20 100 1000 10000 prosulfocarb rate in gai/ha

Figure 3.6: Dose-response curves for the susceptible standard L. rigidum population PP1 and the multiple-resistant population SLR31 following application of prosulfocarb.

87 CHAPTER 3. Prosulfocarb behaviour under greenhouse conditions

3.6 Conclusions and Perspectives

This introductory chapter raised several important points and provides a background understanding for the use of prosulfocarb as a tool for the control of sensitive and herbicide-resistant ryegrass populations:

• Prosulfocarb applied at 4,000 gai/ha at BBCH03 on TMA soil and under a greenhouse environment is a good rate for the control of susceptible populations.

• However, this rate does not always provide full control; typical visually estimated biomass reduction is just above 80%. This may lead to the development of prosulfocarb resistance over time if the survivors genuinely present genetic resistant traits compared to the dead plants.

• Prosulfocarb eﬃcacy is likely to dependent on environmental factors that increase its volatility.

• Prosulfocarb bioavailability for weed control is mainly dependent on (i) the activity of soil microorganisms, (ii) the organic matter content and (iii) the clay content.

• The sandier the soil, the better the performance of prosulfocarb. A sand system should be preferred for the precise detection of sensitivity- shifts.

• The lack of resistance to prosulfocarb in the multiple-resistant SLR31 population indicates that this herbicide has considerable potential for control of resistant L. rigidum population and, probably, to a greater extend, to L. multiﬂorum populations.

88 4 Assessment of prosulfocarb-resistance evolution

4.1 Introduction

Prosulfocarb is used increasingly in winter cereals in Europe and Australia as a consequence of resistance evolution to ACCase and ALS herbicides in grass weeds. Over the past five years, its market share within this seg- ment has doubled in France where it is the only residual herbicide for which acreage treated has increased (Luc Flamant, personal communication). Pro- sulfocarb resistance has been documented in Alopecurus myosuroides Huds. populations from England [145] but has yet to be reported in ryegrass. The maximum recommended prosulfocarb rate for pre-emergence ryegrass control in winter cereals in Europe is 4,000 gai/ha. Under greenhouse conditions and in unsterilized soil with low organic matter content, this rate typically provides above 80% control of susceptible populations (see Chapter3). Effic- acies as low as 60% for ryegrass control can be observed even under optimal field conditions (Jason Tatnell, personal communication). Prosulfocarb can be regarded as a herbicide that does not provide full grass weed control even at the highest recommended field rate; 4,000 g prosulfocarb/ha may act as a sub-optimal or sub-lethal dose. Increasing prosulfocarb rates to 8,000 gai/ha or even 16,000 gai/ha do not confer 100% mortality (personal observation). Any further dose increase results in unrealistic concentrations due to underlying physical spraying issues.

Several studies have now demonstrated that sub-lethal herbicide rates can lead to the rapid evolution of resistance in known susceptible populations of cross-pollinated species such as ryegrass, thus encouraging growers to always apply herbicides at the full label rate. For instance, Busi and Powles [132] reported a signiﬁcant shift towards resistance in the suscepti-

89 CHAPTER 4. Assessment of prosulfocarb-resistance evolution ble Lolium rigidum Gaud. population VLR1 after three cycles of recurrent selection with glyphosate at 150 gai/ha (one third of the Australian field rate). The parameters of the shift, i.e. rapidity and amplitude, between the parental susceptible population and the selected progenies may be herbicide- dependent. This glyphosate recurrent selection conferred less than 3-fold resistance after three cycles while similar studies also conducted on VLR1 with the ACCase inhibitor diclofop-methyl resulted in up to 18-fold resistance and more than 40-fold after respectively two and three cycles of selection [132–134]. The selection intensity exerted by the herbicide is also likely to influence the amplitude of the resistance shift. A VLR1 progeny selected with 1/10, then 1/5 and finally 1/2 diclofop-methyl field rate was three to five times less resistant than a progeny selected under the same experimental conditions with 1/10, 1/5 and 1 time the field rate [134]. Plants surviving 4,000 g prosulfocarb/ha could potentially carry minor genes endowing resistance, which could quickly accumulate and spread in the event of a missed post-emergence application. It was therefore of interest to investigate the potential of prosulfocarb to select for phenotypic variations that would result in the development of resistance in a known susceptible ryegrass population.

Prosulfocarb resistance evolution was investigated using a recurrent selection process at 4,000 gai/ha. Cross-resistance patterns with dissimilar herbicides and especially with ACCase and ALS inhibitors aﬀected by non- target-site based resistance have been documented in recurrent selection experiments [133, 134]. Putative cross-resistance patterns were therefore evaluated on the selected progenies with (i) clodinafop-propargyl as a representative of ACCase inhibitors aﬀected by metabolic-based resistance, (ii) iodosulfuron as a representative of ALS inhibitors and (iii) ‘Experimental Compound X’, an herbicide under-development at Syngenta with a mode of action similar to prosulfocarb (Ian Zelaya, personal communication).

90 4.2. Materials and Methods

4.2 Materials and Methods

4.2.1 Recurrent selection

The recurrent selection process was initiated in April 2009. Seeds of the susceptible standard Lolium multiflorum Lam. population G0 were pre- germinated on agarose as described in section 2.1.6 and transplanted into 3” pots filled with TMA soil at BBCH05-07. One hundred and twelve pots were treated with prosulfocarb at 4,000 gai/ha or left untreated as control. The number of survivors was recorded 21 days after application (DAA). The individuals that survived prosulfocarb at 4,000 gai/ha and grew vigorously after the assessment were transplanted into 4” pots containing JIP compost and grown to maturity until seed harvest (see section 2.1.11). The selection process was repeated two more times and the third and last generation G3 was harvested in February 2011. The effective population size was calculated after each cycle according to Wright [150] with the formula described in

Equation 4.1, where Ne is the eﬀective population size, t the generation number and Nfi the number of plants that produced ﬂowers and seeds at generation i.

t 1 1 X 1 = (4.1) N t Nf e i=1 i

4.2.2 Resistance proﬁle

Response to recurrent selection with prosulfocarb

The development of prosulfocarb resistance from the parental susceptible population G0 to the last prosulfocarb-selected progeny G3 was evaluated with three diﬀerent test formats and several endpoints:

1. PRE single dose. In order to determine whether the selection process resulted in a sensitivity shift of practical signiﬁcance, prosulfocarb was applied at 4,000 gai/ha on both G0 and G3. Seeds were pre-germinated onto agar as previously described. Five seeds per population were transplanted into 4” pots ﬁlled with TMA soil. A total of 15 pots, i.e. 75 seeds per population were either treated with prosulfocarb at 4,000 gai/ha or left untreated as control. The experiment was carried out a total of three times between March and April 2011.

91 CHAPTER 4. Assessment of prosulfocarb-resistance evolution

The emerged plants were counted 21 DAA and their dead-or-alive status was recorded (Figure 4.1). Weed control was then visually assessed and an injury score was given to each and every emerged plant. Dead plants were scored as 98%/99% or 100% control whether the ﬁrst leaf had emerged through the coleoptile or not. Surviving plants were scored anything between 0% (as untreated) and 97% (Figure 4.1).

2. PRE sand dose-response. As highlighted in Chapter3, the sand bioassay maximises prosulfocarb bioavailability for the weed seeds. A dose-response experiment performed on sand was carried out to detect any small differences related to prosulfocarb efficacy between G0 and G3. Grade 1 filter papers were placed to cover the holes at the base of EPS punnets that were then filled with Humax silver sand. Twelve pre-germinated seeds of both G0 and G3 were transplanting into each punnet, and three punnets were treated with 0; 10; 20; 40; 80; 160; 320; 640 and 1,000 gai/ha prosulfocarb. The dose-response experiment was performed a total of three times. Assessments were carried out 21 DAA as described above.

3. Prosulfocarb foliar efficacy. The recurrent selection process was performed with prosulfocarb applied PRE. However, prosulfocarb is increasingly used in post-emergence mixtures. For instance, the formulated mix prosulfocarb+clodinafop can be applied at 2,400+30 gai/ha as soon as weeds have reached BBCH10. Any resistance trait that had been selected during the recurrent selection process may also affect prosulfocarb foliar efficacy. Seeds of G0 and G3 were directly sown into 4” pots filled with TMA soil in order to obtain approxim- ately 30 emerged seedlings in each control pot. Three replicate pot units were produced per treatment. Pots were treated with 2,400 g prosulfocarb/ha when the seedlings had reached BBCH10-11 (about 9 days after sowing). Control pots were not sprayed. The experiment was repeated three times. Biomass reduction was visually recorded 21 DAA.

92 4.2. Materials and Methods

Figure 4.1: Examples of injury scoring for ﬁve pre-germinated seeds per pot 21 days after a PRE application of 4,000 g prosulfocarb/ha. After treatment a given seed may or may not have lead to an emerged seedling. After emergence the seedling was either dead or alive. An injury score was then attributed to each and every emerged seedling.

Cross-resistance evaluation with ‘Experimental Compound X’

‘Experimental Compound X’ is under development at Syngenta for the control of broad-leaved weeds in maize. It is a low rate herbicide achieving high pre-emergence control on key weeds, including some grasses. Its mode of action resembles the inhibition of VLCFA elongases and it is chemically unrelated to prosulfocarb. Therefore, it was a compound of choice for assessing whether the recurrent selection process had triggered any biological mechanisms that could confer resistance to it. Seeds of both G0 and G3 were sown onto dry TMA soil, covered with dry soil and subsequently sprayed with 0; 3.75; 7.5; 12.5; 25; 50; 100 and 300 gai/ha. Pots were hand-watered half a day after herbicide application. There were about 15 emerged seedlings in the control pots for G0 and 45 for G3. Three replicate pot units were produced per rate and per population. The experiment was carried out only once. Biomass reduction was visually recorded 21 DAA.

93 CHAPTER 4. Assessment of prosulfocarb-resistance evolution

Cross-resistance evaluation with ACCase and ALS inhibitors

G0 and G3 were assessed for diﬀerences in ACCase and ALS susceptibility using a single rate of clodinafop and iodosulfuron. The rates were chosen in order to (i) be sub-lethal and (ii) result in about 50% of biomass reduction for the survivors. G0 and G3 seeds were sown in trays containing JIP compost, covered with JIP:vermiculite and watered as needed. Three seedlings were then transplanted into 4” pots (JIP compost) seven to nine days after sowing. Pots were treated about seven days after transplanting, i.e. when seedlings had reached BBCH11-12. A total of 90 seedlings per generation were respectively sprayed with clodinafop at 7.5 gai/ha and iodosulfuron at 1.25 gai/ha while 45 seedlings were left untreated. Plant survival and individual biomass reduction was visually assessed 21 DAA.

4.2.3 Data analysis

PRE sand dose-response assay

Plant survival was calculated as described in Equation 4.2 for G0 and G3. Datasets from repeated experiments were pooled and ﬁtted to a non-linear log-logistic regression model as detailed in section 2.1.12.

(n ) survival = alive treated (4.2) (nemerged)untreated

Single-dose experiments

The datasets from each experiment for the PRE treatment at 4,000 gai/ha, were treated separately. Fisher’s exact tests for count data were carried out with the dead-or-alive records. Kolmogorov-Smirnov tests (KS-tests, [151]) were then performed to determine whether the diﬀerences observed for the weed control distributions for G0/G3 survivors were signiﬁcant. When they were, location tests were carried out (Wilcoxon Mann-Whitney exact rank sum tests or WMW-test) to test the equality of the mean values and a median test to test the equality of medians [152]. A similar approach was undertaken to analyse the datasets from the clodinafop and iodosulfuron POST treatments. Datasets of the three repeated experiments for prosulfocarb foliar application at 2,400 gai/ha were pooled in order to have a total

94 4.3. Results of nine data points per generation tested. The Wilcoxon Mann-Whitney exact test was then performed.

4.3 Results

4.3.1 Recurrent selection

Sixty-one G0 seedlings out of the 110 finally treated with prosulfocarb at 4,000 gai/ha for the first recurrent selection cycle had emerged (BBCH09, when the coleoptile penetrates the soil surface). Forty-one of them withstood the application while 20 died soon after the cracking stage. Thirty-six survivors grew vigorously and produced flowers and seeds for the next generation G1 (Table 4.1). All the plants kept for bulking did not produce flowers at the same time. Phytohormones such as GA5 and GA6 are known to synchronise flowering in Lolium species [153]. However, such treatments were not applied in order to avoid any further plant stress. The effective population size was 20 after three cycles of selection.

4.3.2 Response to recurrent selection with prosulfocarb

Pre-emergence application at the practical ﬁeld rate of 4,000 gai/ha

Fisher’s exact tests for count data were performed on the dead-or-alive records for each experiment to test the significance of the differences between the parental susceptible population G0 and the last selected progeny G3. There was no statistical difference between the number of survivors after prosulfocarb application between G0 and G3 in experiment 1 and experiment 3 (Table 4.2). In the second experiment, G3 was associated with resistance to prosulfocarb in term of number of survivors. The weed control data for the survivors was subsequently analysed with the KS-tests and location tests (Figure 4.2, Table 4.3). The parental susceptible population G0 and the last prosulfocarb-selected progeny G3 showed similar weed control patterns for experiment 1 and experiment 3. Conversely, significant differences were observed for experiment 2 in term of average percentage of weed control and of median. This was due to the excellent control of G0 observed in this second experiment. Patterns observed for G3 were consistent across the three experiments (p-value>0.13). Based on this series of experiments,

95 CHAPTER 4. Assessment of prosulfocarb-resistance evolution oteslcino h hr progeny. (21DAA); third the time of selection the to 4.1: Table emergence; 4.1 . Equation with calculated as size population xeietGnrto Treatment Generation Experiment n ubro edig novdi h rsloabrcretslcinpoes rmtessetbesadr ouainG0 population standard susceptible the from process, selection recurrent prosulfocarb the in involved seedlings of Number b G0 1 G2 G1 3 2 h ubro lnskp o bulking; for kept plants of number the n A h ubro survivors; of number the n T rsloab400gih 1 23 12 91 20 15 25 19 19 36 25 29 36 41 31 11 31 40 57 42 33 112 20 90 gai/ha 4,000 41 prosulfocarb 112 61 gai/ha 4,000 prosulfocarb 110 gai/ha 4,000 prosulfocarb stenme fpegriae ed used; seeds pre-germinated of number the is n D nrae 1 0 108 108 112 106 106 112 104 104 Untreated 112 Untreated Untreated h ubro edselns uvvl() h ecnaeo uvvr eaieto relative survivors of percentage the (%), Survival seedlings; dead of number the , N f h ubro lnsta rdcdflwr n ed and seeds and flowers produced that plants of number the n T n E n n A E h ubro mre edig tassessment at seedlings emerged of number the n D uvvl(%) Survival n b N f N e h effective the N e

96 4.3. Results it appeared that G3 was controlled in a more or less same manner as G0, suggesting that the recurrent selection process had not yet selected for any major biological mechanisms that could confer resistance to prosulfocarb at the practical ﬁeld rate of 4,000 gai/ha.

exp.3 100 ● 80 ● 60

0 exp.1 exp.2 100 ● ● ● ● 80

40 weed control (visual percentage) weed 20

0 G0 G3 G0 G3

Figure 4.2: Distribution of the weed control values for the plants that survived 4,000 g prosulfocarb/ha. The median is represented with a solid dot, outliers are represented with a cross, whiskers extend to the minimum and maximum values in the absence of outliers.

97 CHAPTER 4. Assessment of prosulfocarb-resistance evolution

Table 4.2: Herbicide sensitivity at 4,000 g prosulfocarb/ha for the parental susceptible population G0 and the last selected progeny G3 across three distinct experiments with the p-value of Fisher’s exact tests. nA is the number of survivors and nD the number of dead plants out of the emerged seedlings at the assessment time (21DAA).

Experiment number 1 2 3

nA nD Mortality nA nD Mortality nA nD Mortality G0 15 24 62% 7 47 87% 23 16 59% G3 26 28 52% 29 26 47% 30 22 42% p-value 0.40 < 10−5 1

Table 4.3: Kolmogorov-Smirnov and location tests outputs for the weed control data for the plants that survived 4,000 g prosulfocarb/ha (α = 0.05). KS-test WMW-test median D p-value Z p-value Z p-value experiment 1 0.2051 0.42 experiment 2 0.5123 0.02 2.3416 0.02 -2.414 0.03 experiment 3 0.1551 0.51

98 4.3. Results

Dose-response sand bioassays

After three cycles of recurrent selection, G3 was shifted from the parental population G0 (Table 4.4, Figure 4.3). RF50 values were 1.66 for the weed control data (emerged seedlings) and 1.96 for plant survival. Based on the comparison carried out between sand and TMA soil in Chapter3, 4,000 gai/ha corresponds to 160 gai/ha in the sand assay (see section 3.4.2). At this rate, three times more G3 seedlings survived than G0 (respectively 12% and 4%). However, the Fisher’s test was not signiﬁcant for that rate (p-value = 0.11). Altogether, this suggested that only minor biological mechanisms eﬀective at low prosulfocarb rates have been selected during the recurrent selection process.

100 ● ● ● ● ● 1.0 ● ● G0 G3

80 ● 0.8 ●

60 0.6

● 40 0.4 ●

● survival (x100)

20 0.2 ● weed control (visual percentage) weed ● G0 ● 0 G3 0.0 ● ● ● 1 10 100 1000 1 10 100 1000 prosulfocarb rate in gai/ha prosulfocarb rate in gai/ha

(a) Visual biomass reduction (b) Survival

Figure 4.3: Dose-response curves for the parental susceptible population G0 and the third prosulfocarb-selected progeny G3 against a range of prosulfocarb rates.

Prosulfocarb foliar application

Putative differences in efficacies between G0 and G3 for prosulfocarb applied post-emergence were evaluated at 2,400 gai/ha. Raw data per experiments are presented in Figure 4.4. Taking the mean and the median there was no statistical difference between G0 and G3 (p-values of respectively 0.25 and 0.35). This suggested that prosulfocarb foliar uptake was similar in G0 and G3 and/or that prosulfocarb activation and translocation was comparable.

99 CHAPTER 4. Assessment of prosulfocarb-resistance evolution hr eetdpoeyG n h orsodn eitnefcosa 0 ee fcnrl(F0=G3/G0). = (RF50 control of level 50% at factors resistance corresponding the and G3 progeny selected third 4.4: Table aaeeso h o-oitcmdlue oetmt h D0vle o h aetlssetbepplto 0adthe and G0 population susceptible parental the for values ED50 the estimate to used model log-logistic the of Parameters eeainFte data Fitted Generation 36 6-6 .6(1.64-2.34) 1.96 (1.36-2.03) (61-76) 1.66 68 (27-35) 31 G3 G0 G3 G0 0 -1.80 100 0 4.3a ) (Figure damages visual 0 1.89 100 0 4.3b ) (Figure survival b d c D0(I9% F0(I95%) (CI RF50 95%) (CI ED50 4(23)n.a. (32-37) 34 9(72)n.a. (17-20) 19

100 4.3. Results

G0 G3

100 ● ● ● ● ● ●

20 weed control (visual percentage) weed

exp.1 exp.2 exp.3 exp.1 exp.2 exp.3

Figure 4.4: Distribution of the weed control values for prosulfocarb applied at BBCH11 on the parental susceptible population G0 and the third selected progeny G3. The median is represented with a solid dot, outliers are represented with a cross, whiskers extend to the minimum and maximum values in the absence of outliers.

101 CHAPTER 4. Assessment of prosulfocarb-resistance evolution

4.3.3 Cross-resistance evaluation with ‘Experimental Compound X’

Parallel curves (b = −4.41) with common asymptotic limits at 100 and 0 were ﬁtted for G0 and G3 (Figure 4.5). There was no shift in eﬃcacy for the ‘Experimental Compound X’ and the RF50 value was estimated at 0.99 (95% CI = 0.77 - 1.27). There was no evidence of resistance evolution to this experimental compound after three cycles of recurrent selection with prosulfocarb.

100 ● ●

●

80 ●

weed control (visual percentage) weed ● G0 ● ● 0 ● G3 1 10 100 1000 'Experimental Compound X' rate in gai/ha

Figure 4.5: Dose-response curves (visual biomass reduction) for the parental susceptible population G0 and the third prosulfocarb-selected progeny G3 against a range of ‘Experimental Compound X’ rates.

4.3.4 Cross-resistance evaluation with ACCase and ALS inhibitors

Fisher’s exact test for count data showed that there was no difference in susceptibility to clodinafop applied at 7.5 gai/ha in terms of plant survival. Differences were significant for iodosulfuron at 1.25 gai/ha, with more plants from the unselected population G0 withstanding the herbicidal treatment

102 4.3. Results

(Table 4.5). The distribution of weed control data for the survivors is presented in Figure 4.6. KS-tests showed that there was no statistical diﬀerence in the shape of the distribution for the pair G0/G3 for the two herbicides tested (clodinafop(p-value) = 0.099 and iodosulfuron(p-value) = 0.16). In conclusion, the recurrent selection process with prosulfocarb did not result in major sensitivity shifts for either clodinafop or iodosulfuron.

CDF iodo

100 ● ●

● ● 20 weed control (visual percentage) weed

G0 G3 G0 G3

Figure 4.6: Distribution of the weed control values for clodinafop applied POST at 7.5 gai/ha (CDF) and iodosulfuron applied POST at 1.25 gai/ha (iodo) on the parental susceptible population G0 and the third selected progeny G3. The median is represented with a solid dot, outliers are represented with a cross, whiskers extend to the minimum and maximum values in the absence of outliers.

103 CHAPTER 4. Assessment of prosulfocarb-resistance evolution

Table 4.5: Herbicide sensitivity for clodinafop applied POST at 7.5 gai/ha and iodosulfuron applied POST at 1.25 gai/ha on the parental susceptible population G0 and the last selected progeny G3. nA is the number of survivors and nD the number of dead plants out at the assessment time (21DAA). The p-value associated to Fisher’s exact tests are reported underneath.

clodinafop iodosulfuron

nA nD Mortality nA nD Mortality G0 80 10 10% 64 26 29% G3 86 4 4% 42 48 53% p-value 0.16 <0.05

104 4.4. Discussion

4.4 Discussion

This study aimed to evaluate the potential of prosulfocarb resistance evolution in an initially herbicide-sensitive population of L. multiflorum. Several types of observation were chosen to fully appraise prosulfocarb effects on this population. There was some indication of a shift towards prosulfocarb resistance (Figure 4.3 and Table 4.4) that had minimal effects at the practical pre-emergence field rate of 4,000 gai/ha (Figure 4.2, Tables 4.2 and 4.3). No difference was observed at the post-emergence level (Figure 4.4). Like- wise, cross-resistance patterns with either ACCase and ALS inhibitors or the ‘Experimental Compound X’ were not observed (Figure 4.5).

The selected resistance mechanisms are unlikely to be target-site mediated

The condensation of a C2 unit to a long chain acyl-CoA (>C16) is the ﬁrst committed step for the production of very long chain fatty acids (C20-C36) in the endoplasmic reticulum. This reaction is performed by the 3-keto-acyl- CoA synthases (KCS) of the elongase multi-protein complex. More than 20 genes are known to encode for KCS enzymes in Arabidopsis thaliana (L.) Heynh. [154]. As reviewed in Chapter3 thiocarbamates and molecules belonging to the HRAC group K3 have a similar mode of action and were shown to inhibit more than one KCS enzymes. Therefore, the evolution of prosulfocarb target-site resistance may require the occurrence of simultaneous mutations in the genes encoding each inhibited enzyme without conferring any dramatic ﬁtness costs. This is less likely to happen than a mutation in a single target such as ACCase and ALS.

The physiological underlying resistance mechanisms may be speciﬁc to thiocarbamates

Assuming that the minor resistance mechanisms are non-target-site mediated, they may then involve herbicide metabolism processes. Prosulfocarb, as other thiocarbamates, is a pro-herbicide that is converted into a more potent sulfoxide form after absorption by the plant [38]. NADH-dependent enzymes have been shown to activate thiocarbamates in mammals and soil microorganisms [51, 155]. However, the precise plant enzyme sets involved

105 CHAPTER 4. Assessment of prosulfocarb-resistance evolution in this process have yet to be identified. Triallate resistance in wild oats is due to a metabolic loss of function. The activation rate was 10 to 15- times slower in the resistant populations tested compared to the susceptible ones [52]. Clodinafop degradation in wheat relies on the arylhydroxyla- tion of the pyridyl ring by P450s [156]. Chlorsulfuron undergoes similar metabolic reactions in ryegrass and iodosulfuron may follow the same route [108]. Assuming that only one enzyme set performs all these functions, a reduced prosulfocarb sulfoxidation may, on the contrary, enhance clodinafop or iodosulfuron efficacy as less degrading enzymes would be available for their breakdown, thus resulting in a higher plant mortality rate. Only slight evidence of such pattern was recorded for iodosulfuron applied at 1.25 gai/ha as less plants from the selected population G3 withstood the application (Table 4.5). In every instance, more recurrent selection cycles are required to confirm the hypothesis. Due to the low levels of response observed and the restrictive condition put on the enzyme sets, two alternatives can be proposed, (i) the enzyme sets involved in prosulfocarb sulfoxidation are thiocarbamate-specific and cannot significantly impact on either clodinafop or iodosulfuron efficacy or (ii) the generated levels of prosulfocarb-resistance were too small to induce any noticeable effects at the clodinafop rate investigated. Comparative efficacies of prosulfocarb and prosulfocarb-sulfoxide on G0 and G3 may determine whether reduced prosulfocarb sulfoxidation is a likely resistance mechanism in the selected progeny.

