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Rapid Evolution of Herbicide Resistance by Low Herbicide Dosages

Published online by Cambridge University Press:  20 January 2017

Sudheesh Manalil ,
Roberto Busi ,
Michael Renton  and
Stephen B. Powles
Sudheesh Manalil
Affiliation:
Australian Herbicide Resistance Initiative, The University of Western Australia, 35 Stirling Highway, 6009-Crawley, Western Australia Kerala Agricultural University, Kerala, India- 680654
Roberto Busi
Affiliation:
Australian Herbicide Resistance Initiative, School of plant biology, Institute of Agriculture, The University of Western Australia, 35 Stirling Highway, 6009-Crawley, Western Australia
Michael Renton
Affiliation:
Australian Herbicide Resistance Initiative, School of plant biology, Institute of Agriculture, The University of Western Australia, 35 Stirling Highway, 6009-Crawley, Western Australia
Stephen B. Powles*
Affiliation:
Australian Herbicide Resistance Initiative, School of plant biology, Institute of Agriculture, The University of Western Australia, 35 Stirling Highway, 6009-Crawley, Western Australia
*
Corresponding authors's E-mail: stephen.powles@uwa.edu.au
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Abstract

Herbicide rate cutting is an example of poor use of agrochemicals that can have potential adverse implications due to rapid herbicide resistance evolution. Recent laboratory-level studies have revealed that herbicides at lower-than-recommended rates can result in rapid herbicide resistance evolution in rigid ryegrass populations. However, crop-field-level studies have until now been lacking. In this study, we examined the impact of low rates of diclofop on the evolution of herbicide resistance in a herbicide-susceptible rigid ryegrass population grown either in a field wheat crop or in potted plants maintained in the field. Subsequent dose–response profiles indicated rapid evolution of diclofop resistance in the selected rigid ryegrass lines from both the crop-field and field pot studies. In addition, there was moderate level of resistance in the selected lines against other tested herbicides to which the population has never been exposed. This resistance evolution was possible because low rates of diclofop allowed substantial rigid ryegrass survivors due to the potential in this cross-pollinated species to accumulate all minor herbicide resistance traits present in the population. The practical lesson from this research is that herbicides should be used at the recommended rates that ensure high weed mortality to minimize the likelihood of minor herbicide resistance traits leading to rapid herbicide resistance evolution.

Keywords

Diclofoprigid ryegrass, Lolium rigidum Gaud. LOLRIwheat, Triticum aestivum LCross-resistancefield selectionreduced herbicide rate
Type
Weed Management
Information
Weed Science , Volume 59 , Issue 2 , June 2011 , pp. 210 - 217
Copyright
Copyright © Weed Science Society of America 