The underlying resistance mechanisms may be growth-stage dependent

The small shift observed towards resistance in the sand assay could also be due to a reduced hypocotyl uptake that would have only major influence at low prosulfocarb rates. Penetration resistance is a well established insecticide resistance mechanism that affects carbamate and organophosphate compounds [157] and has been shown to be mediated by ABC transporters overexpressed in the insect cuticle [158]. On the other hand, studies that looked at differential cuticular uptake as a mechanism for herbicide resistance did not report any significant differences between herbicide- resistant and sensitive sublines [66, 159, 160]. Only one study described a

106 4.4. Discussion cuticle thickening effect between glyphosate-resistant and sensitive L. multiflorum populations that may explain the differences observed in the absorption, contact angles, and spray retention between the two populations [cited in 161]. Reduced prosulfocarb uptake could be evaluated with hypocotyl penetration studies.

Inﬂuence of compounds, rates and time-scale

Only two cycles of recurrent selection on a susceptible population with sub- lethal doses of diclofop-methyl (1/10 and 1/5 of the field rate) resulted in a minimum of six-fold shift in resistance [134]. Conversely, three cycles with glyphosate applied at 1/3 followed by twice 5/9 of the field rate resulted in an average shift towards resistance of only 1.98 [132]. Glyphosate is considered as a low risk herbicide in terms of resistance evolution while the ACCase inhibitors, e.g. diclofop-methyl, are at high risk and thiocarbamates at moderate risk [162]. Resistance to triallate in wild oats from Canadian field was reported more than 20 years after repeated use suggesting a slow evolution of thiocarbamate resistance [163]. This prosulfocarb recurrent selection resembles more the glyphosate selection performed by Busi and Powles [132]. More selection cycles with prosulfocarb may be necessary to observe higher levels of resistance in Lolium populations. Lower prosulfocarb doses should also be investigated.

The selected resistance mechanisms may only be a consequence of the experimental design

Two recurrent selection cycles on a susceptible L. rigidum population conducted with sub-lethal rates of diclofop-methyl in (i) a field environment with wheat competition and (ii) in pots grown outdoors, resulted in a six- fold resistance difference between the pot-selected progeny and the field- selected progeny [133]. Herbicide field applications were performed with a boom sprayer at crop establishment while the pots were sprayed with a laboratory sprayer. Uneven herbicide exposure was very probably more important in the field due to crop-shading, drift and any environmental factors enhancing herbicide dissipation. Some surviving plants may be fully sensitive while others carry resistant alleles. This was confirmed with the slower resistance evolution to diclofop-methyl in the field environment compared

107 CHAPTER 4. Assessment of prosulfocarb-resistance evolution to the pot experiment [133]. The present prosulfocarb-recurrent selection study was carried out under ideal experimental conditions that maximised prosulfocarb uptake, i.e. single pre-germinated seeds were transplanted per 45 cm2, sprayed with 4,000 g prosulfocarb/ha, and survivors were not subjected to any competition for nutrients. This may have selected the resistance traits quicker than under field conditions as reported by Manalil et al. [133]. When prosulfocarb is applied at the pre-emergence stage in a field, uneven coverage occurs due to shadowing effects of clods. The impacts on prosulfocarb efficacies against A. myosuroides were such that reduced angled nozzles were especially developed to replace the traditional 110◦ fan jet and minimise efficacy losses [164]. Genetic variability of populations subjected to bottleneck declines, which results in the rapid fixation on the selected trait [165]. This effect is enhanced as population size decreases. The more highly selected a strain the smaller the number needed for keeping it [166]. An average of 25 plants were involved in the crosses during the prosulfocarb recurrent selection process. Although Cooper [167] showed that much genetic variation can be carried within only one ryegrass individual, this may have lead to the quicker fixation of the prosulfocarb-resistance traits. It is then expected that true field resistance to prosulfocarb as a result of its own repetitive application would only develop extremely slowly. The starting material also plays a major role as exemplified by the study conducted by Neve and Powles [135]. Thirty-one L rigidum populations were collected from Australian non-farm sites with no history of herbicide treatment and where there was little probability of gene flow from adjacent resistant populations. After two consecutive applications of diclofop-methyl at field rate, five populations were selected with survival frequencies from 0.28% to 1.1%. A diclofop-methyl dose-response experiment conducted on the five progenies resulted in very diverse resistance profiles with a highly resistant progeny (Kudardup) and a low resistant progeny (Busselton 2) (Figure 4.6). This showed that a variety of responses can be obtained with fairly similar starting material in terms of sensitivity to the herbicide studied. Consequently, in order to better understand the biological mechanisms responsible for the small shift towards prosulfocarb resistance observed from G0 to G3, it is of critical importance to (i) conduct similar recurrent selec- tions with other sensitive Lolium spp. populations, (ii) investigate the in-

108 4.4. Discussion

ﬂuence of the number of surviving plants used to generate the progeny and (iii) investigate the importance of the growth conditions, e.g. greenhouse vs. outdoors conditions and presence or absence of crop competition.

Table 4.6: Details of the ﬁve non-farm population selected after two consecutive diclofop-methyl applications at the Australian commercial ﬁeld rate (375 gai/ha). The percentage survival (out of about 1,000 plants) is presented, as well as the number of surviving plants per population that were allowed to cross-pollinated to generate the corresponding progeny. The RF50 values are the ratio of the ED50 values obtained after a diclofop-methyl dose-response experiment with the parental population and the progeny. It is worth noting that resistance was not due to an insensitive ACCase target. M stands for mortality and FWR for Fresh Weight Reduction. Adapted from Neve and Powles [135].

Population ID % survival No. survivors RF50 (M) RF50 (FWR) Busselton 2 1.1 13 2.8 3.9 Gnangara 0.91 9 5.2 3.1 Busselton 1 0.63 7 13.4 15.4 Kudardup 0.49 6 23.2 9.4 Victoria 9 0.28 4 6.2 6.2

Role of prosulfocarb survivors for maintaining sensitivity to herbicides

The sand bioassay provided some indication of a shift towards prosulfocarb resistance from G0 to G3. However, these effects were not significant at the practical PRE field rate of 4,000 gai/ha. The survivors may only be genuine escapes, in other terms susceptible plants, as a consequence of uneven herbicide exposure. When prosulfocarb was initially applied, the biological effect of the dose received varied between individuals although extreme care was taken to reduce variations induced by plant growth. Modelling studies showed that variation in pesticide dose received may substantially slow down the development of resistance [168]. Of interest, it was demonstrated that the greater the spread of the dose received by treated individuals in the population for a given degree of control, the less selection occurs. Finally, these prosulfocarb-sensitive survivors may play the role of ‘resistance trait diluents’ when crossing with plants exhibiting other resistant traits such as resistance to ACCase or ALS inhibitors.

109 CHAPTER 4. Assessment of prosulfocarb-resistance evolution

4.5 Conclusions and Perspectives

This study showed that small shifts towards prosulfocarb-resistance can be artificially selected under greenhouse conditions in a susceptible L. multiflorum population. After three cycles of recurrent selection, the underlying mechanisms did not impact on either prosulfocarb efficacy applied PRE at 4,000 gai/ha or POST at 2,400 gai/ha. Likewise, cross-resistance with the dissimilar compounds clodinafop, iodosulfuron and ‘Experimental Com- pound X’ was not observed. More selection cycles, larger population sizes, other sensitive Lolium spp. populations, selection at lower rates and/or different growth stages and/or under different growing conditions are necessary to determine whether effects of agronomical importance can be obtained or whether the prosulfocarb survivors were only genuine escapes. P450s are involved in the degradation routes of both prosulfocarb and clodinafop, although none of them have been precisely identified. Cross-resistance between prosulfocarb and clodinafop was not observed as a consequence of prosulfocarb selection probably due to the too low levels of resistance generated in the present study. High levels of non-target-site based resistance to clodinafop may be required to confer resistance to prosulfocarb. This aspect is investigated in Chapter5.

110 5 Prosulfocarb eﬃcacy over selected non-target-site based resistance to clodinafop-propargyl in Lolium multiﬂorum Lam. progenies

5.1 Introduction

The excellent eﬃcacy and selectivity of herbicides that inhibit the enzymes acetolactate synthase (ALS) and acetyl-CoA carboxylase (ACCase) have led to their wide adoption for post-emergence grass control in small grain cereal crops. However, overreliance over the past 30 years has resulted in the development and spread of herbicide resistance. Several mechanisms can reduce ACCase inhibitors eﬃcacy in ryegrass including target-site resistance and enhanced metabolism (reviewed in Chapter1).

Cross-resistance to ALS inhibitors endowed by enhanced metabolism to ACCase inhibitors have been established by several recurrent selection studies [133–135]. Genetic control studies of P450-mediated resistance to diclofop- methyl and chlorsulfuron showed dominance of the nuclear inherited resistant trait at the recommended field rate of both molecules and suggested that resistance was endowed by two additive genes [169]. Non-target-site based resistance mechanisms also confer unpredictable resistance patterns that impact greatly on the efficacy of current products and those under development with the same or different modes of action [92, 170]. Lolium are cross-pollinated species with pollen capable of travelling considerable dis- tances [13, 171]. Besides, neighbouring fields are not independent units and gene flow can freely operate between conventional and organic fields. As

111 CHAPTER 5. Prosulfocarb vs. ACCase non-target-site based resistance recently shown for another allogamous wind-pollinated species (Alopecurus myosuroides Huds.), conventional fields with lower weed densities can act as ‘genetic sinks’ that facilitate the diffusion of ACCase-resistance traits to organic fields worsening the problem of herbicide resistance as the trait can move back to conventional fields [172].

Consequently, pre-emergence compounds like prosulfocarb are increasingly used in herbicide programs and sequences to suppress as many weeds as possible as early as possible in the season and thus relieve the pressure put on ACCase and ALS inhibitors. After absorption by the plant, prosulfocarb is converted into a more potent sulfoxide that is potentially rapidly conjugated by GST enzymes [38]. Although GSTs have not been shown to be involved in any clodinafop degradation route yet, they are known to metabolise the ACCase inhibitor fenoxaprop-p-ethyl in A. myosuroides and maize [173, 174]. Lastly, the metabolic attack on clodinafop and prosulfocarb starts with a monooxygenation [38, 156]. However, Chapter4 showed that the low levels of prosulfocarb-resistance artificially selected under a greenhouse environment did not confer cross-resistance to clodinafop. Higher levels of prosulfocarb-resistance may be necessary to significantly impact on clodinafop efficacy. Resistance to prosulfocarb has evolved very slowly and the time constraints did not allow any further recurrent selection cycles. Another approach to appraise the putative relationships between clodinafop and prosulfocarb resistance is to select a ryegrass field population exhibiting high levels of non-target-site based resistance mechanisms to clodinafop and evaluate prosulfocarb efficacy. Three recurrent selection cycles with high rates of clodinafop were carried out on such population to further increase the levels of resistance. Cross-resistance patterns with ALS inhibitors were investigated using iodosulfuron.

5.2 Materials and Methods

5.2.1 Seed source

Seeds of the L. multiflorum population UK225.G0 were harvested in 2005 in a Cambridgeshire field, UK. The initial sensitivity profile of UK225.G0 was determined alongside the susceptible standard population G0 with se-

112 5.2. Materials and Methods lected ACCase and ALS inhibitors. Seeds of both populations were sown in troughs ﬁlled with TMA soil. Three replicate units per treatment were produced. A total of eight diﬀerent compounds was applied at BBCH11 as described in section 2.1.7, i.e. clodinafop at 30 gai/ha; pinoxaden at 45 gai/ha; cycloxydim at 200 gai/ha; sethoxydim at 200 gai/ha; haloxyfop at 150 gai/ha; iodosulfuron at 10 gai/ha; sulfometuron at 100 gai/ha and imazapyr at 100 gai/ha. Herbicide damage was visually recorded 19 days after application.

5.2.2 Recurrent selection

The recurrent selection process was initiated in June 20061. For each treatment, 28 seedlings of G0 and UK225.G0 were individually transplanted in 3” pots containing JIP compost. Clodinafop at 15; 30; 60; 120; 240; 480; 960; 1,920 and 3,840 gai/ha was applied at BBCH11-12. The number of survivors was recorded 26 days after application. Dose-responses were analysed with a log-logistic model as described in section 2.1.12. The individuals that survived clodinafop at 240, 480 and 960 gai/ha and grew vigorously after a subsequent 42 DAA assessment were selected for seed production. A UK255.G1 progeny was then obtained. The selection process was repeated in February 2007 using a similar experimental procedure2. The number of seedlings treated per rate is presented in Table 5.1. The 29 UK225.G1 seedlings that survived clodinafop at 1,920 and 3,840 gai/ha were selected and crossed to obtain a UK225.G2 generation. The last selection was carried out in April 2008 (Table 5.1). Out of the 57 individuals that survived clodinafop at 1,920 and 3,840 gai/ha, only 15 grew vigorously after the assessment. They were then transplanted in 4” pots containing JIP compost, trimmed and tillered as needed until heading (BBCH 51). Seed production was then as described in section 2.1.11.

5.2.3 ACCase resistance mechanisms

Preliminary work conducted after the ﬁrst clodinafop dose-response suggested that the UK225.G0 survivors collected at 240, 480 and 960 gai/ha did

1This work, with the exception of the dose-response analysis, was carried out by Amy Lycett, Syngenta, Jealott’s Hill. 2This work was also carried out by Amy Lycett, Syngenta, Jealott’s Hill.

113 CHAPTER 5. Prosulfocarb vs. ACCase non-target-site based resistance

Table 5.1: Number of seedlings treated for the recurrent selection process with clodinafop-propargyl.

Clodinafop rate in gai/ha Date Population 0 15 30 60 120 240 480 960 1,920 3,840 G0 7 7 7 7 7 14 7 7 7 7 Feb. UK225.G0 27 27 28 28 27 56 54 56 56 56 2007 UK225.G1 28 28 27 26 27 54 52 55 55 56 G0 14 14 14 14 14 14 14 14 14 14 April UK225.G0 28 0 0 28 28 70 70 70 70 70 2008 UK225.G1 28 0 0 27 28 70 70 70 70 70 UK225.G2 26 0 0 27 28 70 69 70 70 70

not contain any known ACCase target-site resistance mutation3. However, it was not possible to precisely link this information to each and every selected survivor. Moreover, initial plant material was not available to repeat and complement the analysis. In order to ascertain the resistance mechanisms selected in population UK225.G0 during the ﬁrst selection process an a posteriori approach was undertaken. Eighty-three UK225.G0 seedlings were sprayed with clodinafop at 480 gai/ha (March 2010). Thirty of them withstood the application. The 24 plants that grew vigorously after the assessment were used for subsequent molecular and enzymatic studies.

Molecular studies

Seven individuals were selected for cloning and sequencing a fragment of the ACCase CT domain, namely UK225.G0.10, UK225.G0.24, UK225.G0.28, UK225.G0.54, UK225.G0.58, UK225.G0.62 and UK225.G0.75. As introns are not reported in the targeted region, sequencing was carried out on a PCR fragment generated from genomic DNA [90]. A leaf fragment of the plants listed above and from two known herbicide-sensitive populations (G0 and 2005 UK 203) was sampled. Total genomic DNA was manually extracted as described in section 2.2.1. The primer pair was designed to encompass 1,967 bp of the CT domain covering the region where polymorphisms have been reported to confer resistance to ACCase inhibitors, i.e. between residue 1,644

3This work was carried out by Alexandra Rowland during June-August 2006, Syngenta, Jealott’s Hill.

114 5.2. Materials and Methods and 2,299 [9, Chap. 7]. PCR amplifications were performed using Easy-A High-Fidelity PCR Master Mix (Agilent Technologies, Stockport, UK) in a final volume of 50 µL consisting of 5 µL of purified DNA template, 0.3 µM of each primer (CT forward: 5’-GGTATGGTAGCCTGGATCTTGGAC-3’ and CT reverse: 5’-ATGGA AGACCCTGCGGCAGG-3’), 25 µL of Easy-A 2X master mix and sterile water. The thermal cycler was programmed with an initial denaturation step at 94◦C for 2 minutes followed by 40 cycles of 10 s at 94◦C, 30 s at 60◦C and 2 min at 72◦C. A final extension step of 10 min at 72◦C was added, products were kept at 4◦C until use and subsequently stored at -20◦C. PCR products were visualized under UV lamps in 1.2% or 1.5% (w/v) agarose/1X TBE buffer gels. The products of interest were then excised and purified using ZymocleanTM Gel DNA Recovery Kit (Cambridge Bioscience, Cambridge, UK) according to manufacturer’s recommendations. Ultra-pure DNA was eluted in 6 µL of pre-warmed sterile water at 65◦C. Finally, cloning of the purified PCR products was carried out using StrataClone PCR Cloning Kit (Agilent Technologies, Stockport, UK). The ligation reactions (3 µL cloning buffer + 2 µL ultra-pure PCR product + 1 µL vector) were incubated overnight at 4◦C. The transformation of the competent cells was performed according to the manufacturer’s recommendations with 2 µL of the ligation reactions. After a 2-hour recovery period, the cells were plated on LB-kanamycin agar supplemented with 40 µL of 2% X-gal. After overnight incubation at 37◦C, a number of white colonies were picked for each transformation reaction and PCR-checked to confirm that they contained the correct in- sert. PCRs were carried out using puReTaq Ready-To-Go PCR beads (GE healthcare, Little Chalfont, UK) in a final volume of 25 µL consisting of 0.3 µM of each primer (F9: 5’-TGGCAGAGCAAAACTTGGAGGG-3’ and CT reverse) and sterile water with the PCR programme detailed above. Three positive colonies for each transformation reaction were subsequently grown overnight in V-tubes containing 5 mL of liquid LB medium supplemented with 5 µL of kanamycin stock solution at 50 µg.mL−1. Plas- mids were then purified using QIAprep Spin Miniprep Kit (Qiagen Ltd, Crawley, UK) and a benchtop centrifuge according to manufacturer’s recommendations. Purified plasmids were eluted in 50 µL buffer EB and sent for sequencing with the universal primers M13F and M13R and the customized primers F6 (5’-ATGTCCACTCCTGAATTTCCC-3’), F7 (5’-

115 CHAPTER 5. Prosulfocarb vs. ACCase non-target-site based resistance

ACAAGACACAGCTAGATAGTGG-3’) and F9. Traces were edited and aligned using the DNASTAR Lasergene suite including SeqMan and Meg- Align. As G0 and 2005 UK 203 are known to be sensitive to ACCase herbicides, SNPs were only recorded in the event of diﬀerences between the UK225.G0 individuals and the pair {G0-2005 UK 203}.

Enzymatic studies

A mutation conferring resistance to clodinafop located outside the range covered in the molecular studies described above would not be have been detected. Therefore, the ACCase activity of UK225.G0 survivors was assayed against selected ACCase inhibitors including clodinafop. ACCase extraction was carried out as described in section 2.3.1 with respectively 19.6 g of fresh leaf material from all UK225.G0 survivors and 13.87 g for the susceptible population G0. For each population, 11.7 mL of active fractions were obtained. The enzyme was subsequently assayed with the malachite green method (see section 2.3.2). The extracts were previously diluted in buﬀer C (300 µL.mL−1 for G0 and 320 µL.mL−1 for UK225.G0). Pairwise comparisons of IC50 values of G0 and UK225.G0 were performed using a t-test.

5.2.4 Resistance proﬁle

Response to recurrent selection with clodinafop

All the progenies were ﬁnally evaluated in a dose-response assay with clodinafop as described in Table 5.2. Seedlings were individually transplanted in 3” pots containing JIP compost. Treatments were applied at BBCH11-12. The number of survivors and the symptomatology for each and every individual were recorded 21 DAA and the dose-responses were analysed with a log-logistic model as described in section 2.1.12.

Response to prosulfocarb after the recurrent selection with clodinafop

Two diﬀerent aspects were chosen to fully appraise prosulfocarb eﬃcacy on the clodinafop-selected progenies:

116 5.2. Materials and Methods Clodinafop rate in gai/ha 0 1.875 3.75 7.5 15 30 60 120 240 480 960 1,920 3,840 7,680 Number of seedlings tested per population and clodinafop rate at the end of the recurrent selection process. G0UK225.G0 7UK225.G1 7UK225.G2 7 7UK225.G3 0 7 0 7 0 0 0 0 0 7 0 0 14 7 0 0 21 7 7 0 7 7 7 7 7 7 7 7 7 7 7 7 7 28 7 7 28 7 70 7 28 70 70 7 28 56 70 56 56 70 7 56 70 56 70 0 56 70 28 70 0 28 68 56 56 0 Table 5.2:

117 CHAPTER 5. Prosulfocarb vs. ACCase non-target-site based resistance

1. prosulfocarb application at the practical field rate of 4,000 gai/ha. Twelve replicate units were produced. Seeds of the susceptible population G0, the field population UK225.G0 and the clodinafop- selected progenies UK225.G1 and UK225.G2 were sown in troughs filled with TMA soil. Prosulfocarb was applied at the single rate of 4,000 gai/ha at BBCH03-05. Damages were visually recorded 21 days after application. Kolmogorov-Smirnov tests [151] were performed to determine whether the differences observed in the weed control distributions between the four populations were significant4.

2. prosulfocarb dose-response. The sand dose-response assay was designed to detect any small shifts towards resistance that are more pronounced at low prosulfocarb dosages (see section 4.3.2). It may also anticipate any issues that could arise in environments closer to field conditions should the recurrent selection process be continued. Two clodinafop-selected progenies were chosen for this study. UK225.G1 was taken as a reference instead of UK225.G0 firstly because there was no significant increase in the levels of clodinafop resistance between these two populations after the first selection cycle (see section 5.3.3) and secondly because UK225.G1 was the only progeny that was significantly less controlled than the susceptible standard population after prosulfocarb application at 4,000 gai/ha (see results presented in section 5.3.4). UK225.G3 was selected since it was the latest progeny obtained. Grade 1 filter papers were placed to cover the holes at the base of EPS punnets that were then filled with Humax silver sand. Twelve pre-germinated seeds of the susceptible standard population G0, UK225.G1 and UK225.G3 were transplanted into each punnet (see sections 2.1.1 and 2.1.6 for more details). Three punnets were treated with 0; 10; 20; 40; 80; 160; 320; 640 and 1,000 gai/ha prosulfocarb. The dose-response experiment was performed a total of two times. Assessments were carried out 21 DAA by counting the number of survivors and by recording the symptomatology for each and every plant that has emerged. Data analyses followed the procedure described in Chapter4 using Equation 4.2.

4These results were orally presented at the XIIIth International Conference on Weed Biology held in Dijon (France) in December 2009.

118 5.3. Results

Response to iodosulfuron after the recurrent selection with clodinafop

Resistance proﬁles between ACCase and ALS inhibitors were evaluated with iodosulfuron on all the UK225 populations following the method described for clodinafop. The number of seedlings tested per rate was as described in Table 5.3. The dose-responses were analysed with a log-logistic model as described in section 2.1.12.

Table 5.3: Number of seedlings tested per population and iodosulfuron rate.

Iodosulfuron rate in gai/ha 0 0.3125 0.625 1.25 2.5 5 10 20 40 80 160 320 G0 7 7 7 14 14 14 14 14 7 0 0 0 UK225.G0 7 0 7 14 28 84 84 84 56 28 7 7 UK225.G1 7 0 7 14 28 84 84 84 56 28 7 7 UK225.G2 7 0 7 14 28 84 84 84 56 28 7 7 UK225.G3 7 0 7 14 28 84 84 84 56 27 7 7

5.3 Results

5.3.1 UK225.G0 initial sensitivity proﬁle

The initial herbicide screen showed that UK225.G0 was highly resistant to the ACCase inhibitor clodinafop with minor levels of resistance to iodosulfuron (Table 5.4). Out of the five ACCase inhibitors tested, only clodinafop was strongly affected by resistance. The first clodinafop dose-response carried out for the recurrent selection process confirmed these high levels of resistance (Figure 5.1). All treated plants were alive at the recommended field rate of 30 gai/ha. Dead plants were only observed from 480 gai/ha. The ED50 value for UK225.G0 was estimated at 1,757 gai/ha (95%CI = 1,386 - 2,127), which was nearly 60 times the labelled rate.

5.3.2 ACCase resistance mechanisms determination

A gene fragment of the CT domain from amino acid position 1,644 to 2,299 (A. myosuroides equivalent) was PCR-ampliﬁed. Only ﬁve non-synonymous

119 CHAPTER 5. Prosulfocarb vs. ACCase non-target-site based resistance ouainU25G gis eetdACs n L niios ausaema ftrerpiaetog nt.Ayvlebelow value Any units. trough replicate necrosis. three complete of for mean codes are 100 Values survivors; of inhibitors. presence ALS the and indicated ACCase 98 selected against UK225.G0 population 5.4: Table K2.009 99 99 0 100 100 90 99 99 99 98 0 UK225.G0 09 91010109 0 100 100 99 100 100 100 99 97 G0 ecnaeo iulcnrlprhriieadpplto etdt eemn h nta estvt rfieo h field the of profile sensitivity initial the determine to tested population and herbicide per control visual of Percentage 0gai/ha 30 clodinafop 5gai/ha 45 pinoxaden Caeihbtr L inhibitors ALS inhibitors ACCase 0 gai/ha 200 cycloxydim 0 gai/ha 200 sethoxydim 5 gai/ha 150 haloxyfop 0gai/ha 10 iodosulfuron 0 gai/ha 100 sulfometuron 0 gai/ha 100 imazapyr

120 5.3. Results

● ● ● ● ● 1.0 ● G0 ● UK225.G0

0.8 ●

●

0.6 ●

0.4 survival (x100)

0.2 ● ●

0.0 ● ● ● ● ● ● ● ● 10 100 1000 10000 clodinafop rate in gai/ha

Figure 5.1: Survival data for the susceptible standard population G0 and the ﬁeld population UK225.G0. Line is the predicted response curve from the non-linear regression (upper asymptotic limit = 100, lower asymptotic limit = 0, slope (b) = 1.49). Symbols represent the data points. As all the data points for the standard sensitive population G0 were below 20% survival, the log-logistic model could not be ﬁtted and only the observation points were plotted. Therefore, resistance factors could not be estimated. G0 and UK225.G0 seedlings were sprayed at BBCH11 and mortality was recorded 19 DAA. polymorphisms were detected between the seven selected UK255.G0 survivors and the pair of known ACCase-sensitive populations {G0-2005 UK 203} (Table 5.6). However, none of them was consistently present in each and every plant tested. The only homozygous substitution was at position 1,729 in sample UK225.G0.54 where a proline (CCT) was replaced by an alanine (GCT). None of the polymorphisms known to confer resistance to ACCase inhibitors were found. Polymorphism at amino acid position 1,946 discovered in UK225.G0.24 has already been documented in a susceptible L. rigidum population from Australia [175]. The ACCase activity assay provided comparable IC50 values for UK225.G0 and the susceptible standard population G0 when tested with clodinafop (Table 5.5, p-value = 0.45). The dissimilar ACCase inhibitors pinoxaden acid and tralkoxydim were not

121 CHAPTER 5. Prosulfocarb vs. ACCase non-target-site based resistance aﬀected either (p-value = 0.16 and 0.11, respectively). Therefore, the molecular and enzymatic analyses established that the underlying resistance mechanism(s) aﬀecting clodinafop were not due to an insensitive ACCase target. Other assays, such as metabolic studies are required to establish the precise mechanism(s) involved in resistance to clodinafop in UK225 progenies.

Table 5.5: IC50 values obtained for the extracted ACCases from the susceptible standard population G0 and the clodinafop-selected survivors of UK225.G0. Values are expressed in µM for each herbicide tested and replicate (rep). Experiment 1 and 2 were conducted with the same enzyme batch using the same procedure but on two diﬀerent days. M denotes a missing value due to experimental issues. IC50 values were compared by a t-test and were not statistically diﬀerent for any herbicide tested (p-value > 0.11). clodinafop pinoxaden acid tralkoxydim rep 1 rep2 rep 1 rep2 rep 1 rep2 experiment 1 3.071 3.465 0.078 0.097 0.610 0.495 G0 experiment 2 M 2.281 0.089 0.097 0.555 0.247 experiment 1 1.126 3.240 0.092 0.101 0.349 0.519 UK225.G0 experiment 2 5.903 5.390 0.313 0.280 0.938 1.075

5.3.3 Response to recurrent selection with clodinafop

The three clodinafop-selected progenies, the parental population U225.G0 and the susceptible standard population were all tested against a clodinafop dose-response. The recurrent selection process resulted in a resistance increase of more than 3-fold between UK225.G0 and UK225.G3 (Tables 5.7 and 5.8, Figure 5.2). At a given rate, the UK225.G3 seedlings that withstood the treatment were more vigorous than the ones of the previous generations (Figure 5.3). For instance, at 240 gai/ha, 57% of the UK225.G0 seedlings survived (71% is the estimated value from the ﬁtted curve) while all UK225.G3 were alive. UK225.G0 seedlings were severely hit, i.e. stun- ted, leaf malformation and discoloration with an observed average of 81% damages while UK225.G3 plants were more vigorous with only 33% visual damages (Figure 5.3). The initial levels of resistance in the parental population UK225.G0 were extremely high for non-target-site based resistance mechanisms as the shift observed was greater than 20-fold.

122 5.3. Results

1.0 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 100 ● ● ● ● ● ● ● ● ● ● ● ● 0.8 80 ●

● ● ● ●

● ● 0.6 ● 60 ● ● ●

● ● ● 0.4 40 ●

● survival (x100) ● ● ● G0 ● ● ● UK225.G0 0.2 ● G0 20 ● ● ● UK225.G1 ● UK225.G0 ● ● ● weed control (visual percentage)) weed ● ● UK225.G1 ● ● UK225.G2 ● ● ● ● UK225.G2 ● ● ● UK225.G3 ● 0 ● ● 0.0 UK225.G3 ● ● ● ● ● ● ● ● ● 1 10 100 1000 10000 1 10 100 1000 10000 clodinafop rate in gai/ha clodinafop rate in gai/ha

(a) Visual biomass reduction (b) Survival

Figure 5.2: Dose-response curves for the susceptible standard population G0, the ﬁeld population UK225.G0 and the three subsequent clodinafop-selected progenies, UK225.G1, UK225.G2 and UK225.G3, against a range of clodinafop rates.

5.3.4 Response to prosulfocarb after the recurrent selection with clodinafop

Pre-emergence application at 4,000 gai/ha

On average, prosulfocarb provided the least control on the first clodinafop- selected progeny UK225.G1, i.e. mean of 65% visual damages compared to 73% for the susceptible population, 66% for the field population UK225.G0 and 68% for the second clodinafop-selected progeny UK225.G2 (Figure 5.4). Nevertheless, the Kolmogorov-Smirnov tests showed that there was no statistical difference in the shape of the distribution of weed control values for most of the pairs studied, i.e. G0 compared to UK225.G0 (p-value = 0.23), G0 compared to UK225.G2 (p-value = 0.23), UK225.G0 compared to UK225.G1 (p-value = 0.90), UK225.G0 compared to UK225.G2 (p-value = 0.54) and UK225.G1 compared to UK225.G2 (p-value = 0.84). The only significant difference was recorded for the susceptible standard population G0 compared to UK225.G1 (p-value = 0.02), probably due to the two outliers, i.e maximum control value of 90% for G0 and minimum control value of 40% for UK225.G1. To conclude, the field population UK225.G0 was recorded as sensitive as

123 CHAPTER 5. Prosulfocarb vs. ACCase non-target-site based resistance

Figure 5.3: Example of 28 seedlings for each UK225 generation treated with 240 g clodinafop/ha showing the increase of the number of survivors and their vigour. the susceptible population of reference G0 to prosulfocarb applied pre- emergence at the practical field rate of 4,000 gai/ha. They was no significant difference between any of the three UK225 populations tested suggesting that the clodinafop selection had neither reduced nor increased prosulfocarb efficacy.

Dose-responses with the sand bioassay

The sand bioassay showed that prosulfocarb provided less control in terms of visual damage on the first clodinafop-selected progeny UK225.G1 than on the susceptible standard population G0, confirming the observations of Figure 5.4. The estimated resistance factor was 3.27 (95% CI = 2.45 - 4.38) (Tables 5.9 and 5.10, Figure 5.5). Differences in prosulfocarb efficacy were the greatest for rates between 10 and 80 gai/ha. There was no significant difference between the two UK225 progenies studied (RF50 = 0.91, 95% CI = 0.78 - 1.06; Table 5.9). In terms of survival, the predicted values at 160 gai/ha (equivalent to 4,000 gai/ha in the pot assay with TMA soil, see section 3.4.2) showed that there were significantly more survivors for UK225.G1 and UK225.G3 compared to G0 (Table 5.10). Nevertheless, these surviving plants were seriously affected with above 90% visual damage, which corresponds to good levels of control. Interestingly, there was about half as many survivors for UK225.G3 compared to UK225.G1 based on the RF value (0.54, 95% CI = 0.43 - 0.68). This second approach also showed that the recurrent selection with clodinafop had not resulted in a decreased prosulfocarb efficacy from UK225.G1 to UK225.G3.

124 5.3. Results

● ● ●

● 60

20 weed control (visual percentage) weed

G0 UK225.G0 UK225.G1 UK225.G2

Figure 5.4: Boxplot of prosulfocarb efficacies on the susceptible standard L. multiflorum population G0, the field population UK225.G0 and the two subsequent clodinafop-selected progenies obtained, i.e. UK225.G1 and UK225.G2. Prosulfo- carb was applied at 4,000 gai/ha at BBCH03-05 on twelve replicate troughs units. Damages were visually recorded 21 days after application. The median is represented with a solid dot, outliers are represented with a cross, whiskers extend to the minimum and maximum values in the absence of outliers. Kolmogorov-Smirnov tests performed for each pairs showed that the only generation that was significantly less controlled than the standard sensitive population G0 was UK225.G1 (p-value = 0.02).

125 CHAPTER 5. Prosulfocarb vs. ACCase non-target-site based resistance

● ● ● ● 100 ● ● ● ● 1.0 ● ● ● ● ● ● G0 ● ● ● UK225.G1 ● ● UK225.G3 ● ● 80 ● 0.8 ●

● ● ● ● 60 0.6

● ● ●

40 ● 0.4 ● survival (x100)

● ● 20 0.2 ● ● G0 ● ● weed control (visual percentage) weed ● ● ● UK225.G1 ● ● ● ● UK225.G3 ● ● 0 0.0 ● ● ● 1 10 100 1000 1 10 100 1000 prosulfocarb rate in gai/ha prosulfocarb rate in gai/ha

(a) Visual biomass reduction (b) Survival

Figure 5.5: Dose-response curves for the susceptible standard population G0, the ﬁrst clodinafop-selected UK225 progeny (UK225.G1) and the last one (UK225.G3), against a range of prosulfocarb rates. Prosulfocarb was applied at BBCH05-07 in the sand bioassay (Figure 5.6).

Figure 5.6: Sand dose-response from the second experiment. UNT stands for untreated control. Prosulfocarb rates are expressed in gai/ha. The picture was taken 23 DAA. From top row to bottom row: susceptible standard G0; UK225.G1; UK225.G3.

126 5.3. Results

5.3.5 Response to iodosulfuron after the recurrent selection with clodinafop

The initial observation of multiple- or cross-resistance to iodosulfuron in the parental UK225.G0 was confirmed with the dose-response bioassay (see Tables 5.11 and 5.12, Figure 5.7). Fifty-six seedlings out of 84 withstood the application of 10 g iodosulfuron/ha (recommended field rate). These survivors were severely weakened with 81% of biomass reduction visually recorded. In a field situation, with crop competition and possibly sub-optimal growth conditions affecting the weeds, some of these survivors may eventu- ally die or not grow vigorously enough to compromise crop yield. The RF50 between the susceptible standard population and UK225.G0 was greater than 10 for the survival values (Table 5.12). Altogether, this suggested that the biological mechanisms affecting the performance of iodosulfuron had a greater impact at rates lower than the practical field rate. There was no statistical evidence of resistance increase to iodosulfuron from the parental population UK225.G0 to the last clodinafop-selected progeny UK225.G3. Therefore the resistance mechanisms accumulated during the clodinafop recurrent process did not impact on iodosulfuron efficacy. Given the fact that the non-metabolisable herbicides sulfometuron and imazapyr provided full control on UK225.G0 (Table 5.4) and that the survivors at 10 g iodosulfuron/ha were severely affected, non-target-site resistance mechanisms to iodosulfuron were suspected.

127 CHAPTER 5. Prosulfocarb vs. ACCase non-target-site based resistance

● ● ● ● ● ● ● ● ● ● ● 100 ● 1.0 ● ● ● ● ● ● ● ● ● ● ● ● ●

● ● 80 ● 0.8

●

● ● ● 60 0.6

● ● ● ● ● ● ● ● 40 0.4 ● ● ● survival (x100)) ● ● ● G0 G0 ● ● ● ● ● ● ● UK225.G0 UK225.G0 20 ● ● 0.2 ● ● ● ● ● UK225.G1 UK225.G1 ● ● weed control (visual percentage)) weed ● ● UK225.G2 ● UK225.G2 ● ● UK225.G3 ● UK225.G3 0 0.0 ● ● ● ● ● 0.1 1 10 100 1000 0 1 10 100 1000 iodosulfuron rate in gai/ha iodosulfuron rate in gai/ha

(a) Visual biomass reduction (b) Survival

Figure 5.7: Dose-response curves for the susceptible standard population G0, the ﬁeld population UK225.G0 and the three subsequent clodinafop-selected progenies, UK225.G1, UK225.G2 and UK225.G3, against a range of iodosulfuron rates.

128 5.3. Results A. myosuroides 1,729 1,946 2,047 2,125 2,126 Amino acid position(EMBL derived accession from AJ310767) the full length chloroplastic ACCase gene from Nucleotide and amino acid substitutions in the sequenced fragment of the ACCase CT domain of the seven UK225.G0 Wild-type CCT (proline) GAA (glutamic acid) ACA (threonine) TTG (leucine) ATA (isoleucine) UK225.G0.10UK225.G0.24UK225.G0.28 CCTUK225.G0.54 CCT GCTUK225.G0.58 (alanine) CCTUK225.G0.62UK225.G0.75 CCT GRA CCT (glycine) GAA GAA CCT GAA ACA MCA GAA (proline) GAA ACA GAA ACA TTG TTG ACA ACA TTG ACA TTG ATA WTG (methionine) ATA TTG TTG AWA (lysine) ATA ATA ATA ATA Table 5.6: selected plants compared toreported the with wild the type single sequences letter of code: either R G0 = or G 2005 or UK A; M 203. = Heterozygote A mutations or at C; the W nucleotide = level A are or T. The corresponding amino acid is noted in brackets.

129 CHAPTER 5. Prosulfocarb vs. ACCase non-target-site based resistance 4 g 240 . 5.2a Figure in shown presented are are pictures corresponding curves Europe; Dose-response in cereals 0. in control and grass 100 for rate at field 5.3 . fixed recommended Figure respectively the in times were four limits represents asymptotic clodinafop/ha lower and Upper 5.7: Table K2.3-.031(2-7)3 (30-37) 34 (41-47) 44 (71-78) 74 (99-100) 99 (70-90) 80 (326-374) 351 (251-293) 272 -1.80 (3.38-4.18) (96-128) 3.78 112 UK225.G1/UK225.G0 -1.98 (95-123) -3.11 109 UK225.G3/UK225.G0 -1.39 UK225.G3/G0 -1.76 UK225.G0/G0 UK225.G3 UK225.G2 UK225.G1 UK225.G0 G0 siae aaeesfo h o-oitcmdlue ofi h aastfrtevsa sesetatrcoiao application. clodinafop after assessment visual the for set data the fit to used model log-logistic the from parameters Estimated b D0(5C)we oto ecnaea 4 ldnfph F0(95%CI) RF50 clodinafop/ha g 240 at percentage control weed (95%CI) ED50 .2(0.83-1.23) 1.02 (2.75-3.68) 3.21 3(81-104) 93 9(24-34) 29

130 5.3. Results 60 (45-80) 271 (203-361) 4.48 (3.60-5.36) 1.39 (1.00-1.72) LD50 (95%CI) survival percentage at 240 g clodinafop/ha RF50 (95%CI) b Estimated parameters from the log-logistic model used to fit the data set for the mortality assessment after clodinafop UK225.G3/G0 G0UK225.G0UK225.G1UK225.G2UK225.G3UK225.G0/G0 2.21 2.21UK225.G3/UK225.G0 2.21 358 2.21UK225.G1/UK225.G0 (282-434) 498 2.21 (401-596) 5.51 (5.19-6.74) 721 1,605 (507-936) (1,558-1,651) 0.02 71 (0.001-0.05) (65-77) 84 99 (78-89) (98-99) 92 (89-95) Table 5.8: application. Upper and lower240 asymptotic g limits clodinafop/ha were respectively representsshown fixed four in at times Figure 100 the5.3 . and recommended 0. field Dose-response rate curves for are grass presented control in in Figure cereals5.2b . in Europe; corresponding pictures are

131 CHAPTER 5. Prosulfocarb vs. ACCase non-target-site based resistance plcto sn iasy.Upradlwraypoi iiswr epcieyfie t10ad0 oersos uvsaepresented are curves Dose-response 0. and 100 at fixed respectively 5.6 . were and limits 5.5a asymptotic lower Figure and in Upper bioassay). (sand application 5.9: Table K2.3-.12 2-5 5(92-98) 95 (99-100) (91-97) 99 94 (8.45-11) (25-35) 9.65 29 (27-38) 32 -1.71 -1.71 -1.71 UK225.G1/UK225.G3 UK225.G3/G0 UK225.G1/G0 UK225.G3 UK225.G1 G0 siae aaeesfo h o-oitcmdlue ofi h aastfrtevsa sesetatrprosulfocarb after assessment visual the for set data the fit to used model log-logistic the from parameters Estimated b D0(5C)we oto ecnaea 6 rsloabh F0(95%CI) RF50 prosulfocarb/ha g 160 at percentage control weed (95%CI) ED50 .1(0.78-1.06) 0.91 (2.21-4.04) 2.99 (2.45-4.38) 3.27

132 5.3. Results 4.55 (3.13-6.61) 2.46 (1.69-3.59) LD50 (95%CI) survival percentage at 160 g prosulfocarb/ha RF50 (95%CI) b Estimated parameters from the log-logistic model used to ﬁt the data set for the mortality assessment after prosulfocarb G0UK225.G1UK225.G3UK225.G1/G0 UK225.G3/G0 UK225.G1/UK225.G3 1.71 1.71 97 1.71 (77-123) 52 (41-67) 21 (18-25) 30 (21-39) 13 3.08 (7.32-19) (1.32-4.85) 0.54 (0.43-0.68) . Table 5.10: application (sand bioassay). Upperin and Figures lower asymptotic5.5b limitsand were5.6 respectively ﬁxed at 100 and 0. Dose-response curves are presented

133 CHAPTER 5. Prosulfocarb vs. ACCase non-target-site based resistance 5.7a . Figure in cereals. presented in are curves control grass Dose-response for 0. rate and field 100 recommended at the fixed respectively is were iodosulfuron/ha limits g asymptotic 10 lower and Upper application. 5.11: Table K2.3-.226 24-.6 0(88-92) 90 (91-95) 93 (99-100) 99 (87-90) 88 (75-98) 87 (2.40-2.86) 2.62 (1.77-2.20) -1.62 1.97 (0.39-0.53) 0.45 (2.84-3.33) -1.61 3.07 -2.46 (2.29-2.87) UK225.G3/UK225.G0 -1.70 2.54 UK225.G3/G0 -1.36 UK225.G0/G0 UK225.G3 UK225.G2 UK225.G1 UK225.G0 G0 siae aaeesfo h o-oitcmdlue ofi h aastfrtevsa sesetatriodosulfuron after assessment visual the for set data the fit to used model log-logistic the from parameters Estimated b D0(5C)we oto ecnaea 0gidsluo/aR5 (95%CI) RF50 iodosulfuron/ha g 10 at percentage control weed (95%CI) ED50 1.03(0.89-1.18) 5.72(4.82-6.78) 5.54(4.63-6.63)

134 5.3. Results 11 (6-20) 14 (8-26) LD50 (95%CI) survival percentage at 10 g iodosulfuron/ha RF50 (95%CI) b Estimated parameters from the log-logistic model used to fit the data set for the mortality assessment after iodosulfuron UK225.G3/G0 UK225.G3/UK225.G0 1.31(0.92-1.87) G0UK225.G0UK225.G1UK225.G2UK225.G3UK225.G0/G0 1.62 1.62 1.62 18 (12-25) 1.62 1.60(1.21-2.10) 19 (13-29) 1.62 16 (11-23) 23 (16-34) 4.88(1.21-8.55) 71 (70-81) 74 (62-86) 68 (54-83) 80 (69-90) Table 5.12: application. Upper and lower10 asymptotic g limits iodosulfuron/ha were respectively is fixed the at recommended 100 field and rate 0. for Dose-response grass curves control are in presented cereals. in Figure 5.7b .

135 CHAPTER 5. Prosulfocarb vs. ACCase non-target-site based resistance

5.4 Discussion

This study aimed to evaluate the resistance patterns between clodinafop, prosulfocarb and iodosulfuron when high and increasing levels of non-target- site based resistance to clodinafop were selected in L. multiflorum progenies. Over three cycles of recurrent selection, the resistance levels to clodinafop were increased by about 4-fold from the parental population UK225.G0 to the last progeny UK225.G3 (visual damages and survival) (Tables 5.7, 5.8 and Figure 5.2). UK225.G0 was as sensitive as the susceptible standard population when treated with prosulfocarb PRE at 4,000 gai/ha (Figure 5.4). Likewise, the two successive UK225 progenies were as well controlled as the parental population. The sand bioassay pointed out differences between the first clodinafop-selected progeny UK225.G1 and the last one UK225.G3 in terms of survivors since there was half as many survivors for UK225.G3 compared to UK225.G1 (Table 5.10 and Figure 5.5b). Finally, there was no resistance increase to iodosulfuron (Tables 5.11, 5.12 and Figure 5.7).

The underlying mechanisms of resistance to clodinafop are likely to be polygenic

The dose-response curves for the last two progenies were not merged suggesting that resistance to clodinafop has been increased but has not reached its maximum yet (Figure 5.2). This demonstrated the scalable aspect of the non-target-site based resistance mechanisms as opposed to target-site resistance, i.e. increased levels of resistance after each generation. Assum- ing that the underlying resistance mechanisms to clodinafop are mediated by the fate of the toxicant via degradation enzymes, the genetic control of resistance is most likely to be polygenic. Inheritance studies involving controlled paring with UK225.G0 survivors and known susceptible population(s) may help to determine the minimum number of loci involved in clodinafop-resistance. The starting point for such studies is crucial and would greatly inﬂuence the outcome highlighting the danger of generalisa- tion. In the very ﬁrst experiment, the lowest rate at which all susceptible plants were killed was 30 g clodinafop/ha (Figure 5.1). At this rate, all the UK225.G0 plants survived and dead plants were only observed from 480 gai/ha onwards. Inheritance studies carried out with UK225.G0 survivors at 30 gai/ha may lead to a lower number of loci compared to survivors at

136 5.4. Discussion

480gai/ha. Besides, high rates, i.e. greater than 10 times the lowest rate required to kill the susceptible standard population, are most likely to select for homozygous resistant traits due to higher selection pressure. Another approach would be to conduct crosses at segregating rates between UK225.G0 individuals exhibiting a sensitive and a resistant phenotype based on clone proﬁling.

Investigations on ecological costs associated with clodinafop-resistance are required to better understand its evolution

During the course of the recurrent selection process, it seemed that biomass, seed production and viability for the UK225 progenies were not different from any herbicide-sensitive populations. These parameters were not assessed and only relied on visual observations. In a cropping environment with crop competition, non-optimal growth conditions, limited nu- trient resources and without herbicide selection pressure, the growth and reproductive behaviour of the UK225 progenies may be affected. Most of the fitness studies associated with resistance to ACCase inhibitors were conducted on target-site resistant populations since the production of wild- type and homozygote mutants sublines was easily achievable [reviewed in 123]. Fitness costs seemed to be specific to the amino-acid substitution studied and were recessive for D2078G [176]. Only one study provided insights on fitness costs associated with non-target-site based resistance using the multiple herbicide resistant L. rigidum population SLR31 [177]. The authors showed the impaired ability of the resistant sub-population to compete for resources. However, resistance in SLR31 is more likely to have been selected by different herbicide chemistries as demonstrated by its multiple- herbicide resistance profile (see Chapter1). Thus, UK225 progenies represent a unique opportunity to unravel ecological costs specifically associated with ACCase resistance on a non-target-site basis. Comparing the four progenies together would provide indications on the evolutionary profile of non-target-site based resistance to clodinafop.

137 CHAPTER 5. Prosulfocarb vs. ACCase non-target-site based resistance

Resistance to clodinafop may have induced negative cross-resistance eﬀects to prosulfocarb

It was hypothesised in Chapter4 that cross-resistance between clodinafop and prosulfocarb would arise provided the fact the resistance levels to clodinafop were high enough. It was the case in the present study with a shift greater than 20-fold between the susceptible population of reference G0 and the parental population UK225.G0 (Tables 5.7 and 5.8). However, there was no evidence of cross-resistance with prosulfocarb for UK225.G0. The sand dose-response assay showed a significant shift towards sensitivity from UK225.G1 to UK225.G3 at the survival level (Table 5.10 and Figure 5.5b). More cycles of clodinafop recurrent selection are required to confirm whether the tendency observed corresponds to fitness costs associated with clodinafop resistance that would results in negative-cross resistance effects or only denotes natural variability within the progenies obtained.

Putative importance of P450s for negative cross-resistance eﬀects

The constitutive overexpression of P450 genes in resistant insect strains as measured by mRNA levels is a well documented mechanism of resistance [reviewed in 178]. The metabolic attack on clodinafop and prosulfocarb starts with a monooxygenation [38, 156]. The speciﬁcity of the P450 enzyme(s) involved in clodinafop metabolism is unknown. Assuming that substrate speciﬁcity is not stringent, and under the hypothesis of overexpression, these P450s may therefore convert prosulfocarb more quickly into its active form in UK225.G3 than in UK225.G1. This would virtually increase the concentration of active prosulfocarb in the plant at a given time point, thus provoking higher mortality.

Role of safener in clodinafop resistance evolution

Safeners are compounds that protect the grass crop from herbicide injury [33]. Many post-emergence graminicides are now co-formulated with a safening molecule. The hypothesis that safeners select for herbicide resistance is supported by the evidence that they enhance herbicide tolerance in target weed species via the overproduction of degrading enzymes [100]. Cloquintocet-mexyl, the safener partner of clodinafop, has been shown to enhance the activity of O-GTs, P450s, GST isozymes and ABC transport-

138 5.4. Discussion ers in barley and wheat [156, 179–182]. After being hydroxylated by P450s, clodinafop is conjugated to plant sugars in wheat via O-GTs [156]. As- suming a similar pathway in the UK225 progenies, it can be hypothesised that cloquintocet-mexyl had selected for increased activity of these spe- ciﬁc O-GTs. Although very restrictive, this is corroborated by the fact that there was no resistance increase to iodosulfuron (Tables 5.11, 5.12 and Figure 5.7). The safener partner of iodosulfuron is mefenpyr-diethyl and iodosulfuron has not been shown to be degraded via O-GTs. The role of safeners in clodinafop resistance evolution could be ascertained by conduct- ing comparative recurrent selection at the whole plant level with safeners only and the corresponding unsafened herbicide formulations.

Cross-resistance between ACCase and ALS inhibitors is not systematic

Many recurrent selection experiments have reported cross-resistance patterns with dissimilar herbicides and especially with the pair ACCase/ALS inhibitors [e.g. 134, 135]. The present study showed that the levels of cross- resistance to iodosulfuron were not significantly modified in either direction from the original parental population to the last selected progeny demon- strating that cross-resistance evolution is not systematic. Other ALS inhibitors such as chlorsulfuron should be studied in order to complement the existing resistance profiles.

Future research directions

The only documented cases of resistance to PSII inhibitors and more particularly to chlorotoluron in Lolium spp. and A. myosuroides populations involved non-target-site based mechanisms [183–185]. The degradation route of chlorotoluron in these two species is based on a ring-hydroxylation followed by glucose conjugation that is likely to require P450 enzymes [184, 185]. Genetic control studies also suggested that two nuclear genes encoded for chlorotoluron resistance in A. myosuroides populations [cited in 186]. Chlorotoluron was widely used in Europe. Consequently, similar detailed investigations should be conducted with ryegrass populations spe- ciﬁcally resistant to chlorotoluron in order to assess the danger of further se- lecting resistance to prosulfocarb with pre-existing metabolic mechanism(s)

139 CHAPTER 5. Prosulfocarb vs. ACCase non-target-site based resistance capable of aﬀecting its eﬃcacy.

5.5 Conclusions and Perspectives

This study showed that high and increasing levels of non-target-site based resistance to clodinafop in selected L. multiflorum progenies neither increased resistance levels to the dissimilar herbicide iodosulfuron nor reduced prosulfocarb efficacy. Conversely, small evidence of negative cross-resistance was observed suggesting that prosulfocarb may efficiently contribute to overcoming ACCase and ALS resistance in grass weeds. Outdoors studies are required in order to confirm that the observed effects are of agronomic importance in a field situation. A subsequent aspect of negative cross-resistance with prosulfocarb is investigated in Chapter6 with pure target-site resistant sublines.

140 6 Assessment of negative cross-resistance with prosulfocarb and other lipid synthesis inhibitors on wild and ACCase target site resistant Lolium multiﬂorum Lam. sublines

Negative cross-resistance (NCR) also termed super/hyper-sensitivity arises in a given population when a genetic factor that mediates resistance to one toxicant increases sensitivity to a second one [56]. It is seen as a potentially interesting feature to delay or overcome the evolution of resistance since there is scope for the intelligent pairing of such compounds [187, 188]. NCR has been reported for a wide range of molecules including those active against insects, weeds, fungi and bacteria [56, 189–191]. However, commercial successes of such strategies are rare. One of the few examples was the introduction of the carbendazim/diethofencarb mixture to control grey mould in French vineyards [192, 193]. Diethofencarb controlled the carbendazim- resistant strains without aﬀecting the carbendazim-sensitive ones.

Herbicide-NCR effects were first reported in vitro by Oettmeier et al. [194]. Phenolic herbicides had significantly higher activities on atrazine- resistant Amaranthus retroflexus L. plastids compared to the sensitive ones. It is now well established that the binding properties of phenolic herbicides are modified by the S264G substitution in the psbA gene that confer target-site resistance to triazines [195, 196]. The few cases of herbicide-NCR

141 CHAPTER 6. Negative cross-resistance that have been published afterwards were based on laboratory engineered resistance, e.g. site-directed mutagenesis on an less agronomically relevant weed, i.e. Hydrilla verticillata (L.f.) Royle [197] or interspecific hybrid- ization to transfer trifluralin resistance genes from Setaria viridis (L.) P. Beauv. into Setaria italica (L.) P. Beauv. [198]. Negative cross-resistance was also demonstrated with in vitro measurements or Petri-dish assays that rely on potentially transient herbicide effects such as impaired coleoptile elongation after three days of incubation [198, 199], and/or populations that do not share the same genetic background since their points of origin were spatially separated to the order of several kilometres [200].

In order to fully appraise the potential of herbicide-NCR as a strategy to control herbicide-resistant weed populations, it is of critical importance to simulate field conditions as far as possible since in vitro observations may not be directly transposable to the field [110]. Studies must also involve agronomically relevant weed populations having well characterised resistance mechanisms or use weed populations with a genetically controlled background. These measures will determine whether the NCR effects observed are mediated by the genetic factor(s) that confer resistance and are not the result of natural variability between populations. The only study meeting more or less these criteria was performed by Gadamski et al. [187]. The authors showed that 11 herbicides exerted significant negative cross-resistance against atrazine-resistant biotypes of Echinochloa crus-galli (L.) P. Beauv. and Conyza canadensis (L.) Cronquist.

Rather than blindly screen for active ingredients that may result in NCR effects, a more rational approach may be to concentrate on impaired physiological functions associated with herbicide resistance alleles. Of interest, the Gly-2078 and Arg-2088 mutant alleles have been reported to result in lower specific ACCase activities compared to the wild type enzymes extracted from Lolium rigidum Gaud. populations [89, 201]. This may impose a fitness penalty at the whole plant level as indicated by field studies carried out in the absence of herbicide pressure on Alopecurus myosuroides Huds. [176]. In this study, the GG2078 plants displayed a significant reduction in biomass (42%), height (6%) and seed production (36%) compared to the wild-type population [176].

142 Chloroplastic ACCase catalyses the first committed step in the biosynthesis of plant fatty acids. It produces malonyl-CoA which is the source of carbon for chain elongation performed by the chloroplastic fatty acid synthase complex. The resulting acyl-CoAs are exported into the endoplasmic reticulum to be further elongated by the membrane-bound elongases that are the suspected biological targets of prosulfocarb (thiocarbamate herbicides) and flufenacet (K3) (Figure 6.1 and Chapter1). The concentration of malonyl-CoA is rate limiting in fatty acid biosynthesis [202]. The ACCase is therefore the major regulation site of this pathway. Consequently, a reduced ACCase specific activity endowed by a target-site mutation that confer resistance to ACCase inhibitors result in lower amounts of acyl-CoAs produced during a given period of time as compared to the wild-type. It may therefore alter the production of VLCFAs. Lower amounts of prosulfocarb may therefore be needed to effectively control homozygote mutant compared to the wild-type sublines. This is also supported by the fact that herbicides acting at different targets in the same metabolic pathway have been shown to act synergistically [203]. Finally, the kinetics, i.e. palmitic acid and stearic acid production and their transfer vs. herbicide absorption and translocation are important factors but cannot be directly assessed in the current herbicide whole plant assays.

In this study, the putative negative cross-resistance effects of prosulfocarb and other lipid synthesis inhibitors were investigated on wild and ACCase target-site resistant L. multiflorum sublines. The I1781L substitution was used as a positive control since (i) no fitness cost has been reported for a L. rigidum biotype [204], (ii) a LL1781 S. italica (L.) P. Beauv. line displayed a fitness advantage over the wild-type [205] and (iii) the 1781-Leucine allele is naturally present in Poa annua L. and Festuca rubra L. species [82]. Three other mutations were studied, namely W1999S, D2078G and C2088R.

143 CHAPTER 6. Negative cross-resistance

acyl-CoA (n)

palmitic acid 16:0 + malonyl-CoA

stearic acid 18:0 KCS KCR Elongases HCD Fatty Acid Synthase ECR

malonyl-CoA ER acyl-CoA (n+2)

triacylglycerol chloroplast ACCase epicuticular waxes acetyl-CoA suberin phospohlipids cytosol sphingolipids

epidermis cell of a grass weed

Figure 6.1: Schematic representation of the biosynthesis of very long chain fatty acids. VLCFAs are elongated from the saturated 16- or 18-carbon fatty acids, i.e. palmitic and stearic acids. These fatty acids are produced by the chloroplastic fatty acid synthase complex and ultimately activated to CoA esters by a long- chain acyl-CoA synthetase in order to cross the plastid membrane. The endoplasmic reticulum membrane-bound multi-protein complex named elongases catalyse the four successive enzymatic reactions leading to the elongated molecule that is incorporated into diﬀerent lipid pools, e.g. epicuticular waxes. KCS: 3-keto-acyl- CoA synthase; KCR:β-ketoacyl-CoA reductase; HCD: β-hydroxyacyl-CoA; ECR: enoyl-CoA reductase.

6.1 Materials and Methods

6.1.1 Production of homozygote wild-type and homozygote mutant sublines for four ACCase mutations

I1781L

The I1781L substitution was detected in sample 2006 UK 217 from the Jealott’s Hill seed bank during resistance monitoring work (Dr. Shiv Shankhar Kaundun and Richard Dale, data not shown). The population was sensitive to ALS inhibitors (data not shown). A homozygote wild-type line (II1781) and a homozygote mutant (LL1781) were produced from this population based on molecular analyses. In this respect, 190 seedlings from population

144 6.1. Materials and Methods

2006 UK 217 were individually grown in 3” pots ﬁlled with JIP compost. Leaf fragments were sampled at the BBCH12 stage. DNA extraction was conducted as described in the General Materials and Methods chapter (see section 2.2) using the automatic platform Biomek FX Workstation. Poly- morphism at position 1781 was identiﬁed using the 1781 dCAPS assay as previsouly described (see section 2.2.5). Homozygote mutants and homozygote wild-type individuals were selected to produce two batches of seeds for the trait of interest. Seed batches were produced initially at Jealott’s Hill in 2008 in two isolated growth chambers. In the autumn, 61g of LL1781 and 1.1g of II1781 seeds were harvested. A larger-scale seed production was then undertaken by Herbiseed (Twyford, UK) as described in section 2.1.11. This process allowed the production of 574 g of LL1781 and 172 g of II1781 seeds.

W1999S

The W1999S substitution was detected in sample 2006 UK 211 from the Jealott’s Hill seed bank (Dr. Shiv Shankhar Kaundun and Richard Dale, data not shown). The population showed minor levels of resistance to the ALS inhibitor iodosulfuron, most probably due to non-target-site based resistance mechanisms (data not shown). Purification into a homozygote wild-type line (WW1999) and a homozygote mutant (SS1999) population was carried out following the procedure aforementioned. Ninety-six seedlings from population 2006 UK 211 were individually grown in 3” pots filled with JIP compost. Polymorphism at position 1999 was identified using the 1999 dCAPS assay described in section 2.2.5. Initial seed production was performed at Jealott’s Hill and resulted in the production of 64 g of SS1999 and 3 g of WW1999. Larger-scale seed production by Herbiseed was performed for WW1999 only and resulted in the production of 662 g of seeds.

D2078G

The D2078G substitution was detected previously in sample UK24 in which high levels of non-target-site based resistance to diclofop-methyl was also reported [91]. This population showed low levels of resistance to ALS inhibitors (data not shown). The frequency of the homozygote mutants in UK24 was too low, i.e. approx. 5% (data not shown) to allow a direct dCAPS

145 CHAPTER 6. Negative cross-resistance analysis. Consequently, 777 UK24 individuals were grown in 3” pots containing JIP compost and treated with pinoxaden at 100 gai/ha at BBCH12. Thirty-five UK24 individuals were grown in a similar manner but left untreated. Forty-five survivors were recorded 26 days after pinoxaden application and sampled for DNA analyses alongside the 35 untreated plants. Polymorphism at position 2078 was then determined with the 2078 dCAPS assay described in section 2.2.5. Sixteen individuals out of the 45 survivors were homozygous mutants, which represented 35% of the survivors from the pinoxaden treatment. There were only three homozygous mutants out of the 35 untreated plants. In total, 22 individuals were fingerprinted as being DD2078 and 19 as GG2078. Initial seed production was undertaken at Jealott’s Hill for DD2078 and resulted in the production of 8 g of seeds. The 19 GG2078 mutant individuals were repotted, trimmed and fertilised as required. Subsequent seed bulking by Herbiseed yielded 545 g of DD2078 and 108 g of GG2078.

C2088R

Subpopulations CC2088 and RR2088 were produced by Dr. Shiv Shankhar Kaundun from a parental population containing the C2088R following a more or less similar methodology (molecular analyses followed by greenhouse seed production at Jealott’s Hill). The parental population was free from any non-target-site based resistance mechanisms that could aﬀect either ACCase or ALS inhibitors (Shiv Shankhar Kaundun, personal communication).

6.1.2 Prosulfocarb dose-responses

Herbicide dose-response assays were carried out for each and every pair of pure homozygote wild-type (WT) and pure homozygote mutant (M) lines. The susceptible standard L. multiﬂorum population G0 was included for comparison. Seeds were pre-germinated onto agarose as described in section 2.1.6. Twenty-eight G0 pre-germinated seeds were individually transplanted into 3” pots ﬁlled with TMA soil for each treatment including the untreated control. Prosulfocarb was applied at 0; 125; 250; 500; 1,000; 2,000, 4,000 and 8,000 gai/ha on respectively 28, 28, 56, 56, 84, 112 and 56 pre-germinated seeds of both the WT and the M populations. The smallest

146 6.1. Materials and Methods manageable experimental unit consisted of a tray of twenty-eight 3” pots. Each set of experiment was fully randomized within treatment. Twenty-one days after application, the number of plants that emerged was counted and survival was recorded.

6.1.3 Detailed study for D2078G

In order to assess the negative-cross resistance effects of prosulfocarb and other fatty acid synthesis inhibitors on ACCase target-site resistant lines, a more detailed study was conducted for the D2078G substitution. This pair was chosen based on the fitness penalty reported elsewhere at the enzyme and the whole plant levels [89, 176]. Dose-responses were then conducted with the DD2078 and GG2078 lines alongside the susceptible standard population G0. Two thiocarbamate herbicides and four representatives of the HRAC group K3 were tested as detailed in Table 6.1. A seed measure was sown for each population in punnets filled with sand. Three replicate punnets were produced per treatment including the untreated control and each punnet contained the three populations. Herbicides were sprayed at BBCH03-05. The experiments were conducted a total of three times. Weed control was visually recorded 21 days after application as percentage of biomass reduction compared to the untreated controls.

Table 6.1: List of herbicides applied on DD2078 and GG2078 sublines as well as the susceptible standard population G0 in the sand bioassay.

Active ingredient HRAC group Rate in gai/ha prosulfocarb N 0; 20; 40; 80; 160; 320; 640 and 1,000 EPTC N 15; 30; 60; 120; 240; and 720 pyroxasulfone K3 0.1; 0.2; 0.5; 1; 2; 10 and 40 S-metolachlor K3 2; 5; 10; 30; 90; 270 and 810 ﬂufenacet K3 1; 2; 5; 15; 45; 135 and 405 napropamide K3 5; 15; 30; 60; 120; 360 and 1,080

147 CHAPTER 6. Negative cross-resistance

6.1.4 Data analysis

Prosulfocarb dose-responses

Plant survival based on the number of seedlings that emerged in the untreated pre-germinated units was calculated as described in Equation 6.1.

For each and every population tested, Pij is the survival for population j at prosulfocarb rate i;(nalive)ij the number of survivors for population j at rate i and (ntested)UNT j, the number of individuals transplanted for the untreated control for population j, this value is constant across all set of experiments and populations and was set at 28. Plant survival was then ﬁtted to a non-linear log-logistic regression model as detailed in section 2.1.12

(nalive)ij(ntested)UNT j Pij = (6.1) (nalive)UNT j(ntested)ij

Detailed study for D2078G

The visual percentage of weed control for the DD2078 and GG2078 pure lines and the suceptible population G0 was ﬁtted to a non-linear log-logistic regression model as detailed in section 2.1.12. Datasets from repeated experiments were pooled.

6.2 Results

6.2.1 Prosulfocarb dose-responses with I1781L, W1999S, D2078G and C2088R sublines

Significant negative cross-resistance (NCR) was only observed for the pair RR2088/CC2088 (Table 6.2). Less than half the prosulfocarb concentration was required to achieve 50% of emergence reduction of the mutant RR2088 as compared to the wild-type CC2088 (RF50 = 0.5, 95%CI = 0.17-0.84). It is noteworthy that although not significant, the RF50 values for the three other pairs were less than 1 suggesting that minor biological mechanisms may account for a small negative cross-resistance effect. There were minimal indications of the NCR effect at the field rate of 4,000 prosulfocarb/ha. Variability in emergence control compared to the susceptible standard population G0 was also observed. In this respect, there was a consistent shift to the left for the 1999 and 2088 pairs indicating that

148 6.2. Results both the wild-type and the mutant sublines required less prosulfocarb to achieve the same level of control as compared to G0. This shift was statistically significant for the two mutant lines, i.e. RF50 SS1999/G0 = 0.6 (95%CI = 0.10-0.71) and RF50 RR2088/G0 = 0.31 (95%CI = 0.10-0.51). In contrast, both the mutant and the wild-type for the 1781 pair were significantly shifted to the right indicating that they were less controlled than G0. Interestingly, the wild-type DD2078 was somewhat less controlled than G0 while the mutant GG2078 was more controlled than G0. However, these differences were not statistically significant. In general the effects observed were more significant at low prosulfocarb rates than at 4,000 gai/ha. The II1781-LL1781 pair was considered as sensitive as G0 to prosulfocarb with respect to the predicted percentage of emergence reduction at 4,000 gai/ha.

To enable direct comparisons between the four pairs of mutant and wild- type populations that were assayed at different times, the prosulfocarb rates that resulted in 50% emergence reduction for G0 was then arbitrarily set at 1. Out of the 28 estimated RF50 values, 14 were significantly different from 1 showing natural variability between the tested populations. The largest difference in response was observed for II1781/RR2088 with an RF50 estimated at 4.42 (95%CI = 2.69-7.24). For the four wild-type populations, the largest shift was for II1781/CC2088, which was estimated at 2.39 (95%CI = 1.28-4.44), while CC2088 and DD2078 gave comparable responses (CC2088/DD2078 = 0.97, 95%CI = 0.49-1.94). Finally, for the four homozygote mutant populations, the largest difference was recorded for LL1781/RR2088 which was estimated at 4.09 (95%CI = 2.56-6.54), while SS1999 and GG2078 gave comparable responses (GG2078/SS1999 = 1.15, 95%CI = 0.67-1.99).

149 CHAPTER 6. Negative cross-resistance

R08 n h idtp I18 rC28)aantarneo rsloabrates. prosulfocarb of range a against CC2088) or (II1781 wild-type the and RR2088) 6.2: Figure emergence 0.0 0.2 0.4 0.6 0.8 1.0 0 ● ● ● oersos uvs(mrec)frtessetbesadr ouainG,tehmzgu uatsbie(L71or (LL1781 subline mutant homozygous the G0, population standard susceptible the for (emergence) curves Dose-response G0 LL1781 II1781 prosulfocarb rate in gai/ha 100 ● ● (a) ● ● ● I1781L ● ● ● 1000 ● ● ● ● ● ● ● ● ● 10000 ● ● ●

emergence 0.0 0.2 0.4 0.6 0.8 1.0 0 ● ● ● G0 RR2088 CC2088 prosulfocarb rate in gai/ha 100 ● ● ● (b) ● ● ● C2088R ● ● ● 1000 ● ● ● ● ● ● ● ● ● 10000 ● ● ●

150 6.2. Results Predicted percentage of emergence reduction at 4,000 g prosulfocarb/ha the slope at the inﬂexion point. b the asymptotic upper limit and d ED50 (95%CI) RF50 (95%CI) c d b the asymptotic lower limit, c G0 0.1815 1 1.89 997 (773-1221) 24 (17-31) G0 0.2962 1 2.07 3817 (1805-5829) 63 (48-78) G0 0.083 1 3.22G0 2136 (1584-2688) 0.2692 1 1.10 1463 (708-2218) 19 (1.54-36) 25 (26-64) Parameters and estimated/predicted values for the prosulfocarb dose-response experiments carried out with the pure homo- II1781 0.1815 1 1.71 1624 (1234-2015) 33 (23-42) SS1999 0.2962 1 1.96 1560 (724-2397) 39 (17-61) Subline LL1781 0.1815 1 1.66 1504 (1140-1871) 32 (23-41) CC2088 0.2692 1 1.05 895 (423-1366) 39 (27-52) RR2088 0.2692 1 1.79 455 (276-634) 28 (25-31) DD2078 0.083 1 0.95 2300 (1135-3466) 42 (23-72) GG2078 0.083 1 1.33 1577 (945-2210) 29 (16-41) WW1999 0.2962 1 1.80 2535 (1038-4033) 51 (31-71) II1781/G0 1.62 (1.09-2.16) SS1999/G0 0.40 (0.10-0.71) LL1781/G0 1.51 (1.01-2.00) CC2088/G0 0.61 (0.16-1.06) RR2088/G0 0.31 (0.10-0.51) DD2078/G0 1.07 (0.46-1.68) GG2078/G0 0.73 (0.38-1.09) WW1999/G0 0.66 (0.13-1.19) LL1781/II1781 0.92 (0.61-1.24) RR2088/CC2088 0.50 (0.17-0.84) GG2078/DD2078 0.68 (0.24-1.12) SS1999/WW1999 0.61 (0.12-1.10) Table 6.2: zygous wild-type and homozygousgene. mutant sublines Population G0 for was substitutionsand included at the in position percentage each of 1781, experiment emergencein 1999, as was section 2078 the calculated2.1.12 and susceptible afterwith 2088 standard a of population. 21 DAA the Prosulfocarb assessment. ACCase was chloroplastic The sprayed non-linear at log-logistic BBCH03-05 regression model was as detailed

151 CHAPTER 6. Negative cross-resistance

6.2.2 Detailed study for D2078G

Although the C2088R pair showed significant negative cross-resistance effect in the preliminary experiment there were not enough seeds to conduct a more detailed survey with other lipid synthesis inhibitors. The second most interesting pair was the D2078G substitution for which (i) DD2078 was slightly less controlled than the GG2078 subline and (ii) the predicted percentage of emergence reduction at 4,000 g prosulfocarb/ha was only 29%. Dose-responses with six different compounds that inhibit lipid synthesis were performed. The estimated parameters are reported in Table 6.3. The dose-responses for prosulfocarb and napropamide are shown on Figures 6.3a and 6.3b. Significant negative-cross resistance effects were reported for the two thiocarbamates tested, i.e. prosulfocarb and EPTC (Table 6.3). The three K3 compounds, namely pyroxasulfone, S-metolachlor and flufenacet showed evidence of negative cross-resistance but without statistical significance. Napropamide stood out as being the only compound for which the mutant type (GG2078) was less controlled than the corresponding wild-type (DD2078). However, this difference was not statistically significant (RF50 = 1.14, 95%CI = 0.73-1.55). It was also the only compound for which the wild type was significantly more controlled than the susceptible standard population G0. An attempt at hierarchical classification was made for the six compounds tested based on the RF50 ratios (Figure 6.4). It confirmed that the thiocarbamates elicited a different plant response from the K3 representatives. Within this class, four different chemical families were tested according to the HRAC classification i.e. oxyacetamide for flufenacet; chloroacetamides for S-metolachlor; acetamide for napropamide and ‘other’ for pyroxasulfone. Flufenacet and pyroxasulfone had similar patterns while being different from S-metolachlor and napropamide. The functional amide group in flufenacet, S-metolachlor and napropamide did not result in a consistent response as these three compounds had very dissimilar profiles suggesting the importance of the residues in the structure-activity-relationship patterns.

152 6.2. Results ● ● ● 1000 DD2078 GG2078 G0 ● ● ● ● ● ● ● ● ● 100 ● ● ● ● ● ● (b) ● ● ● 10 napropamide rate in gai/ha napropamide rate ● ● 1

80 60 40 20 100 percentage) (visual control weed ● ● ● 1000 ● ● ● DD2078 GG2078 G0 ● ● ● ● ● ● ● ● ● ● ● 100 ● ● ● ● (a) ● ● ● ● ● ● 10 prosulfocarb rate in gai/ha rate prosulfocarb Dose-response curves (visual biomass reduction) obtained in the sand bioassay for the susceptible standard population G0, 1

80 60 40 20 100 percentage) (visual control weed Figure 6.3: the homozygous mutant subline GG2078, the wild-type subline DD2078 against a range of prosulfocarb and napropamide rates.

153 CHAPTER 6. Negative cross-resistance n h ecnaevsa ims euto a eodd2 asatrapiain h o-ierlglgsi ersinmdlwas model regression log-logistic non-linear The 6.4 . Table application. in BBCH03-05 after reported at are days with sprayed factors 21 were 2.1.12 resistance recorded Herbicides section Estimated was G0. in reduction population detailed standard biomass susceptible as visual the percentage and the GG2078 and subline mutant homozygous the DD2078, 6.3: Table cieigein RCgroup HRAC ingredient Active yoaufn 3010-.310 08-.1 .0(.811)10 (0.73-1.38) 1.01 (0.58-1.11) 0.80 (0.83-1.31) 1.04 -1.23 100 0 K3 pyroxasulfone -eoaho 3010-.71 1-2 6(21)1 (9.34-15) 12 (12-19) 16 (16-22) 19 -1.37 100 0 K3 S-metolachlor arpmd 3010-.73 3-6 7(64)7 (70-83) 76 (26-48) 37 (30-36) 32 -1.47 100 0 K3 napropamide rsloabN010-.86 6-4 7(24)6 (58-80) 67 (32-42) 37 (61-74) 67 -2.18 100 0 N prosulfocarb ueae 309 38 15 .0(.675)43 32-.5 .6(4.14-7.22) 5.46 (3.29-5.75) 4.35 (4.96-7.51) 6.10 -1.56 89 93 90 0 K3 flufenacet aaeesadetmtdvle o h oersos xeiet are u ihtehmzgu idtp subline wild-type homozygous the with out carried experiments dose-response the for values estimated and Parameters PCN010-.712(816 2(48)8 (63-97) 80 (54-89) 72 (88-116) 102 -2.17 100 0 N EPTC c h smttclwrlimit, lower asymptotic the c D08G27 0D27 G08G0 GG2078 DD2078 G0 GG2078 DD2078 d d h smttcuprlmtand limit upper asymptotic the b b D0(95%CI) ED50 h lp tteiflxo point. inflexion the at slope the

154 6.2. Results RF50 (95%CI) DD2078/G0 GG2078/G0 GG2078/DD2078 EPTC N 1.27 (0.85-1.70) 0.89 (0.73-1.05) 0.69 (0.44-0.95) ﬂufenacet K3 1.11 (0.71-1.74) 0.79 (0.60-1.05) 0.71 (0.45-1.11) prosulfocarb N 1.00 (0.81-1.24) 0.55 (0.48-0.62) 0.55 (0.44-0.67) napropamide K3 0.42 (0.33-0.50) 0.48 (0.34-0.61) 1.14 (0.73-1.55) S-metolachlor K3 1.59 (1.08-2.32) 1.25 (0.99-1.58) 0.78 (0.53-1.15) pyroxasulfone K3 1.03 (0.62-1.71) 0.79 (0.57-1.09) 0.76 (0.46-1.27) Active ingredient HRAC group Estimated resistance factors and their corresponding conﬁdence intervals for each herbicide tested against the homozygous Table 6.4: wild-type subline DD2078,sprayed the at BBCH03-05 homozygous and the mutantare percentage reported subline visual in biomass GG2078 reduction Table was6.3 . and recorded the 21 days susceptible after application. standard Other population estimated parameters G0. Herbicides were

155 CHAPTER 6. Negative cross-resistance aefrpoufcr n PCol.Smlry Ssad o nnsgicn’idctn htte9%Iitrascmrsdtevalue the the 6.4 comprised was Table intervals this (see 95%CI 1, branch the than the that less of indicating significantly top ‘non-significant’ was the for GG2078/DD2078 at stands for indicated NS value populations Similarly, RF50 of only. the The pair EPTC 1. e.g. the population. and ‘significant’, for G0 prosulfocarb values) for standard for ED50 stands susceptible case of S the (ratios estimates). and RF50 parameters population the for are GG2078 branches mutant the homozygote on pure values corresponding the DD2078, population 6.4: Figure irrhclognzto o h i ebcdstse nads-epneeprmn gis h uehmzgt wild-type homozygote pure the against experiment dose-response a in tested herbicides six the for organization Hierarchical

156 6.3. Discussion

6.3 Discussion

This study aimed to investigate whether negative cross-resistance (NCR) could be observed with lipid synthesis inhibitors on a number of ACCase target-site resistant L. multiflorum homozygous mutant and wild-type sublines. The preliminary experiment showed that prosulfocarb exerted low NCR effects on all the four mutations tested, i.e. I1781L, W1999S, D2078G and C2088R (Table 6.1, Figure 6.2). NCR effects estimated at 50% emergence reduction were significant only for the C2088R substitution. Overall, there were minimal consequences of this effect at the usual recommended field rate of 4,000 gai/ha (predicted percentage of emergence reduction not significantly different, Table 6.2). Natural variability between the wild- type sublines was substantial. The II1781 and LL1781 sublines were less controlled with prosulfocarb than the susceptible standard G0 population (Figure 6.2a). The more precise sand bioassay carried out with five other lipid synthesis inhibitors on the D2078G sublines showed that EPTC also resulted in significant NCR effects (Tables 6.3 and 6.4). Interestingly, the thiocarbamates (prosulfocarb and EPTC) and the K3 compounds (flufenacet, pyroxasulfone, napropamide and S-metolachlor) had different effects on sublines DD2078 and GG2078. NCR effects were only significant for the thiocarbamate herbicides (Figure 6.4).

Observed NCR eﬀects were of low relevance for ACCase-resistance management

Only small shifts were observed for the D2078G lines with RF50 values that ranged from 0.55 to 0.71 (Tables 6.3 and 6.4). This contrasted with the high levels of NCR observed in an atrazine-resistant E. crus-galli population which was 30 times more sensitive to the ACCase inhibitor ﬂuazifop- butyl than was the susceptible biotype [187]. Numerous studies have already demonstrated the ﬁtness penalties associated with target-site resistance to triazine herbicides mediated by the S264G substitution [reviewed in 206]. The substitution induces conformational changes in the D1 protein that result in impaired electron transfer from the QA (primary quinine acceptor) to the QB (secondary quinine acceptor) protein which reduces the photosynthetic capacity of the mutant compared to the wild-type. This leads to overall lower carbon assimilation in triazine-resistant plants which renders

157 CHAPTER 6. Negative cross-resistance them more vulnerable to stresses such as herbicide applications [195, 207]. Such effects have yet to be reported with ACCase target-site resistance although reduced ACCase specific activity has been documented for D2078G and C2088R [89, 201]. Finally, Jordan et al. [208] showed that NCR effects conferred by bentazon on Amaranthus hybridus L. populations resistant to atrazine were influenced by the growth conditions (field vs. greenhouse) and the growth stage (seedlings vs. established plants). Consequently, the usefulness of the prosulfocarb-NCR effects to specifically controlled ACCase- resistant populations should be further investigated.

Potential oﬀset by mitochondrial lipid synthesis

Plant mitochondria possess their own fatty acid synthase complex that dif- fers from the chloroplastic one and predominantly results in the production of 8-, 16- and 18-carbon fatty acids [209, 210]. Interestingly, mitochondria of dicotyledonous plants lack the ACCase enzyme required for the production of malonyl-CoA (Figure 6.1). Malonate produced by the cytosolic homomeric ACCase is transported to the mitochondria where it is used as the first building block for lipid synthesis [210]. Homomeric ACCase has recently been identified in mitochondria from barley and wheat [211] and peptides corresponding to a homomeric ACCase were found in the rice mitochondrial proteome [212]. The mitochondrial ACCase might be a general feature of grasses. Partial amino acid comparisons from chloroplastic and mitochondrial ACCase sequences from barley showed that both proteins were structurally very similar and possibly identical [211]. Further research is needed to confirm whether these two proteins are encoded by a unique nuclear gene. In the event of distinct chloroplastic and mitochondrial ACCase enzymes and assuming that fatty acids can be exported from grass mitochondria, it could be hypothesised that the mitochondrial lipid synthesis pathway compensates for the impaired production of acyl-CoA in the chloroplast in GG2078 and RR2088 mutants resulting in lower than expected negative cross-resistant effects. An alternative explanation would be that the putative reduction of specific activity for the mutant RR2088 is too low to induce a significant shortage of malonyl-CoA.

158 6.3. Discussion

Diﬀerences between thiocarbamates and others: elongase discrimination?

Slightly greater levels of negative cross-resistance were observed for the thiocarbamate herbicides compared with the HRAC K3 compounds tested against the D2078G lines (Tables 6.3, 6.4 and Figure 6.4). This observation might imply that different compound classes inhibit different elongases. This is supported by the work of Trenkamp et al. [48] that showed that thiocarbamates and K3 have different elongases specificity in Arabidopsis thaliana (L.) Heynh. On the other other hand, Tanetani et al. [213] has recently shown that for a given compound, i.e. pyroxasulfone, there were significant differences in the inhibitory potencies against elongases from susceptible grass weeds like L. multiflorum or Echinochloa frumentacea Link. and tolerant plants like wheat or corn, suggesting a high variability of the elongases pool within monocotyledonous plants. In every instance, detailed molecular and enzymatic studies are required to identify the precise target(s) of thiocarbamate herbicides in Lolium.

Is it worth looking for compounds exerting NCR eﬀects?

Pittendrigh and Gaffney [214] presented a theoretical framework utilising ultrahigh-throughput screening to systematically look for pesticides that may exert a NRC effect. However, a few years later they acknowledged that, despite its potential, this approach had not widely been adopted and was far from being developed outside the academic world [189]. This could be due to the lack of attractiveness of these toxicants compared to the discovery of a new mode of action, or more likely to their scarcity amongst existing pesticides. It may be more productive to exploit the conformational changes induced by known substitutions that result in target-site resistance in order to design compounds that would counteract those mutations by binding to a different niche. To a limited extent this situation already naturally exists. For instance, imidazolinones effectively control grass weeds carrying P197 substitution in the ALS gene while sulfonylureas have no effect [34]. Metabolic-based resistance also presents interesting possibilities for recip- rocal effects. Detoxification and activation of two different classes of toxicants may be performed by the same P450 as observed in laboratory mutants of rice blast fungus resistant to phosphorothiolate fungicides [215]. Unfor-

159 CHAPTER 6. Negative cross-resistance tunately, it was reported a few years later that resistant field isolates did not reproduce the NCR-effects with phosphoramidates [216]. This example highlighted (i) the importance of complementing laboratory experiments with field studies and (ii) the relevance of the organisms studied.

Insights into methodology

Once the suitability of the organism studied is acknowledged, the methodology used for assessing NRC effects is also critical. In the first part of this study the D2078G lines showed no significant evidence of NCR with prosulfocarb (Table 6.2), while significant NCR effects were observed with the sand bioassay (Table 6.4, Figure 6.3a). In both cases, the amplitude was low, i.e. less than 2-fold. The sand bioassay tends to artificially amplify differences leading to effects potentially not attainable at the field level. This reinforces the importance of experiments performed as close as possible to field conditions [145]. For the pre-emergence herbicide studied here, outdoors growth conditions and applications may have been ideal. However, this considerably limits the number of series of experiments that can be performed in a year and is more prone to considerable year-to-year variations [217].

6.4 Conclusions and Perspectives

This glasshouse study provided insights into the potential of several lipid biosynthesis inhibiting herbicides to exert negative cross-resistance effects (NCR) on a number of ACCase target-site resistant lines of L. multiflorum. Overall, prosulfocarb, EPTC, S-metolachlor, flufenacet and pyroxasulfone resulted in NCR effects of low amplitude. Napropamide was the only compound for which the mutant type was less controlled than the wild type. The NCR effects had little practical relevance for ACCase-resistance management. Altogether, the data generated here met the definition of scientific negative cross-resistance. Nevertheless, there remains the possibility of exploiting prosulfocarb-based mixtures to enhance the control of resistant Lolium spp. populations. In this respect, Chapter7 investigates the potential of four different prosulfocarb-based mixtures.

160 7 Prosulfocarb mixtures for the control of Lolium spp. populations in winter wheat and winter barley

7.1 Introduction

In the absence of chemicals with new modes of action from the agrochem- ical industry, farmers are having increasing difficulty combating herbicide resistance and are beginning to call for the comeback of mechanical, cultural and even biological techniques for effective weed control. There are a number of options to relieve the pressure put on chemical weed control. The choice of the crop and cropping program is of first importance. Ro- tating crops with different life cycles, i.e. winter wheat and oil seed rape; including fallow or cover crops; delaying drilling; increasing crop density and planting highly competitive crops/cultivars have been shown to provide a competitive advantage to suppress weeds without over-reliance on chemical solutions [218–222]. If soil erosion is not a problem, tillage and inter-row cultivation are recommended [222–224]. Finally, bioherbicides may be an option for the future. Weed biocontrol using plant diseases has had most success in the control of alien weeds that had escaped the restraint of their indigenous pathogens [225, 226]. Controlled release of a pathogen into the new habitat has had some successes, for example the introduction in Aus- tralia of a rust fungus to control Chondrilla juncea L. (rush skeletonweed), a noxious weed invading fields and side roads [227].

Surveys have indicated that most farmers are, in general, well aware of the diﬀerent options they have available to prevent and manage the evolution of herbicide resistance [222, 228]. However, economical, regulatory,

161 CHAPTER 7. Prosulfocarb mixtures environmental and societal barriers may prevent their implementation [229]. If Integrated Weed Management had been more widely adopted since the introduction of the concept in the 1970-80’s there would be fewer cases of herbicide resistance. As chemical control remains the number one option for weed management, the existing solutions have to be used sustainably. Guidelines advocate the rotation of herbicide modes of action complemented with reduced reliance on high-risk compounds such as ACCase and ALS- inhibiting herbicides and recommend the use of herbicide sequences and mixtures [222]. The idea of mixing herbicides for eﬀective weed control is in fact not new and dates from the beginning of organic pesticide use [230]. Herbicide mixtures were acknowledged as a anti-resistance strategy since the ﬁrst concerns about triazine and sulfonylurea resistances [121, 126]. Early mixtures were developed mainly for broadening the spectrum of weeds controlled, i.e. one compound controls monocotyledonous weeds and the other the grasses. Currently, the focus is more on synergistic mixtures as they could help (i) reducing total herbicide inputs while providing excellent control on susceptible weeds and (ii) controlling some resistant weed populations.

In this study, the possible outcomes of a mixture are defined using Tammes [231] terminology. Synergism is the cooperative action of the two (or more) components, such that the total effect is greater than the individual effects. In the case of an additive effect, the components may be substituted for each other in amount inversely proportional to their activity such that the total effect is equal to the sum of the individual effects. Antagonism is the opposite of synergism. Two separate models and companion statistical analyses have been developed to assess herbicide joint action.

The oldest and simplest approach is the method deﬁned by Colby [232] in 1967, sometimes termed MSM for Multiplicative Survival Model. It com- pares the expected weed control of herbicides A and B applied in mixture to the observed weed control based on the solo performance of A and B. If the expected value is less than the observed value, then, the mixture shows evidence of synergy. Endpoints can be anything from visual percentage of weed control, to percentage survival, to percentage of biomass reduction based on dry weight measurement. It is not limited to the evaluation of binary

162 7.1. Introduction mixtures and can be extended to ternary or higher mixes of active ingredients. Originally proposed without a statistical companion Flint et al. [233] suggested a modified ANOVA for log-transformed data to analyse statistically the joint activity based on slope comparisons for dose-response curves. The shift from parallelism and its steepness indicates whether there is synergism, antagonism or additivity. Although statistically viable, the method has three limitations. Firstly, it deals with mixtures of two active ingredients and cannot account for adjuvant effects as these are by definition inactive ingredients. Secondly, it is limited by single herbicide rates that result in maximum biomass reduction. Consequently, ‘false’ antagonism can be reported as it is no longer biologically achievable to obtain parallel slopes for high rates [234]. Finally, it requires the use of a dose-response experimental design.

The second model is the Additive Dose Model (ADM) [235]. Contrary to the MSM model which assumes multiplicativity of effects, the ADM assumes additivity of doses. It requires the determination of the relative potencies of the two herbicides tested. Lines that represent all mixtures that give the same level of response are drawn [236]. The straight line means additivity of effects; a concave deviation demonstrates antagonism and a convex deviation synergism. This model also implicitly assumes that the two herbicides have the same mode of action but do not compete at the binding site [237]. Nevertheless, this model has also been used with herbicides having different biological targets [238]. The main limitation of the ADM model for prosulfocarb mixtures stands in the ‘biological exchange rate’, in other words, the relative potencies. Prosulfocarb requires very high rates to achieve even 50% control at the PRE application stage. Its efficacy is inversely proportional to the application growth stage, making POST mixtures difficult to analyse with ADM. There seems to be no general con- sensus about which reference model, i.e. MSM or ADM, should be used in which situation [239].

This chapter evaluates the potential of different prosulfocarb mixtures for the control of selected Lolium spp. populations in winter wheat and winter barley based on the MSM model without Flint’s analyses. Four different mixtures were investigated with different objectives:

163 CHAPTER 7. Prosulfocarb mixtures

1. Evaluation of herbicides not commonly used for grass weed control in cereals. Metribuzin and diﬂufenican do not have approval for grass weed control in cereals in all European states but are widely used for broad-leaved weed control in potatoes [240, 241]. Their primary targets are broad-leaved weeds, but they exert some graminicide activity. Metribuzin is a potential solution for rigid brome (Bro- mus rigidus L.) control in Australia in barley crops [242]. A recent patent that investigates herbicidal compositions comprising prosulfocarb showed the potential of a prosulfocarb plus diﬂufenican mixture for grass control in rice, cereals and maize [243].

2. Evaluation of a newly registered active ingredient. Pyroxasul- fone is now registered in Australia for grass weed control in wheat, triticale and barley crops. Studies have already proven the suitability of pyroxasulfone to control herbicide-resistant Lolium rigidum Gaud. populations [244, 245]. Recurrent selection at sub-optimal pyroxasulfone rates showed the potential for rapid herbicide resistance evolution in rigid ryegrass [246]. Pyroxasulfone mixtures have not been investigated yet but are in agreement with the development of eﬀective stewardship programs to sustain its use.

3. Evaluation of a POST mixture with an ALS inhibitor. The usefulness of prosulfocarb POST mixtures with the ACCase inhibitor clodinafop-propargyl has already been demonstrated for the control of a resistant Alopecurus myosuroides Huds. population [247]. It was therefore of interest to determine whether a mixture with an ALS inhibitor was suitable for the control of a resistant L. multiﬂorum population. The chosen partner was the pre-packaged mixture iodosulfuron- methyl-sodium+mesosulfuron-methyl 1:5 (referred as ATL) due to its wide use in Europe. It has to be noted that ATL is not recommended on barley crop due to toxicity issues.

164 7.2. Materials and Methods

7.2 Materials and Methods

7.2.1 Mixture design

The prosulfocarb mixtures with the four different partners were investigated under greenhouses conditions at two different growth stages according to the partner tested. Each mixture was evaluated against a susceptible standard Lolium sp. population. A population exhibiting non-target-site based resistance to the mixing partner investigated was included whenever possible. If not available, the populations SLR31 or UK225.G1 were chosen because of their atypical and extreme resistance profiles (UK225 populations are detailed in Chapter5). The selectivity of the mixtures was investigated with one cultivar of winter wheat and winter barley; respectively Hereward and Suzuka (see section 2.1.3). These two cultivars were on the recommended Home Grown Cereal Authority (HGCA) list and were widely grown across Europe. Eight seeds of both cereal species were sown per pot. Two replicate pots units were produced for each treatment including the untreated controls. A matrix design was set up, (i) prosulfocarb was tested alone in a dose response with a minimum of four rates (= columns of the matrix), (ii) the herbicide partner was also tested alone in a dose response with a minimum of four rates (= rows of the matrix), and (iii) each ‘intersection’ was the combination of both herbicides. Experiments were randomised per block, each block corresponding to one replicate of a particular species. Seeds were sown in 4” pots filled with TMA soil. PRE experiments were visually assessed 14 DAA while POST experiments were assessed 21 DAA.

• Mixture 1 prosulfocarb plus metribuzin applied PRE on G0 (susceptible standard Lolium multiﬂorum Lam. population) and UK225.G1. All combinations of the following rates were studied: prosulfocarb at 0; 320; 640; 1,600; 2,400; 3,200 and 4,000 gai/ha; metribuzin at 0; 32; 64; 160,240 and 320 gai/ha.

• Mixture 2 prosulfocarb plus diﬂufenican applied PRE on G0 and UK225.G1. All combinations of the following rates were studied: prosulfocarb at 0; 640; 1,600; 2,400; 3,200 and 4,000 gai/ha; diﬂufenican at 0; 32; 64; 160 and 240 gai/ha.

• Mixture 3 prosulfocarb plus pyroxasulfone applied PRE on PP1

165 CHAPTER 7. Prosulfocarb mixtures

(susceptible standard L. rigidum population) and SLR31. All combinations of the following rates were studied: prosulfocarb at 0; 640; 1,600; 2,400; 3,200 and 4,000 gai/ha; pyroxasulfone at 0; 16; 32; 64 and 160 gai/ha.

• Mixture 4 prosulfocarb plus the formulated mix iodosulfuron + mesosulfuron 1:5 (ATL) applied POST on G0 and 2005 UK 242. All combinations of the following rates were studied: prosulfocarb at 0; 1,600; 2,400; 3,200 and 4,000 gai/ha; ATL at 0; 2.25; 4.5; 9 and 18 gai/ha (cumulative basis weight). The recommended adjuvant Biopower (Bayer CropScience) was added to the spray mix at 0.5% v/v for every mixture and for the ATL treatments. Population 2005 UK 242 was previously characterised to exhibit low levels of metabolic-based resistance against the ALS inhibitor ATL [112].

7.2.2 Evaluation of the prosulfocarb plus pyroxasulfone tank mix at 3,200 gai/ha plus 64 gai/ha

The most promising prosulfocarb/pyroxasulfone tank mix was evaluated against 13 L. rigidum populations including PP1 and SLR31. The 11 remaining populations were harvested in Australian fields by Syngenta representative in 2003 and were selected based on their resistance profiles (Table 7.1), which was determined using a single discriminative rate of 14 different herbicides. Seeds were sown in troughs filled with TMA soil. Only one replicate trough was produced. The populations were screened alongside the reference populations PP1 (susceptible) and SLR31 (resistant). Nine POST treatments were evaluated as described in section 2.1.7, namely clodinafop 60 gai/ha, pinoxaden 45 gai/ha, cycloxydim 200 gai/ha, sethoxydim 200 gai/ha, haloxyfop 100 gai/ha, ATL 18 gai/ha, sulfometuron 100 gai/ha, imazapyr 100 gai/ha and iodosulfuron 10 gai/ha. Chlorotoluron was applied at the ePOST growth stage at 1,500 gai/ha. Three compounds were sprayed at the PRE growth stage, i.e. diflufenican 250 gai/ha, flufenacet 450 gai/ha and trifluralin 200 gai/ha. Trifluralin (and only trifluralin) was applied onto uncovered seeds sown on dry soil. Seeds were covered 10 to 20 minutes after application with TMA soil and watered 2 hours later. The prosulfocarb/pyroxasulfone tank mix was subsequently evaluated. Seeds were sown in 4” pots filled with TMA soil. Three replicate pot units were

166 7.2. Materials and Methods produced for each population and herbicidal treatment. Prosulfocarb and pyroxasulfone were applied alone at respectively 3,200 and 64 gai/ha. The combination of both rates was also applied. This experiment was conducted only one time. Biomass reduction was visually recorded 14 DAA.

167 CHAPTER 7. Prosulfocarb mixtures PI niio) rflrln20gih mcouueasml niio) iueia 5 a/a(D niio)adflfnct450 flufenacet and gai/ha inhibitor) 1,500 (PDS 2.1.7 . chlorotoluron gai/ha section inhibitors); in 250 (ALS described diflufenican methodology gai/ha inhibitor); the 10 to assembly iodosulfuron according application inhibitors); (microtubule gai/ha, inhibitor) (ACCase after gai/ha gai/ha synthesis obtained 100 (VLCFA 100 values 200 imazapyr haloxyfop gai/ha control trifluralin gai/ha, weed gai/ha, 200 on inhibitor); 100 sethoxydim based gai/ha, (PSII sulfometuron was 200 population cycloxydim gai/ha, field gai/ha, 18 the 45 ATL pinoxaden for gai/ha, profile 60 resistance clodinafop The of origin. and profiles resistance al 7.1: Table u 2 eitn oflfnctFed Victoria Field, Victoria Field, Wales South New Field, Wales Herbiseed South Commercial, New Field, Australia Western Field, Australia Western Australia Field, Western Field, Victoria Origin Field, Victoria Australia Field, Western Field, (TS) inhibitors ALS and (NTSR) inhibitors ACCase flufenacet, to Resistant flufenacet inhibitors to ALS Resistant to resistance ALS-sensitive target-site ACCase-sensitive, inhibitors, ACCase to ALS-sensitive resistance Target-site inhibitors, ACCase to Herbiseed 437 ALS-sensitive resistance Commercial, Aus Target-site inhibitors, ACCase (NTSR) to inhibitors 228 resistance ALS Aus Target-site and ACCase 328 to tested Aus Resistant herbicides all 362 to tested Aus Sensitive herbicides all 253 to (NTSR) tested Aus Sensitive inhibitors herbicides ACCase all and 250 to flufenacet Aus Sensitive trifluralin, to Resistant and 352 (NTSR Aus inhibitors ACCase and 202 ALS Aus flufenacet, trifluralin, to standard 217 Resistant Susceptible Aus 182 Aus 97 Aus SLR31 profile PP1 Resistance code Population ito the of List TSR) .rigidum L. ouain etdaanttepoufcr lsprxsloetn i,wt hi determined their with mix, tank pyroxasulfone plus prosulfocarb the against tested populations omril Herbiseed Commercial,

168 7.2. Materials and Methods

7.2.3 Data analysis

Mixture evaluation

For each mixture and population/species tested, the average percentage of herbicidal damage was calculated. Mixtures were grouped according to four diﬀerent nested criteria:

• Mixtures resulting in unacceptable levels of control on the susceptible standard population (< 80%).

• Mixtures resulting in good levels of control on the susceptible standard population (equal to a greater than 80%) but resulting in unacceptable levels of phytotoxicity on either winter wheat or winter barley (> 25%).

• Mixtures resulting in good levels of control on the susceptible standard population and below threshold phytotoxicity for winter wheat and winter barley but resulting in unacceptable levels of control on the resistant population tested (< 80%).

• Mixtures resulting in (i) good levels of control on the susceptible standard population and (ii) acceptable levels of phytotoxicity on winter wheat and winter barley and (iii) good levels of control on the Lolium sp. resistant population tested.

Only mixtures meeting the last criterion were considered as a viable option for a ﬁeld application. In this respect, the synergistic potential of the mixtures were assessed using Colby’s formula [232]. Independency of action for the two herbicide partners was assumed based on their biological target. However, it could be argued that the prosulfocarb/pyroxasulfone mixture did not act as a true independent mixture as pyroxasulfone has also been shown to inhibit VLCFAs synthesis [248]. Nevertheless, the Lolium elongase(s) that are inhibited by both prosulfocarb and pyroxasulfone are yet to be identiﬁed. Therefore, it was assumed that the two herbicides did not compete at the target-site level. Finally, the formulated mix ATL, i.e. iodosulfuron+mesosulfuron was considered as one entity only since (i) the ratio of the two active ingredients was kept constant in all the mixtures evaluated and (ii) the objective of the study was not to determine which of these ALS inhibitors was best suitable for a mixture. The expected levels

169 CHAPTER 7. Prosulfocarb mixtures of control for each tank mix were calculated as described in Equation 7.1, where XA is the mean percentage of weed control achieved with herbicide A applied on its own and XB the same for herbicide B. The sign of the diﬀer- ence between the observed value and the expected value indicated whether there was evidence of synergism (0 < observed - expected) or antagonism (0 > observed - expected) or additivity of eﬀects (observed - expected = 0). This value was termed the ‘synergism points’. Exact equality was unlikely, therefore the range -10 < x < 10 was chosen as giving no evidence of either antagonism or synergism and hence indicating additivity.

X X Expected = X + X − A B (7.1) A B 100

Evaluation of the prosulfocarb plus pyroxasulfone tank mix at 3,200 gai/ha plus 64 gai/ha

For each of the three treatments, i.e. prosulfocarb alone at 3,200 gai/ha; pyroxasulfone alone at 64 gai/ha and the tank mix, the statistical signiﬁc- ance between the mean ranks of weed control amongst the 13 populations was tested on the basis of the Kruskal-Wallis test.

7.3 Results

7.3.1 Potential of prosulfocarb mixtures with four diﬀerent partners

Prosulfocarb plus metribuzin

The effects of the metribuzin and prosulfocarb dose-response trials and the corresponding mixtures are shown in Figure 7.1a for the susceptible standard L. multiflorum population G0. Metribuzin provided low levels of control on G0 even at the highest rate tested of 320 gai/ha. Half of the mixtures showed strong levels of synergism, with, for instance, up to +55 points recorded for 320 g prosulfocarb + 32 g metribuzin /ha. The other half were located in the range -10 < x < 10, showing no evidence of either antagonism or synergism. A constant ratio of 10 between prosulfocarb and metribuzin doses was tested five times with different amounts of each ingredient, i.e. 320+32 gai/ha; 640+64 gai/ha; 1,600+160 gai/ha; 2,400+240 gai/ha and 3,200+320 gai/ha (prosulfocarb+metribuzin). All the five combinations

170 7.3. Results showed consistently high levels of synergism, e.g. +28 points were recorded for 2,400+24 gai/ha. However, only the last three mixtures provided good to excellent levels of control on G0. Results are presented in a more sum- marized form in Figure 7.1b.

Metribuzin alone proved to be relatively safe on the winter wheat cv. Hewevard and the winter barley cv. Suzuka with symptoms no greater than 17% on wheat at the highest rate of 320 gai/ha. The synergistic eﬀects observed on G0 and UK225.G1 were transposed to the cereals tested. They were stronger for barley than wheat (data not shown) resulting in unacceptable levels of damages for 13 mixtures, i.e. yellowing, stunting, leaf malformation (Figure 7.1b). Amongst all the mixtures tested, one- third were too phytotoxic, more than half did not provide suﬃcient levels of control on G0 and only two met the criterion for a desirable mixture, i.e. 3,200+32 and 4,000+32 gai/ha (prosulfocarb+metribuzin).

Prosulfocarb plus diﬂufenican

Overall, the prosulfocarb plus diflufenican mixtures provided excellent levels of control on the susceptible population G0 (Figure 7.2). However, the levels of synergisms were in general lower than those observed for metribuzin. Only 30% of the mixtures were recorded as synergistic and the highest level was for 640+64 gai/ha (prosulfocarb+diflufenican) with +28 points. As previously observed with metribuzin, the highest rate of diflufenican (240 gai/ha) in combination with prosulfocarb rates greater than 640 gai/ha were too phytotoxic (Figure 7.2b). Four mixtures met the qualifying criterion, i.e. 640+240; 2,400+32; 2,400+64 and 4,000+32 gai/ha (prosulfocarb+diflufenican) and only 2,400+32 gai/ha showed strong evidence of synergism for both the susceptible population G0 and UK225.G1.

Prosulfocarb plus pyroxasulfone

Pyroxasulfone alone provided low levels of control on the L. rigidum populations PP1 (susceptible standard) and SLR31 at rates below 160 gai/ha (Figure 7.3). Seventy-ﬁve percent of the mixtures tested with prosulfocarb rates greater than 1,600 gai/ha and any pyroxasulfone rate provided good to excellent levels of control on PP1. High levels of synergism were recorded for

171 CHAPTER 7. Prosulfocarb mixtures some of the mixtures, e.g. 1,600+32 gai/ha (prosulfocarb+pyroxasulfone) with +56 points. All mixtures with the highest rates of pyroxasulfone were too phytotoxic on the cereal cultivars tested (Figure 7.3b); barley being more aﬀected than wheat (data not shown). The most promising mixtures were found at lower rates of pyroxasulfone and were mainly 1,600+64; 2,400+64; 3,200+64 and 4,000+64 gai/ha (prosulfocarb+pyroxasulfone). All the four candidates showed high levels of synergism on the susceptible standard population PP1 and there was some indication of synergism on SLR31. Redu- cing prosulfocarb input was also an objective of the mixture design, therefore, the tank mix 3,200+64 was chosen instead of 4,000+64 gai/ha (prosulfocarb+pyroxasulfone) for the evaluation with ﬁeld populations originating from Australia (see section 7.3.2).

Prosulfocarb plus ATL

Prosulfocarb applied POST did not provide sufficient levels of weed control on either the susceptible standard population G0 or the ALS-resistant population 2005 UK 242 with visual biomass reduction less than 50% in both cases (Figure 7.4a). There was no evidence of a relatively better level of weed control with prosulfocarb on the ALS-resistant population compared to G0. The pre-packaged mix ATL (iodosulfuron:mesosulfuron 1:5) resulted in high levels of control on G0 (87.5%, mean of two replicate pot units) at the lowest rate of 2.25 gai/ha and full control from 4.5 gai/ha. The levels of ALS-resistance in the 2005 UK 242 were more noticeable at low ATL rates (below 9 gai/ha). Full control was recorded at the recommended field rate of 18 gai/ha. For these mixtures, the contribution of prosulfocarb was minimal. As pictured with 2005 UK 242, the mixture patterns resembled more the weed control pattern obtained for ATL on its own. This had consequences on synergism. Only one mixture showed significant levels of synergism with +11 points for 2,400+4.5 gai/ha (prosulfocarb+ATL). For the susceptible standard population G0, there was no evidence that ATL antagonised or synergised the activity of prosulfocarb as synergy points were limited to between -5 and +3.

High levels of phytotoxicity were observed for the prosulfocarb mixes with 18 g ATL/ha on winter barley cv. Suzuka with more than 40% biomass

172 7.3. Results reduction. It has to be noted that ATL is not recommended on barley due to toxicity issues. ATL on its own had only minor toxicity effects with, on average, 7.5% visual damages. Likewise, less than 15% damage was observed for prosulfocarb at all rates tested. However, the mixtures resulted in an important synergistic but phytotoxic effect on the winter barley cultivar with more than 30 synergy points associated with phytotoxicity. The same effect was observed for the winter wheat cultivar Hereward for any mix with 18 g ATL/ha and prosulfocarb rates greater than 1,600 gai/ha. Finally, only one tank mix met the criterion of satisfactory weed control for the susceptible and the resistant populations as well as low phytotoxicity levels, i.e. 2,400+9 gai/ha (prosulfocarb+ATL).

173 CHAPTER 7. Prosulfocarb mixtures ewe 1 n 0sosn togeiec fete naoimor antagonism either effects. value of of Any additivity evidence denote strong synergism. only no higher of and shows The evidence synergism 10 the and 7.1 ). greater -10 Equation the between see value, values, is positive gauge expected the the which the between to difference and gauges, (the next observed green formula value Colby’s the with The on based 80 80 control. points’ and ‘synergism of than the value level 50 greater acceptable control between if an gauges, weed and denotes red any gauges with orange purposes, represented with with was readability coded 50% For is than reduction lower biomass gauge. visual empty of an percent Zero (n=2). control standard susceptible G0 the population for control Weed (a) prosulfocarb rate in gai/ha 1600 2400 3200 4000 320 640 0 ahguerpeet h enpretg fvisual of percentage mean the represents gauge Each . 0 metribuzin rate in gai/ha iue7.1: Figure 32 55 28 0 5 24 10 64 5 30 5 18 8 −6 eut o h rsloabpu erbznmxue experiment. mixtures metribuzin plus prosulfocarb the for Results 160 15 19 18 21 12 −3 .multiflorum L. 240 30 34 4 28 20 10 320 10 6 6 14 4 4 h rtvlerfr otessetbepplto 0adtesecond the and G0 brackets; population UK225.G1. into susceptible population shown resistant re- the are the to the points’ to refers on ‘synergism value control The mixtures first good are the criteria. squares provide all Green to met UK225.G1. acceptable failed that case gave this but and in G0 population, crops on sistant cereal control barley both of winter on levels or criterion wheat phytotoxicity winter the the con- either ( weed for tested ( phytotoxic cultivar ¡80% G0 controlled too successfully i.e. were that mixtures (G0), but are tested squares Red population standard trol. the on control (b) prosulfocarb rate in gai/ha rysursrpeetmxue htddntpoiesufficient provide not did that mixtures represent squares Grey 1600 2400 3200 4000 320 640 > 5) lesursrpeetmxue htfulfilled that mixtures represent squares Blue 25%). metribuzin rate in gai/ha (24,14) (10,5) 32 64 160 240 320 > 80%)

174 7.3. Results 240 (2,7) 160 64 (7,18) 32 (12,28) (−2,11) diflufenican rate in gai/ha rate diflufenican . Green squares meet all criteria for a desirable mix-

640

4000 3200 2400 1600 prosulfocarb rate in gai/ha in rate prosulfocarb (b) Summarised viewexperiment of the prosulfocarb plus diflufenican ture, i.e. good(UK225.G1) control and of acceptable G0, phytotoxicity goodbarley. levels control The on of ‘synergism winter the points’refers wheat are resistant to and population shown G0 into and brackets; the the second first to value UK225.G1. 1 1 1 2 2 240 L. multiflorum 2 4 4 6 11 160 5 9 7 6 28 64 12 12 24 18 −2 32 diflufenican rate in gai/ha rate diflufenican 0 Results for the prosulfocarb plus diflufenican mixtures experiment. For a more detailed legend, refer to Figure 7.1 with ‘synergism points’ indicated below the gauge. 0

640

4000 3200 2400 1600 prosulfocarb rate in gai/ha in rate prosulfocarb Figure 7.2: (a) Weed control for the susceptible standard population G0

175 CHAPTER 7. Prosulfocarb mixtures a edcnrlfrtessetbestandard susceptible PP1 the pulation for control Weed (a)

iue7.3: Figure prosulfocarb rate in gai/ha 1600 2400 3200 4000 640 0 ih‘yegs ons niae eo h gauge. the below indicated points’ ‘synergism with 7.1 Figure to refer legend, detailed more a For experiment. mixtures pyroxasulfone plus prosulfocarb the for Results 0 pyroxasulfone rate in gai/ha 16 −4 −1 16 20 0 32 21 56 29 9 2 64 26 45 12 22 6 .rigidum L. 160 19 14 6 7 6 po- e.Te‘yegs ons r hw nobakt;teﬁs value ﬁrst the SLR31. brackets; population to into second resistant shown the the and are PP1 of points’ bar- to control and ‘synergism refers wheat The good winter on PP1, levels ley. phytotoxicity of acceptable control and (SLR31) good pyroxasulfone plus i.e. prosulfocarb the of experiment view Summarised (b) prosulfocarb rate in gai/ha 1600 2400 3200 4000 640 re qae etalciei o eial mixture, desirable a for criteria all meet squares Green . pyroxasulfone rate in gai/ha 16 32 64 (45,9) (12,8) (22,8) (6,2) 160

176 7.3. Results 18 9 (3,−5) 4.5 ATL rate in gai/ha rate ATL 2.25

4000 3200 2400 1600 . Green squares meet all criteria for a desirable mixture, i.e. good prosulfocarb rate in gai/ha in rate prosulfocarb (b) Summarised viewment of thecontrol prosulfocarb of the plus standardALS-resistant ATL susceptible population population experi- and G0, acceptable phytotoxicity goodwheat levels control and on of winter barley. the Theﬁrst ‘synergism value points’ refers are to shown G0 into and brackets; the the second to 2005 UK 242. po- 0 2 0 −1 18 3 9 −8 −5 −1 L. multiﬂorum 6 8 11 −5 4.5 ATL rate in gai/ha rate ATL 5 4 −8 −1 with ‘synergism points’ indicated below the 2.25 Results for the prosulfocarb plus ATL mixtures experiment. For a more detailed legend, refer to Figure 7.1 0 0

Figure 7.4:

4000 3200 2400 1600 prosulfocarb rate in gai/ha in rate prosulfocarb pulation 2005 UKgauge. 242 (a) Weed control for the ALS-resistant

177 CHAPTER 7. Prosulfocarb mixtures

7.3.2 Evaluation of the prosulfocarb plus pyroxasulfone tank mix on chosen L. rigidum populations

All the four herbicide-sensitive populations tested were successfully controlled with either the solo compounds or the tank mix (Table 7.2, Figure 7.5). This contrasted with the results previously obtained for PP1 and SLR31 where relatively low levels of control were recorded for both pyroxasulfone at 64 gai/ha and prosulfocarb at 3,200 gai/ha (Figure 7.3a). Variable responses were observed for pyroxasulfone at 64 gai/ha (Figure 7.5). Four of the herbicide-resistant populations were fully controlled (> 95%), three were relatively well controlled (80% < x < 90%) while unacceptable levels of control were obtained for SLR31 and Aus 97 (<80%, Figure 7.5). The Kruskal-Wallis test confirmed that there were differences between the 13 populations tested (p-value<=0.01, Figure 7.5). Nevertheless, none of the field harvested populations was significantly different from each other or from the susceptible standard PP1. The variability in response was also greater for pyroxasulfone compared with prosulfocarb and the tank mix as indicated by the pooled error variance calculated across all populations, i.e. 94 for pyroxasulfone, 4.46 for prosulfocarb and 1.74 for the tank mix. Control values ranged from 94% to 98% for prosulfocarb alone, and from 98% to 100% for the tank mix. Finally, the Kruskal-Wallis test confirmed that there was no difference in control between the 13 populations for either prosulfocarb alone or the tank mix (p-value > 0.10). Overall, the tank mix proved to present a significant competitive edge over the pyroxasulfone alone treatment, especially for the control of resistant populations. Data disper- sion was reduced between prosulfocarb alone and the tank mix highlighting another advantage of the mixture.

178 7.3. Results

100

20 weed control (visual percentage) weed

0 PP1 SLR31 Aus.97 Aus.182 Aus.202 Aus.217 Aus.228 Aus.250 Aus.253 Aus.328 Aus.352 Aus.362 Aus.437

Figure 7.5: Percentage of weed control for the 13 ryegrass populations assayed against pyroxasulfone applied pre-emergence at 64 gai/ha. Visual assessment was performed 14 DAA. Main bars represent the mean value of three replicate pot units and the error bars are ±1 standard error of the difference between two means, bounded by 100. PP1, Aus 97 and SLR31 are commercially available L. rigidum populations via Herbiseed. All the other populations originated from Australian fields. PP1, Aus 182, Aus 217 and Aus 202 are herbicide-sensitive lines. For more detailed information on the resistance profiles, refer to table 7.1

179 CHAPTER 7. Prosulfocarb mixtures a/aadtecrepnigtn i.Hriie eeapidpeeegnea BH3 nuysoe eentd1 asafter days 14 noted were scores Injury profiles. BBCH03. resistance at the of pre-emergence determination applied the were for Herbicides 7.1 Table mix. to Refer tank corresponding application. the and gai/ha 7.2: Table u 6 99 100 99 100 96 98 98 100 100 96 99 97 98 89 98 97 96 98 85 94 79 98 98 100 99 and ACCase flufenacet, to Resistant flufenacet to Resistant 437 ALS Aus to resistant 228 ACCase-sensitive, Aus 328 Aus 362 in- Aus ALS and 253 Aus ACCase to 250 Resistant Aus Sensitive 352 Sensitive Aus 202 Sensitive Aus 217 flufenacet, Aus trifluralin, to standard Resistant 182 Susceptible Aus 97 Aus SLR31 PP1 profile Resistance Population ebcd estvt o h 13 the for sensitivity Herbicide L inhibitors ALS inhibitors ALS-sensitive inhibitors, ACCase to Resistant hibitors inhibitors ACCase and ALS .rigidum L. ouain etdaantprxsloea 4gih,poufcr t3,200 at prosulfocarb gai/ha, 64 at pyroxasulfone against tested populations iulpretg fwe oto ma ftrerpiaeptunits) pot replicate three of (mean control weed mix of Tank percentage Visual gai/ha 3,200 prosulfocarb gai/ha 64 pyroxasulfone tnaderro h ieec ewe w means two between difference the of error Standard .017 1.08 1.72 7.90 39 99 98 96 99 95 100 97 98 97 83 97 97 98 95 61 Treatment

180 7.4. Discussion

7.4 Discussion

This study aimed to (i) determine prosulfocarb-based treatments that would provide, under greenhouse conditions, sufficient weed control of two ryegrass populations while being not too phytotoxic for the winter wheat cultivar Hereward and the winter barley cultivar Suzuka; and (ii) test one of the successful mixes across a wider range of L. rigidum populations. Over the 86 mixtures tested, only 11 met the criterion (11.5%) and 34% were too phytotoxic regardless of the weed control achieved. The prosulfocarb plus pyroxasulfone mixture applied PRE at 3,200+64 gai/ha presented a significant competitive edge over the pyroxasulfone treatment, especially for the control of resistant populations, including those resistant to the oxyacetamide herbicide flufenacet.

Choice of the partners: theory and practice

The ideal mixture may be defined as having partners with (1) similar weed spectrum, (2) similar levels of efficacy against the targeted weed(s), (3) different biological targets, (4) different degradation routes, (5) similar soil persistence (of importance for compounds with residual activity), (6) negative cross-resistance, in other words a fitness penalty effect (of importance for a mixture with known resistance to one of the components) and (7) synergism (to reduce the amount of each partner) in order to effectively delay the onset of resistance or manage herbicide-resistant weed populations [121, 126, 222]. Such a combination of attributes is rare, yet even when found nothing guarantees that it would actually provide the expected results as, ultimately, everything relies on farmers’ practices. Paraquat demonstrates the case in point. It does not have a biological target per se, but captures electrons from transport chains primarily at the PSI flow and to a lesser extent during mitochondrial respiration [249]. Its structure makes it non-metabolisable by P450 or GST [cited in 201]. Thus, there was the- oretically, a low risk of paraquat resistance evolution. However, resistance has developed in Conyza species and in every instance paraquat had been applied several times during the same cropping season for more than five consecutive years [250]. Resistance may have never evolved or would have evolved later if paraquat had been used in a wiser manner, e.g in mixtures or sequences [251].

181 CHAPTER 7. Prosulfocarb mixtures

Modelling studies showed that resistance evolution was slower when a mixture of two herbicides was repeatedly applied as compared to rotational applications [cited in 162]. Mixtures have to be well integrated into programs to avoid any adverse effects that would hamper their usage. On paper, none of the four mixtures presently investigated fulfilled the seven requirements listed above. Three had different biological targets, namely metribuzin (PSII inhibition), diflufenican (PDS inhibition) and ATL (ALS inhibition) while pyroxasulfone was border-line (elongase inhibition). For the prosulfocarb plus diflufenican mixture at 2,400 + 32 gai/ha, the two components had opposite individuals efficacies, i.e. highly effective for prosulfocarb and mediocre for diflufenican, invalidating criterion (2). Never- theless, this resulted in strong synergism effects on the two weed populations tested with +12 points for G0 and +28 for UK225.G1 (Figure 7.2), meeting criterion (7) relative to synergism. The prosulfocarb plus ATL mixture was tested against the ALS-resistant population 2005 UK 242. Prosulfocarb alone did not provide a better POST control on 2005 UK 242 compared to the susceptible standard, suggesting the absence of negative cross-resistance, which invalidates criterion (6). The only prosulfocarb+ATL mixture that did not result in excessive crop damage while successfully controlling the susceptible standard and 2005 UK 242 did not show any evidence of synergism, invalidating criterion (7). However, prosulfocarb, iodosulfuron and potentially mesosulfuron are more than likely to be degraded via different biological pathways meeting criteria (4) and have similar weed spectrum (see chapters4 and5).

From a resistance management perspective, the seven aforementioned attributes should be checked for any mixture about to be registered and any already marketed pre-packaged product. Surprisingly, amongst the 429 formulated mixes registered for use in 2008 in Tennessee, 210 contained two or more components having the same mode of action [252], meaning than only 51% of the registered mixtures met criteria (3). Resistance to synthetic auxins had evolved remarkably slowly [253] and may represent less risk. After having removed synthetic auxins mixtures, 62 out of the 210 mixes remained (14%). Amongst them, triazines mixtures were predominant. They were followed by mixture with ALS inhibitors. This was a very

182 7.4. Discussion high proportion considering the current triazine and ALS resistance problems in Tennessee and, to a greater extent, in the USA [54]. Complying with criteria (3) does not seem to be of essential importance when marketing a new pre-packaged mixtures.

To conclude, only large-scale screens complemented with long-term ﬁeld experiments would help deciding whether any of the 11 mixtures selected in the present study are suitable for the management of resistant ryegrass populations.

Mixtures with metribuzin, a potentially phytotoxic compound to winter cereals

Cultivars of different crops including soybeans, potatoes, tomatoes, wheat and barley differ in their response to metribuzin [242, 254]. Barley seems to be more tolerant than wheat, based on two studies that involved two cultivars of each crop [255, 256]. In the present study, metribuzin was applied on the winter wheat cultivar Hereward, which is resistant to chloro- toluron1. This property may partially explain the tolerance observed (see section 7.3.1). Although chlorotoluron and metribuzin belong to two dissimilar chemistries that both act by inhibiting PSII. Phytotoxicity was visually assessed 14 days after herbicide application, which was very early in the development of the cereal plants. In a field experiment, early metribuzin symptoms observed on the metribuzin-sensitive winter wheat cultivar Dozier did not impact significantly on grain weight [257]. Moreover, despite the symptoms, wheat yield was significantly higher compared to the untreated control that was left to compete with the weeds at the set density of 450 ryegrass plants per square metre. Metribuzin cultivar tolerance should be further investigated in order to better determine in which cropping systems the mixtures with prosulfocarb can be implemented.

Mixtures with a partner aﬀected by resistance

The choice of the ALS inhibitor ATL as a prosulfocarb partner may be questioned in terms of resistance management, since European grass weeds

1http://www.nufarm.com/Assets/14955/1/CTUvarietylist2011final2.pdf

183 CHAPTER 7. Prosulfocarb mixtures have evolved resistance to iodosulfuron and mesosulfuron more than to metribuzin, diflufenican or pyroxasulfone (not yet marketed in Europe). A recent modelling study tackled this question by investigating the evolution of resistance in weed populations resistant to one of the components of a binary mixture [258]. Simulations were run for an annual, diploid, out-crossing species and several initial resistance frequencies, which would correspond to the case of 2005 UK 242 only if its resistant trait was monogenic. This is ar- guable as it is believed to be a non-target-site based mechanism. Jacquemin et al. [258] showed that for low efficiency mixtures, e.g. 85% control, 63.3% of the simulations reverted back to sensitivity, suggesting that the lower the efficacy of the mixture, the higher the probability of reducing the frequency of resistance over time. Conversely, for highly efficient mixtures, (99% weed control) only 26.5% of the simulations reverted back to sensitivity. Therefore, mixing a low risk component such as prosulfocarb with an ALS inhibitor may have more desirable effects on resistance management than initially thought.

Mixtures with a newly registered active ingredient

Pyroxasulfone has recently been granted approval in Australia for incorporation at sowing at 100 gai/ha in wheat, triticale and barley crops. Stud- ies have shown that pyroxasulfone provided excellent control on trifluralin resistant populations offering an acceptable solution to affected farmers [244, 245]. Likewise, the present study demonstrated that pyroxasulfone complemented with prosulfocarb successfully controlled multiple-herbicide resistant populations including flufenacet resistance. Solo or in mixture, this new active ingredient has proven to be a partner of choice for managing herbicide resistance. However, as any other new and good molecule, its life-span may be threatened by resistance. A study that aimed to select for rare gene(s) conferring high levels of resistance to pyroxasulfone in two susceptible L. rigidum cultivars by applying 10 times the recommended field rate in sequential applications showed that this event occurred at a low frequency, approx. 4 × 10−6 [246]. This is one to two orders of magnitude lower than the initial frequency of target-site resistance to the ALS inhibitors sulfometuron and imapzapyr in L. rigidum [127]. Inter- estingly, there was no evidence of pyroxasulfone resistance increase in the

184 7.4. Discussion progeny of any of the surviving plants, conﬁrming the low risk of target-site resistance evolution. On the other hand, the same study showed that pyroxasulfone was vulnerable with respect to non-target-site based resistance. After only two cycles of recurrent selection at sub-lethal doses of pyroxasulfone (about 50 gai/ha), the progeny of the susceptible population was not successfully controlled with pyroxasulfone at 90 gai/ha (about 30% survivors). Likewise, cross-resistance patterns were observed with the dissimilar herbicide diclofop-methyl (ACCase inhibitor). In order to preserve pyroxasulfone potential it would seem desirable to promote its use in mixtures with prosulfocarb or any other suitable compound.

A success story for an already marketed prosulfocarb mixture

The prosulfocarb plus S-metolachlor pre-packaged mix (prosulfocarb + S- metolachlor at 800gai/L+120gai/L) has been granted approval for rigid ryegrass and toad rush (Juncus bufonius L.) control in wheat and barley in Australia since 2007 [259]. Prosulfocarb was not used before in Australia and was therefore considered as a new mode of action that could potentially help managing ACCase, ALS and trifluralin resistance in rigid ryegrass. Since then, several studies have demonstrated the usefulness of this mixture to control trifluralin-resistant populations reaffirming the need of having prosulfocarb-based treatments [244, 260].

Prosulfocarb ‘adjuvant’ eﬀect with post-emergence mixtures

A number of post-emergence mixtures with ATL (ALS inhibitors) resulted in high levels of crop phytotoxicity. For instance, more than 30% visual biomass reduction was observed on winter wheat treated with 18 gai/ha (ATL) with any prosulfocarb rate from 2,400 gai/ha. Conversely, prosulfocarb and ATL on their own had minimal effects on cereals (maximum 5% damages for prosulfocarb at 4,000 gai/ha). A study that investigated foliar uptake of prosulfocarb and the ALS inhibitor flupyrsulfuron-methyl applied alone or in mixture showed that prosulfocarb greatly enhanced the uptake of flupyrsulfuron-methyl in wheat and L. multiflorum [261]. The foliar penetration of flupyrsulfuron-methyl in wheat and ryegrass was virtually nonexistent. Prosulfocarb applied alone was absorbed at 30% by wheat leaves and at 3% by ryegrass leaves 72h after application. When

185 CHAPTER 7. Prosulfocarb mixtures

flupyrsulfuron-methyl and prosulfocarb were deposited as mixtures, the foliar uptake of flupyrsulfuron-methyl was about five-fold higher for ryegrass and the increase in penetration for wheat was brought from 1% to 45%. Con- sequently, prosulfocarb may have enhanced ATL leaf penetration resulting in greater crop damages. This feature may potentially help in developing effective mixtures for the control of low levels of non-target-site based resistance to ALS inhibitors but care has to be taken with regards to crop toxicity.

7.5 Conclusions and Perspectives

This chapter showed that metribuzin and diflufenican may be used in winter wheat and winter barley offering a ‘new’ mode of action for ryegrass control in these crops. The prosulfocarb plus pyroxasulfone mixture successfully controlled multiple-herbicide resistant populations including resistance to flufenacet, an emerging concern. Finally, the post-emergence mixture with iodosulfuron:mesosulfuron 1:5 may help to control low levels of non-target- site based resistance to ALS inhibitors. The pre-emergence mixtures rely on the good control offered by prosulfocarb. However, these studies only related to greenhouse conditions, which can be very different to the field, especially so with a pre-emergence compound like prosulfocarb. The aim was to provide insights into the potential of different prosulfocarb mixtures for the control of herbicide-sensitive and resistant ryegrass populations. In- teresting mixtures should now be tested outdoors and subsequently in field trials. Efficacy of ryegrass control might be poorer outside, but phytotoxicity on cereals might be less. Evidence of sensitivity shifts affecting prosulfocarb have been reported in A. myosuroides populations from the UK [145]. Therefore, Chapter8 aims to picture prosulfocarb sensitivity in L. multiflorum by investigating its performances on field populations collected in the UK between 2000 and 2008.

186 8 The distribution of prosulfocarb eﬃcacies on Lolium populations collected in England between 2000 and 2008

8.1 Introduction

Resistance to the post-emergence ACCase and ALS herbicides in ryegrass in the United Kingdom is well-documented and is an increasing threat for effective grass weed control [9, 95, 262]. By 2004, a total of 324 farms were reported as having herbicide resistant Lolium multiflorum Lam. populations [263]. A recent semi-random survey indicated partial resistance to the ALS inhibitors iodosulfuron:mesosulfuron 1:5 (marketed as the pre-packaged mix Atlantis R ) in nine fields out of the 50 sampled [264]. Upon growing resistance to these modes of action, pre-emergence herbicides are recommended [222]. Prosulfocarb is a key compound in programs that are designed to control these ACCase and ALS-resistant ryegrass populations. The previous chapters provided a better understanding of its suitability for such use and showed that (i) prosulfocarb could efficiently contribute to overcoming ACCase resistance in L. multiflorum populations since evidence of negative cross-resistance with respect to ACCase target-site mutations was recorded for GG2078 and RR2088 sublines (Chapter6), (ii) prosulfocarb efficacy was not affected by high levels of non-target-site based resistance to clodinafop (Chapter5), (iii) the repetitive use of prosulfocarb alone resulted in a small but significant shift towards resistance in a susceptible L. multiflorum population, thus promoting prosulfocarb use in mixtures (Chapter4), and that (iv) novel pre-emergence mixtures with metribuzin, diflufenican and pyroxasulfone effectively controlled the few herbicide-sensitive and resistant ryegrass populations tested (Chapter7). However, none of these individual

187 CHAPTER 8. Prosulfocarb efficacies on Lolium samples experiments provided insights into the situation that cereal farmers face today as they were based on specific cases and/or greenhouse selected lines. A survey that would assess the distribution of prosulfocarb efficacies on ryegrass field samples in a key country was thus desirable.

Pre-emergence applications of prosulfocarb under controlled conditions at the maximum labelled rate of 4,000 gai/ha can give variable responses on the susceptible standard L. multiflorum population G0 (visual biomass reduction: min = 61%, max = 98%, mean = 83% and median = 85%, Chapter3). Prosulfocarb can also be applied in post-emergence mixtures [265]. Detecting prosulfocarb resistance in the first place and assessing its evolution and spread can be more difficult than monitoring for ACCase or ALS resistance. Consequently, this study aimed to provide a comprehensive view of prosulfocarb efficacy on ryegrass populations by studying its pre- emergence performances at different rates and comparing its post-emergence efficacy on a collection of L. multiflorum populations from English farm sites.

8.2 Materials and Methods

8.2.1 Seed source, herbicide history and prosulfocarb testing

A collection of ryegrass seeds sampled across England between summers 2000 and 2008 was available at Jealott’s Hill (Syngenta). These populations were suspected resistant to at least one herbicide recently used in the cereal field they originated from. Thirty-four populations were selected based on their germination rate and the amount of seeds available. Consequently, they were not random samples. There was a maximum of five samples per year. Figure 8.1 shows the location and the year of collection for the selected samples. The field history, i.e. crop rotations and herbicide treatments were not available or dated from a maximum of two years. Based on the available information, there was no consistent pattern in grass management programs between fields and locations. Overall, post-emergence grass control was dominated by the ACCase inhibitors pinoxaden and tralkoxydim and ALS inhibitors (pre-packaged mix Atlantis R iodosulfuron:mesosulfuron 1:5). Pre-emergence treatments were more variable and included the use of

188 8.2. Materials and Methods the ureas isoproturon and chlorotoluron before isoproturon approval expired in June 2009. Chlorotoluron alone is under phased revocation and should not be used after August 2011. However, it is still registered until end of December 2021 in the formulated mix with diflufenican for weed management in winter cereals [241]. The other active ingredients used were triallate, trifluralin, pendimethalin and flufenacet. Prosulfocarb was only used once in one field (from which sample 2008 UK 204 originated) for an autumn application at 2,400 gai/ha with a pre-packaged mix of 600 gai/ha pendimethalin plus 120 gai/ha flufenacet. The 34 selected field populations were tested for prosulfocarb efficacy alongside the susceptible standard L. multiflorum population G0. Seeds were sown in 4” pots filled with TMA soil. Three replicate pot units were produced for each treatment. Prosulfocarb was applied pre-emergence at 2,400; 3,200 and 4,000 gai/ha. The experiment was repeated three times leading to a total of nine data points per treatment and populations. A ‘resistant’ and a ‘sensitive’ sub-set consisting each of seven field populations were selected based on the results of this pre-emergence study. The POST efficacy of prosulfocarb at 2,400 gai/ha was evaluated on these 14 populations alongside the susceptible standard population G0. This last experiment was run in triplicate but only once in time. Weed control was visually assessed 21 days after application for each set of experiment.

8.2.2 Data analysis

Weed mapping

The sampling location was supplied in the form of the farm address with or without a postcode. The latitude and longitude was retrieved using the appropriate application from the webpage iTouchMap.com [266]. The coordinates were then transformed into National Grid coordinates (Eastings and Northings) using the Ordnance Survey online coordinate transformer [267] and fed into the blighty package [268] to locate the origin of the ryegrass samples on the England map (Figure 8.1). This gave only approximate locations and targeted the farm house rather than the ﬁeld as the precise GPS coordinates of the weed patch were not available.

189 CHAPTER 8. Prosulfocarb eﬃcacies on Lolium samples

● Newcastle ● 89 ● 91 ●213 ● 167 ●165 ● 316 ● ●171 ●315 ● 240,242 90 70 km ● 88 ● 230 ● 88 ● 205 ● ●217 Manchester

●●212303 ●310 ● ●232 Birmingham ●104 ● 92 ●201 ● ●305 ●217216 ●207Oxford ●304 ●100 ● ●204 ●203301●216233

Figure 8.1: Map of the origin of the 34 ryegrass samples. The colours indicate the sampling year: black=2000, red=2002, green=2003, dark blue=2004, cyan=2005, pink=2006, yellow=2007 and grey=2008. Points outside the maps denote samples for which no geographical information was available. Numbers are batch code. For instance, the point located East of Birmingham and labelled 310 represents a sample harvested in 2004; the full code is 2004 UK 310.

190 8.2. Materials and Methods

Prosulfocarb PRE and POST eﬃcacies

For the three pre-emergence applications, the statistical significance between the mean ranks of weed control amongst the 35 populations tested was evaluated on the basis of the non-parametric Kruskal-Wallis test due to heteros- cedasticity of variance (Fligner-Killeen test, p-value < 0.05 for the three data sets). Multiple comparisons were then performed with the kruskal function of the agricolae package that allows grouping [269]. Any field population significantly less controlled than the susceptible standard population G0 was labelled with the star significance codes (0.05 ‘*’ 0.01 ‘**’ 0.001 ‘***’). The efficacies of prosulfocarb applied PRE and POST at 2,400 gai/ha on the ‘sensitive’ and ‘resistant’ sub-sets were evaluated on the basis of pairwise t-tests with pooled standard deviation using the Benjamini-Hochberg correction for the control of the false discovery rate.

191 CHAPTER 8. Prosulfocarb eﬃcacies on Lolium samples

8.3 Results

8.3.1 Pre-emergence screen

The susceptible standard population G0 was extremely well controlled with prosulfocarb applied PRE from 2,400 gai/ha (visual biomass reduction: mean = 94%, min = 92%, max = 97%). The lowest levels of control at 2,400 gai/ha were recorded for population 2008 UK 212 with an average of 37% (min = 5%, max = 50%). Across all the 34 field populations tested, the average percentage of visual weed control was 84%, which was extremely good. Fifteen field populations were statistically less controlled than G0 based on the kruskal multiple comparisons (Figure 8.2a). At 3,200 gai/ha, the overall control was improved (91%) showing a dose-response effect, but 17 field populations were statistically less controlled than G0 (Figure 8.2b). Populations 2003 UK 305, 2002 UK 104 and 2002 UK 89, that were less controlled than G0 at 2,400 gai/ha were not significantly different from G0 when sprayed with 3,200 g prosulfocarb/ha. Conversely, populations 2006 UK 230, 2005 UK 242, 2006 UK 316, 2003 UK 301 and 2000 UK 100 were recorded as significantly less controlled than G0 both at 2,400 g and 3,200 g prosulfocarb/ha. Finally, at the maximum labelled rate of 4,000 gai/ha, the overall control on the 34 field populations was 94%. Only 11 populations were reported as being significantly less controlled than G0 and six were dropped from 3,200 gai/ha to 4,000 gai/ha namely 2006 UK 230, 2005 UK 242, 2006 UK 316, 2004 UK 310, 2003 UK 301 and 2000 UK 100 (Figure 8.2c). The lowest levels of control were reported again for sample 2008 UK 212 with a mean of 62% (min = 40% and max = 80%). Across the three prosulfocarb rates applied, only seven populations were consistently less controlled than G0 with high significance levels (p-value < 0.001). These field populations, namely 2004 UK 304, 2005 UK 216, 2005 UK 217, 2006 UK 216 and 2008 UK 201/205/212, were selected to constitute the least controlled sub-set called ‘resistant’ as a simplified terminology. These populations were subsequently treated with prosulfocarb applied POST at 2,400 gai/ha in order to evaluate the relationship between reduced prosulfocarb PRE efficacies and POST control. Fourteen field populations were consistently as well controlled as G0. Only seven of them, all harvested between 2003 and 2007 to match the harvest period of the ‘resistant’ sub- set (2004-2008), were selected to constitute the ‘sensitive’ sub-set.

192

8.3. Results

2008.UK.212 *** 2008.UK.207

** 2008.UK.205 *** 2008.UK.204

* 2008.UK.201

*** 2007.UK.203 2006.UK.233

* 2006.UK.230

2006.UK.217

2006.UK.216

*** 2006.UK.213

2005.UK.242

2005.UK.240

2005.UK.232

0.01 and ‘***’ for

2005.UK.217

*** 2005.UK.216

*** 2004.UK.316

2004.UK.315

2004.UK.310

2004.UK.304

*** 2003.UK.305 2003.UK.303

2003.UK.301 4,000 gai/ha

p-value 2003.UK.167

2003.UK.165

2002.UK.92

2002.UK.90 (c)

2002.UK.89

2002.UK.88

2002.UK.104

2000.UK.91

2000.UK.88

2000.UK.171 2000.UK.100

80 60 40 20 100 percentage) (visual control weed

0.01, ‘**’ for 0.001 G0

< 2008.UK.212

*** 2008.UK.207

*** 2008.UK.205

*** 2008.UK.204

*** 2008.UK.201

*** 2007.UK.203

2006.UK.233 *** 2006.UK.230

p-value

* 2006.UK.217

< 2006.UK.216

*** 2006.UK.213 2005.UK.242

** 2005.UK.240

2005.UK.232

2005.UK.217

*** 2005.UK.216 *** 2004.UK.316

* 2004.UK.315

2004.UK.310

*** 2004.UK.304

*** 2003.UK.305

2003.UK.303

*** 2003.UK.301 3,200 gai/ha

*** 2003.UK.167

2003.UK.165

2002.UK.92

2002.UK.90 (b)

2002.UK.89

2002.UK.88

2002.UK.104

2000.UK.91

2000.UK.88

2000.UK.171 2000.UK.100 **

80 60 40 20

100 percentage) (visual control weed

2008.UK.212 *** 2008.UK.207

* 2008.UK.205 *** 2008.UK.204

* 2008.UK.201

*** 2007.UK.203

2006.UK.233

*** 2006.UK.230

2006.UK.217

2006.UK.216

*** 2006.UK.213

2005.UK.242

2005.UK.240

2005.UK.232

2005.UK.217

*** 2005.UK.216

*** 2004.UK.316

2004.UK.315 2004.UK.310

* 2004.UK.304 *** 2003.UK.305

* 2003.UK.303

*** 2003.UK.301 2,400 gai/ha

2003.UK.167

2003.UK.165

2002.UK.92

2002.UK.90 (a)

2002.UK.89 Mean prosulfocarb pre-emergence eﬃcacies (n=9). G0 is the susceptible population. Stars indicate the level of signi-

* 2002.UK.88 2002.UK.104

* 2000.UK.91

2000.UK.88

2000.UK.171 0.001. 2000.UK.100 <

80 60 40 20 100 percentage) (visual control weed p-value Figure 8.2: ficance for the difference between G0 and the field population. ‘*’ for 0.05

193 CHAPTER 8. Prosulfocarb eﬃcacies on Lolium samples

8.3.2 Comparison of pre-emergence and post-emergence eﬃcacies at 2,400 gai/ha on the ‘resistant’ and ‘sensitive’ sub-sets

‘Resistant’ sub-set

Different patterns were observed within the ‘resistant’ sub-set based on comparisons between PRE and POST efficacies (Figure 8.3a). The highest level of control for the POST application of prosulfocarb was recorded for sample 2008 UK 2005 with a mean value of 62%. This was poorer than the standard sensitive population G0 which was controlled at 82%, but not statistically different (p-value = 0.14). There was no significant difference between the PRE and the POST efficacies for sample 2008 UK 205 (p-value = 0.14). All the other samples were significantly less controlled than G0 at the POST level (p-value <0.001) suggesting that the mechanism(s) that resulted in reduced prosulfocarb PRE efficacies had also some impact on the POST efficacies. However, there was no significant difference between the POST and the PRE prosulfocarb efficacies for sample 2008 UK 212 (p-value = 0.38) while differences were recorded for the remaining five populations (p-value <0.001). The largest difference was observed for sample 2008 UK 201 for which, on average there were -65 points of difference between the PRE and the POST applications. Importantly, samples 2004 UK 304, 2005 UK 216, 2005 UK 217, 2006 UK 216 and 2008 UK 201 were much less controlled by the POST application than the PRE application as compared to the susceptible standard population G0. There were on average -71 points of difference for the POST efficacies but only -25 for the PRE efficacies.

‘Sensitive’ sub-set

G0 was slightly less controlled with the POST application than the PRE application (p-value = 0.03, mean PRE = 94%, mean POST = 82%, Figure 8.3b). None of the seven field population was significantly less controlled than G0 at the POST level (p-value >0.17) confirming their sensitivity to prosulfocarb. Pairwise comparisons showed that the only difference at the POST level between the field populations tested was for sample 2005 UK 240 that was significantly less controlled than 2007 UK 203 (p-value = 0.01). The greatest difference between the PRE and POST efficacies was recorded for

194 8.3. Results sample 2005 UK 240 with an average of -20 points. It was only -13 for the susceptible standard G0 and -12 across the eight populations. The ‘sensitive’ sub-set was then divided into two groups, i.e. (1) POST efficacies significantly lower than PRE efficacies for four samples, namely 2005 UK 240 (p-value < 0.001), 2005 UK 232 (p-value = 0.04), 2006 UK 213 (p-value = 0.01) and 2006 UK 217 (p-value = 0.01) and (2) comparable PRE and POST efficacies for remaining three samples, i.e. 2003 UK 167, 2004 UK 325 and 2007 UK 203 (p-value > 0.06). In conclusion, the samples recorded as ‘sensitive’ based on PRE tests were also sensitive at the POST level. This may be generally applied to other field populations. However, it has to be noted that the difference between the PRE and POST efficacies is unpredictable.

8.3.3 Deﬁning sensitivity groups

Three sensitivity groups were then deﬁned based on the PRE and POST screens:

1. sensitive group that comprised the seven populations of the ‘sensitive’ sub-set that were tested PRE and POST and recorded as sensitive as the susceptible standard G0. The other seven samples that were sensitive based on the PRE screen only were also included as a gener- alisation (see above). These 14 samples accounted for 41% of the ﬁeld populations tested.

2. resistant group made of the seven populations from the ‘resistant’ sub-set (20% of the samples tested).

3. partially resistant group that consisted of all the remaining populations that were signiﬁcantly less controlled than G0 for at least one PRE treatment but not evaluated at the POST level (39% of the samples tested).

8.3.4 Weed resistance mapping

The results from prosulfocarb monitoring were reported on the England map (Figure 8.4). Regardless of the sampling year, the prosulfocarb-sensitive populations were mostly located North of Manchester and at the East of a line Manchester-Newcastle (Yorkshire). In this area, eight samples out of

195 CHAPTER 8. Prosulfocarb eﬃcacies on Lolium samples h ieec ewe w en,buddb 0.Sadr roswr acltdsprtl o R n OTapplications. are POST bars and error PRE the for and separately PRE) calculated for were n=9 errors and Standard POST 100. for by (n=3 bounded value mean means, two the between are diﬀerence bars the Main G0. population standard 8.3: Figure

weed control (visual percentage) 100 20 40 60 80 0

rsloabecce ple R n OTa ,0 a/ao h rssat n sniie u-esadtesusceptible the and sub-sets ‘sensitive’ and ‘resistant’ the on gai/ha 2,400 at POST and PRE applied eﬃcacies Prosulfocarb 2004.UK.304

2005.UK.216 (a)

Rssat sub-set ‘Resistant’ 2005.UK.217 POST 2006.UK.216

2008.UK.201 PRE

2008.UK.205

2008.UK.212

weed control (visual percentage) 100 20 40 60 80 0

2003.UK.167 POST

2004.UK.315 PRE (b)

2005.UK.232 Sniie sub-set ‘Sensitive’

2005.UK.240

2006.UK.213

± 2006.UK.217 tnaderrof error standard 1

2007.UK.203

196 8.3. Results nine were sensitive. The resistant cases were mostly located in the Norfolk, Suffolk and Essex counties where five cases were reported. In general, there were fewer sensitivity cases south of Manchester with a total of three out of 18 samples. Regardless of the origin of the samples, the resistant populations were first detected in 2004 (Figure 8.5). The proportion of sensitive samples tested decreased as years of collection increased. There was an exception in year 2007 since only one sample was tested and recorded as sensitive.

● Newcastle ● ● 2000UK91,2003UK167,2005UK240 ● ● 2004UK316,2005UK242,2006UK230 ● 2008UK205 ● ● ● 70 km ● ● ● ● Manchester

●● ● ● ● Birmingham ● ● ● x2 ● ● ● ● Oxford ● ● ● ● ● ●●

Figure 8.4: English map of prosulfocarb eﬃcacies. Green solid circles represent the prosulfocarb-sensitive populations, orange solid circles the populations that were partially resistant and the red circles the populations recorded as resistant based on both PRE and POST prosulfocarb screens. Points outside the maps denote samples for which no geographical information was available. Sample 2008 UK 205 that was as well controlled as the susceptible reference G0 at the POST level is coded with a red star.

197 CHAPTER 8. Prosulfocarb eﬃcacies on Lolium samples

1.0 1.0

0.8 0.8

0.6 0.6

0.4 0.4

0.2 0.2

n=4 n=5 n=5 n=4 n=5 n=5 n=1 n=5 n=9 n=18 n=7 0.0 0.0

2000 2002 2003 2004 2005 2006 2007 2008 north south unknown

Figure 8.5: Proportion of resistant (red), sensitive (green) and partially resistant (orange) samples per year of sampling and location. The total number of populations tested per factor level is indicated at the bottom of the bars. The north location refers to any samples collected north of Manchester and the south location to any sample collected south of Manchester (see Figure 8.4).

198 8.4. Discussion

8.4 Discussion

This mapping exercise showed the regional distribution of ryegrass sensitivity to prosulfocarb in England across almost a decade of sampling (2000- 2008). The ryegrass samples did not originate from a random survey as they were collected after herbicide failure (not prosulfocarb). This may have biased sampling. Most ryegrass populations were very well controlled (average 94% with PRE applications at 4,000 gai/ha). Nevertheless, there was some variability amongst the field populations tested with gradual levels of reduced efficacies. Sample 2008 UK 212 was the least controlled and considered as prosulfocarb-resistant. Three sensitivity groups to prosulfocarb were defined, namely ‘sensitive’, ‘resistant’ and ‘partially resistant’. Southern regions were more affected by resistance than Northern regions. The first resistance case was recorded for a 2004 sample from Essex (2004 UK 304). Cases of resistant populations has not increased since 2004.

At which level should a ryegrass population be declared resistant to prosulfocarb?

This rather simple question raises several other issues that were tentatively addressed in the present study. Heap [110] recommends for initial characterisation of a putative resistant sample to (i) conduct dose-response experiments under controlled environments with whole plants using a susceptible population of reference and to (ii) determine the resistance factors as ratios of ED50 or GR50 values. Inevitably this falls into a scientific definition of resistance as it does not take into account the recommended field rate of the herbicide [110]. Ryegrass populations were reported resistant to triallate under this scientific definition while they were controlled at the recommended field rate (refer to Chapter3 and [50, 74]). There were not enough seeds available for each and every population tested in this study to conduct repeated dose-responses at the PRE and POST growth stages. That is why only the prosulfocarb rates of agricultural relevance were investigated (2,400 gai/ha for PRE and POST applications; 3,200 and 4,000 gai/ha for PRE only) and the results subjected to a statistical analysis. Another approach would be to evaluate the differences between the putative resistant populations and the average response from numerous sensitive samples. In other terms, to firstly conduct a baseline study. According to

199 CHAPTER 8. Prosulfocarb efficacies on Lolium samples the European and Mediterranean Plant Protection Organization, sensitivity data may be considered as baseline if it is obtained from pest population(s) that have not been exposed to the plant protection product or to related active substances of the same cross-resistance group and so have never been subjected to any relevant selection pressures, and if the pest population(s) concerned show no metabolic resistance to the product [270]. Given the widespread use of herbicide in Europe and the resistance status of ryegrass species, finding such populations in the wild is a great challenge. Com- mercially available ryegrass seeds seem to be the best option to ascertain susceptibility even though limited choice is offered. Another issue with the baseline study lays in prosulfocarb behaviour itself. Indeed, PRE applications even under controlled conditions and at 4,000 gai/ha result in test-to-test variations (see Chapter3). Therefore, the baseline study would also have to account for these variations complicating the resistance testing process. Finally, the establishment of a baseline does not, in itself, resolve the issue of differentiating between resistance and susceptibility. It is the researcher who decides where to put this level. For instance, a baseline sensitivity study carried out to monitor the response of Papaver rhoeas L. to a newly registered ALS inhibitor arbitrarily considered that a sample was resistant if the difference with the baseline was greater than 3-fold [271]. With this definition, a mixed population (presence of genuinely resistant individuals and susceptible plants) may be recorded as sensitive. It does not account either for possibly low shift towards resistance conferred by (i) target-site resistance, as observed for glyphosate [66] or (ii) creeping resistance, as observed for prosulfocarb or other compounds [272] (Chapter4). Finally, although recommended by Heap [110], greenhouse tests may miss some cases of partial resistance as prosulfocarb is known to give variable control under glass (Chapter3). Trials conducted in the farm sites are clearly the more realistic conditions but populations cannot be compared and it lacks of a standard sensitive population and an untreated control. Outdoor containers would allow a much better appraisal of impact of resistance on efficacy [145]. However, it (i) increases the time allocated for a single experiment and (ii) does not allow full year-to-year comparisons between tests. The use of several rates in the greenhouse is therefore one way round the problem. Consequently, the present study aimed to investigate the aforementioned

200 8.4. Discussion aspects and proposed to characterise prosulfocarb resistance under a greenhouse environment based on a combination of an objective scientific definition and an agricultural definition of resistance to provide sensitivity groups of practical relevance.

The sensitivity map matches well the distributions of cereal crops and weed infestation in England

Cereal crops (wheat, barley, oats, rye) make up almost 80% of the total area cropped in the UK [273]. Wheat is the most widely grown crop covering 1.9 million hectares for a harvested production of 18.8 million tons in 2010 [21]. The wheat main production zone is centre-east (Figure 8.6a). The distribution of ryegrass as identified by surveyed farmers as being a weed they need to control goes with the main cereals distribution (Figure 8.6b). In the North and West there is progressively less problem with ryegrass as an arable weed than in the East and South [274]. The intensity of graminicide use on cereals drops as this species is no longer the main target (Jason Tatnell, personal communication). More herbicide pressure in the Eastern regions may therefore explain the dominance of less sensitive prosulfocarb ryegrass populations. An accurate time-dependent picture of prosulfocarb efficacies in cereal fields across England was difficult to draw mainly due to the low number of population tested in this study. The likelihood of prosulfocarb resistance evolution and spread as being a major threat for farmers in the South could only be assessed with a larger number of samples repeatedly collected in given fields over more than five consecutive years.

Reduced prosulfocarb eﬃcacies are probably not a consequence of repetitive prosulfocarb applications

Some of the samples harvested from 2004 onwards showed resistance to prosulfocarb. Despite the missing herbicide history from the sampled farms, it is very unlikely that prosulfocarb was repeatedly applied over the previous years at all these locations, simply because prosulfocarb was not widely used. Data for 1990 to 2010 from the programme of pesticide usage surveys com- missioned by the independent Advisory Committee on Pesticides showed records of prosulfocarb usage in the UK in all crops (including cereals) from only 2006 [276]. Prosulfocarb was applied on only 1% of the total area of

201 CHAPTER 8. Prosulfocarb eﬃcacies on Lolium samples

(a) Wheat distribution according to (b) Values in each coloured region HGCA [275]. is the estimated area in hectares infested by ryegrass based on farmers reports that identiﬁed ryegrass as a weed that need to be controlled [13].

Figure 8.6: Wheat and ryegrass distributions. cereals treated in those years while pendimethalin was stable at 8% and flufenacet grew from 4% in 2006 to 9% in 2010 [276]. Therefore, resistance evolution due to extensive use of prosulfocarb is unlikely. Chapter4 showed that under greenhouse conditions, three cycles of prosulfocarb recurrent selection with a susceptible population resulted in only small shifts towards resistance that had little to no impact at practical field rates. Secondly because prosulfocarb selection pressure on buried seeds is likely to be minimal. Indeed, several studies either based on long-term field experiments or adsorption on model soils (e.g. colloids, biobed) showed that prosulfocarb was (i) not prone to leaching and only detectable in the soil top layer (up to 25 cm) and (ii) readily degradable by the soil microflora [148, 277– 279]. Therefore, soil accumulation and contamination by prosulfocarb is very unlikely suggesting that seeds located further down into the soil profile had little chance to have been in prolonged contact with prosulfocarb or its metabolites. Therefore resistance evolution in 2004 UK 304 and the more recent samples is more likely to have been selected by other compounds.

202 8.4. Discussion

Indeed, cases of resistance evolution to a given herbicide in populations that were not previously exposed to it in the field are common [50]. This feature represents a major threat for sustainable chemical weed control and herbicide discovery. It is easily conceivable that target-site based resistance may be responsible for cross-resistance to a novel molecule that inhibits the same target. This was observed for the ALS inhibitor pyroxsulam which was the first triazolopyrimidine to be registered for grass control in cereals and yet affected by the W574L mutation in L. rigidum [106]. Non-target- site based resistance mechanisms can also confer unpredictable resistance profiles to dissimilar compounds as it has been observed for the three most recently registered cereal compounds, i.e. pinoxaden, pyroxsulam and pyroxasulfone [92, 170, 246]. For instance Petit et al. [92] showed that some blackgrass populations resistant to fenoxaprop-P-ethyl were cross-resistant to pinoxaden but sensitive to clodinafop while some others were resistant to clodinafop, sensitive to fenoxaprop-P-ethyl and resistant to pinoxaden, thus highlighting the variability of impact of non-target-site based resistance mechanisms. As prosulfocarb target-site based resistance is unlikely, very probably due to the suspected multiple targets (Chapter4), the evolution of resistance is much more likely to be non-target-site mediated. Chapter5 suggested that the repetitive application of clodinafop did not lead to prosulfocarb resistance. However, this does not mean that ACCase inhibitors in general did not have any influence on prosulfocarb resistance evolution in other populations. Evaluating the importance of each and every single past and present registered compound on prosulfocarb resistance evolution in the identified resistant samples would be tedious and would provide only partial information as it would just picture the situation at the time of testing and not give information on the evolutionary process.

What are the practical consequences of prosulfocarb reduced eﬃcacies?

For growers The occurrence of resistance to prosulfocarb may potentially hamper the current recommendations and programs for pre-emergence grass control in cereals. Local solutions should be promoted rather than global strategies to better tackle farmers’ problems as it is of critical importance to detect resistance to prosulfocarb at as early a stage as possible.

203 CHAPTER 8. Prosulfocarb eﬃcacies on Lolium samples

This implies that farmers make the effort to regularly monitor their fields especially when resistance has not been detected yet, which can be costly both in time and financially [222]. Precise and up-to-date herbicide application record sheets would also allow to determine the impact of resistance to prosulfocarb versus other herbicides in the field. Finally, growers still have to be encouraged to use non-chemical methods of control, i.e. crop rotations, inter-row cultivation, delayed drilling, choice of competitive cultivars, etc, etc. These first cases of reduced efficacies to prosulfocarb should not be ignored as the longer term consequences may be more problematic. More than 30 years after the first reports of triazine resistance in the UK and despite the fact that atrazine and simazine are no longer registered, partial resistance to related chemistries is still relevant today [54, 241, 264]. This may have contributed to the development of herbicide multiple resistance mechanisms. By definition resistance is an inheritable trait, although there have been some evidence of unconventional genetic mechanisms underlying resistance, such as differential responses between a mother plant and its cuttings (clones) or epigenetic effects [253, 280]. In any event, once reported in a field and due to the sessile nature plants, resistance is unlikely to disappear by itself and can only be wisely managed to limit (i) resistant gene flow by pollen, (ii) the spread of resistant seeds by anthro- pogenic means, e.g. unclean machinery or birds and (iii) the accumulation of resistant seeds in the seed bank [171, 172, 281]. Ryegrass matures more or less simultaneously as its companion crop. Therefore, potential resistant seeds of uncontrolled plants will return to the field and the soil seed bank at harvest. Chaff carts attached to the harvester can efficiently minimise this return. This has been successfully implemented in the Australian grain belt where, on average, 75% of the ryegrass seeds can be removed [282]. A similar approach was tested in France. A study claimed to retain 97% of the weed seeds without significantly affecting the organic matter resources that would have been incorporated into the field without the removal of the chaff [283].

For prosulfocarb sustainable use Five populations of the ‘resistant’ sub-set studied were six times less controlled by the POST application at 2,400 gai/ha than the PRE application (when taking into account the 1.14

204 8.5. Conclusions and Perspectives shift observed for the susceptible standard population). This questions the use of prosulfocarb in POST mixtures for ryegrass control especially when the mixing partner is an ACCase inhibitor for which numerous cases of resistance have been reported. The impact at the pre-emergence level was less marked. On average, 82% visual weed control was reported for the ‘resistant’ sub-set at 4,000 gai/ha as compared to 97% for the susceptible standard G0 and 96% for the ‘sensitive’ sub-set. This greenhouse study conﬁrms the suitability of prosulfocarb to control Lolium populations at the pre-emergence level.

For testing services Resistance monitoring is more powerful when field populations are tested against susceptible and resistant standards. The resistant standard populations should ideally be profiled at the molecular and enzymatic levels. SLR31 is a useful reference for ryegrass profiling but is sensitive to prosulfocarb (Chapter3). This study provides a unique opportunity to include one or more prosulfocarb-resistant populations in future monitoring experiments.

8.5 Conclusions and Perspectives

This greenhouse study is the first report of prosulfocarb resistance in field populations. However prosulfocarb remains a good tool for early-grass control and should not be disregarded, especially in regions where resistance has not occurred yet. Local strategies should be implemented to maximise the effect of chemical weed control in a given field. The resistant populations identified could be included in monitoring experiments as ‘resistant standards’ in order to better evaluate and rank the extent of resistance in the newly tested populations. These samples are also good candidates for the elucidation of underlying resistance mechanisms to prosulfocarb. As non-target-site based resistance is suspected, a first approach could be to compare the bio-activation rate between sensitive and resistant populations. This mechanism has been identified to confer triallate resistance in wild oats [52].

205 9 Summary, Discussion and Directions for further research

Post-emergence grass control in small grain cereal crops is currently predominantly achieved with herbicides that inhibit the enzymes acetolactate synthase (ALS) and acetyl-CoA carboxylase (ACCase). Their extensive use over the past 30 years has resulted in the development and spread of herbicide resistance. Consequently, herbicide programs and sequences involving pre-emergence compounds like prosulfocarb are increasingly used in order to suppress as many weeds as possible as early as possible in the season and thus relieve the pressure put on ACCase and ALS inhibitors.

Prosulfocarb was developed in the 1980’s [143]. It is a broad-spectrum compound that controls major grass and broad-leaved weeds in a wide range of cropping systems including potatoes and cereals. It can be applied pre-emergence, post-emergence or incorporated by sowing at up to 4,000 gai/ha. The exact biological target of prosulfocarb remains unknown but it is thought to impair the biosynthesis of very long chain fatty acids by inhibiting the elongase multi-enzyme complex.

Through an integrated biological (greenhouse-based experiments), biochemical and molecular approach, the research described in this thesis con- tributes towards a more sustainable use of herbicides by studying how prosulfocarb could be integrated for ryegrass management in cereal crops. Re- sistance to prosulfocarb in ryegrass was not documented before this present work [110].

Prosulfocarb performance as a ryegrass-killer is inﬂuenced by experimental conditions. The higher the temperature in the greenhouse,

206 the phytotrons or outdoors, the higher the volatility of prosulfocarb, the lower the activity against ryegrass. Soil composition and texture, e.g. indigenous microflora composition; organic matter, sand and clay content; presence of clods as well as test formats also influence prosulfocarb efficacy (described and discussed in Chapter3 and8). Consequently, prosulfocarb bioavailability for ryegrass control can vary on a test-to-test basis, which is easily noticeable on a susceptible standard population. Detecting prosulfocarb resistance and assessing its evolution is more difficult than monitoring for ACCase or ALS resistance. Chapter8 provides some guidelines for prosulfocarb monitoring under a greenhouse environment. In any prosulfocarb screening assay, it is recommended to test at least three pre-emergence and one post-emergence rates, include a susceptible standard population and at least one resistant reference population. One of the seven prosulfocarb- resistant populations identified in the UK should be used in order to fully appraise prosulfocarb behaviour and adequately assign a sensitivity group to the field populations studied. The sand bioassay (see section 4.3.2) was designed to detect any small shifts towards resistance that are more pronounced at low prosulfocarb dosages and is therefore recommended when a more precise profile is required.

The evolution of prosulfocarb resistance following repetitive application in the field may be extremely slow. This justifies prosulfocarb use for the management of susceptible and resistant ryegrass populations to ACCase and ALS inhibitors (Chapter4). Prosulfocarb is not a total herbicide. Survivors may carry genes endowing resistance that could accumulate over time. The potential of prosulfocarb to select for phenotypic variations that would result in the development of resistance in the susceptible standard Lolium multiflorum Lam. population was investigated via a greenhouse recurrent selection process at 4,000 gai/ha (BBCH03, soil). After three cycles of selection, the sand bioassay showed a small but significant shift towards resistance, i.e. 1.66-fold (95% CI = 1.36 - 2.03) for visual damages and 1.96-fold (95% CI = 1.64-2.34) for survival. However, there was minimal impact at the practical field rate of 4,000 gai/ha (soil experiment). It cannot be excluded that the resistance shifts observed were only the consequences of the experimental design. Prosulfocarb survivors are more likely to be genuine escapes as a consequence of uneven exposure.

207 CHAPTER 9. Summary, Discussion and Directions for further research

Elucidation of the degradation pathway of prosulfocarb in ryegrass would help to conﬁrm this hypothesis. Inﬂuence of other herbicides on selection for resistance to prosulfocarb cannot be excluded and should be investigated in greater details.

The repetitive use of prosulfocarb does not confer either resistance or increased sensitivity to the dissimilar herbicides clodinafop and ‘Experimental Compound X’ as demonstrated with the recurrent selection process (Chapter4). Nevertheless, there was a significant reduction in the number of survivors after the POST application of the ALS inhibitor iodosulfuron (BBCH11-12; iodosulfuron applied at 1.25 gai/ha; Fisher’s exact test for count data p-value = 0.001). The small shift towards prosulfocarb resistance reported above may be due to a metabolic loss of function. This feature has already been reported for triallate resistance in wild oat populations from Canada that exhibited impaired prosulfocarb activation into the sulfoxide form [52]. The current data suggest that iodosulfuron and prosulfocarb may have some similar metabolic processes. More prosulfocarb cycles may be necessary to detect any significant effects on clodinafop and ‘Experimental Compound X’. Similarly, other ACCase and ALS-inhibiting herbicides should be investigated. Fitness costs in the absence of any herbicide pressure as a result of the recurrent selection process should also be evaluated. Indeed, pleiotropic effects that would result in less vigorous plants compared to the initial susceptible population may affect weed distribution and resistance frequency in the event of crop rotations or fallow years.

The selection of prosulfocarb resistance following the repeated use of the ACCase inhibitor clodinafop is unlikely (Chapter5). Non-target-site based resistance (NTSR) to clodinafop in recurrently selected progenies did not confer cross-resistance to prosulfocarb. RF50 values were estimated at 0.91 (95% CI = 0.78-1.06) for visual damages and at 0.54 (95% CI = 0.43-0.68) for survival between the first-selected progeny and the third one. More populations with different ACCase-NTSR profiles should be studied in order to fully justify the use of prosulfocarb for the control of ACCase-resistant populations. The potential of ALS and PSII inhibitors affected by enhanced degradation processes to select for prosulfocarb

208 resistance should also be investigated.

Prosulfocarb exerts negative cross-resistance effects of low relevance for ACCase-target-site resistance management (Chapter6). The potential of prosulfocarb to control pure homozygous mutant sublines better than to wild-types was investigated with four mutations known to confer resistance to the three classes of ACCase-inhibitors currently marketed for grass weed control in cereals. Low negative cross-resistance (NRC) effects were noticeable on the basis of RF50 values (emergence reduction, soil assay), i.e. 0.92 for I1781L, 0.61 for W1999S, 0.68 for D2078G and 0.50 for C2088R. However, these did not confer any competitive advantage at the practical field rate of 4,000 gai/ha. The detection of the NCR effects may depend on the experimental conditions (greenhouse vs. field) as observed by Jordan et al. [208]. Therefore, the usefulness of the prosulfocarb-NCR effects to specifically control these ACCase-resistant sublines should be further investigated under field conditions. Although fitness costs were not reported for mutations that predominantly confer resistance to FOP molecules presuming low prosulfocarb-NCR effects, these substitutions should also be studied [176].

Prosulfocarb can be mixed with other herbicides (Chapter7). The partners studied were metribuzin (PSII inhibitor), diﬂufenican (PDS inhibitor), the pre-packaged mixture Atlantis R {iodosulfuron+mesosulfuron 1:5} (abbreviated as ATL, ALS inhibitors) and pyroxasulfone (VLCFAs synthesis inhibitor). It has to be noted metribuzin is not registered on its own for grass control in cereals in Europe due to phytotoxicity issues. A total of 96 diﬀerent prosulfocarb-based mixtures were tested under the greenhouse. Only 11 provided acceptable levels of control on the susceptible and resistant ryegrass populations studied with minimal phytotoxicity on winter wheat (cv. Hereward) and winter barley (cv. Suzuka). Some of these mixtures exerted very high levels of synergism justifying the use of mixtures in weed management programs. The PRE mixture prosulfocarb+pyroxasulfone at 3,200 gai/ha+64 gai/ha showed a competitive edge over the compounds alone for the control of multiple herbicide-resistant populations. In post-emergence mixtures prosulfocarb may play the role of an adjuvant

209 CHAPTER 9. Summary, Discussion and Directions for further research enhancing the leaf penetration of other active ingredient possibly resulting in crop damages as observed for some prosulfocarb+ATL mixtures [261]. Field experiments are required to determine whether the phytotoxicity levels observed under the greenhouse have signiﬁcant yield consequences. In the presence of a high weed density with plants exhibiting some levels of resistance to ACCase inhibitors the crop losses due to a slightly higher phytotoxicity of a prosulfocarb+ATL mixture may be less detrimental to the farmer than a safer treatment with a lower eﬃcacy. This notion should be integrated in the current herbicides programs and recommendations.

Most of the ryegrass populations from the UK are sensitive or only partially resistant to prosulfocarb. The precise determination of prosulfocarb resistance should be based on the establishment of a sensitivity baseline with unselected populations [270]. However, most of the samples sent to testing centres are suspected to be resistant to chemicals of at least one mode of action. Therefore, in this study, the establishment of prosulfocarb sensitivity groups was based on (i) efficacy screens at different practical field rates including a post-emergence application and (ii) one commercial susceptible standard population. Forty-one percent of the samples tested were sensitive to prosulfocarb, 39% showed signs of partial resistance and 20% were considered as truly resistant. Resistance was of greatest importance at the post- rather than pre-application, with more than six-fold shift in efficacy. Small but significant shifts were observed pre- emergence. For instance, 82% visual damage was recorded for the resistant group compared to 97% for the sensitive group at 4,000 gai/ha. Resistance detection is vital to ensure the sustainable use of herbicides so that counter measures such as chemical rotation can be introduced in a timely manner. The demand for proactive tests that quickly detect resistance before herbicide application is increasing. The design of reliable and cost-effective diagnostic tests is greatly assisted by a knowledge of the resistance mechanism [reviewed in 112]. Having ryegrass populations affected by reduced prosulfocarb efficacies that show differential patterns, e.g. PRE vs. POST applications is a step towards the establishment of such methods. Precision farming may also help to sustain herbicide use. The knowledge of the spatial weed distribution in a field combined with site specific treatment is well-known now to reduce herbicide inputs and provide substantial cost

210 savings to the grower [284]. The selection pressure exerted by the herbicide as defined by Putwain [120] as being the product of herbicide efficacy and soil persistence is considerably lowered. One can now envisage a device that would detect whether the targeted group of plants is resistant to a given class of herbicides. Thanks to non-destructive portable optical sensors that use dual chlorophyll fluorescence excitation to estimate both composition and concentration of UV-absorbing compounds in the epidermal cell layer of leaves, we may not be far from that state of affairs [285]. Target-site based resistance to PSII inhibitors endowed by the S264G substitution in the D1 protein results in overall lower carbon assimilation in the mutant plants [195, 207]. The biosynthesis of phenolic compounds may be affected resulting in differential biopatterns between the resistant and susceptible plants that can be optically assessed.

Taken overall there are encouraging prospects for prolonging the period of eﬃcacy of key herbicides by using strategies such as negative cross- resistance, synergism between pairs of chemicals, and ﬁnding new uses for older compounds such as prosulfocarb which is relatively stable in the face of evolving resistance.

211

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