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References

Literature Cited

Anderson, J. J., Priester, T. M., and Shalaby, L. M. 1989. Metabolism of metsulfuron methyl in wheat and barley. J. Agr. Food. Chem. 37:1429–1434.CrossRefGoogle Scholar
Bayer, . 2010. Bayer crop science. http://www.bayercropscience.com. Accessed: January 10, 2010.Google Scholar
Beckie, H. J. 2006. Herbicide-resistant weeds: management tactics and practices. Weed. Technol. 20:793–814.CrossRefGoogle Scholar
Blackshaw, R. E., O'Donovan, J. T., Harker, K. N., Clayton, G. W., and Stougaard, R. N. 2006. Reduced herbicide doses in field crops: a review. Weed Biol. Manag. 6:10–617.Google Scholar
Busi, R. and Powles, S. B. 2009. Evolution of glyphosate resistance in a Lolium rigidum population by glyphosate selection at sublethal doses. Heredity. 103:318–325.Google Scholar
Christopher, J. T., Preston, C., and Powles, S. B. 1994. Malathion antagonizes metabolism-based chlorsulfuron resistance in Lolium rigidum . Pestic. Biochem. Phys. 49:172–182.Google Scholar
Darmency, H. 1994. Genetics of herbicide resistance in weeds. Pages 263–295 in Powles, S. B., and Holtum, J. A. M., eds. Herbicide Resistance in Plants: Biology and Biochemistry. Boca Raton, FL Lewis.Google Scholar
de Prado, J. L., Osuna, M. D., Heredia, A., and de Prado, R. 2005. Lolium rigidum, a pool of resistance mechanisms to ACCase inhibitor herbicides. J. Agr. Food. Chem. 53:2185–2191.CrossRefGoogle ScholarPubMed
Doyle, P. and Stypa, M. 2004. Reduced herbicide rates—a Canadian perspective. Weed. Technol. 18:1157–1165.Google Scholar
ffrench-Constant, R. H., Daborn, P. J., and Le Goff, G. 2004. The genetics and genomics of insecticide resistance. Trends. Genet. 20:163–170.CrossRefGoogle ScholarPubMed
Forthoffer, N., Helvig, C., Dillon, N., Benveniste, I., Zimmerlin, A., Tardif, F., and Salaun, J. P. 2001. Induction and inactivation of a cytochrome P450 conferring herbicide resistance in wheat seedlings. Eur. J. Drug Metab. Ph. 26:9–16.CrossRefGoogle ScholarPubMed
Groeters, F. R. and Tabashnik, B. E. 2000. Roles of selection intensity, major genes, and minor genes in evolution of insecticide resistance. J. Econ. Entomol. 93:1580–1587.CrossRefGoogle ScholarPubMed
Hall, L. M., Holtum, J. A. M., and Powles, S. B. 1994. Mechanism responsible for cross resistance and multiple resistance. Pages 243–261 in Powles, S. B., and Holtum, J. A. M., eds. Herbicide Resistance in Plants: Biology and Biochemistry. Boca Raton, FL Lewis.Google Scholar
Heap, I. 2010. The International Survey of Herbicide-Resistant Weeds. http://www.weedscience.org. Accessed: January 25, 2010.Google Scholar
Hidayat, I. and Preston, C. 2001. Cross-resistance to imazethapyr in a fluazifop-P-butyl-resistant population of Digitaria sanguinalis . Pestic. Biochem. Phys. 71:190–195.Google Scholar
Jasieniuk, M., BruleBabel, A. L., and Morrison, I. N. 1996. The evolution and genetics of herbicide resistance in weeds. Weed. Sci. 44:176–193.CrossRefGoogle Scholar
Knezevic, S. Z., Streibig, J. C., and Ritz, C. 2007. Utilizing R software package for dose–response studies: the concept and data analysis. Weed. Technol. 21:840–848.CrossRefGoogle Scholar
Letouze, A. and Gasquez, J. 2003. Enhanced activity of several herbicide-degrading enzymes: a suggested mechanism responsible for multiple resistance in blackgrass (Alopecurus myosuroides Huds.). Agronomie. 23:601–608.CrossRefGoogle Scholar
Manalil, S. 2010. Measurement and Modelling of Herbicide Resistance Evolution in Lolium rigidum at Low Rates of Herbicide Application. PhD dissertation. Crawley, Western Australia The University of Western Australia. 183 p.Google Scholar
McKenzie, J. A. 2000. The charecter or the variation: the genetic analysis of the insecticide resistance phenotype. B. Entomol. Res. 90:3–7.CrossRefGoogle ScholarPubMed
McKenzie, J. A. and Batterham, P. 1994. The genetic, molecular and phenotypic consequences of selection for insecticide resistance. Trends. Ecol. Evol. 9:166–169.Google Scholar
Neve, P. 2007. Challenges for herbicide resistance evolution and management: 50 years after Harper. Weed. Res. 47:365–369.Google Scholar
Neve, P. and Powles, S. B. 2005a. High survival frequencies at low herbicide use rates in populations of Lolium rigidum result in rapid evolution of herbicide resistance. Heredity. 95:485–492.CrossRefGoogle ScholarPubMed
Neve, P. and Powles, S. B. 2005b. Recurrent selection with reduced herbicide rates results in the rapid evolution of herbicide resistance in Lolium rigidum . Theor. Appl. Genet. 110:1154–1166.CrossRefGoogle ScholarPubMed
Owen, M. J., Walsh, M. J., Llewellyn, R. S., and Powles, S. B. 2007. Widespread occurrence of multiple herbicide resistance in Western Australian annual ryegrass (Lolium rigidum) populations. Aust. J. Agr. Res. 58:711–718.Google Scholar
Powles, S. B. and Yu, Q. 2010. Evolution in action:plants resistant to herbicides. Annu. Rev. Plant. Biol. 61:317–347.Google Scholar
Preston, C. 2004. Herbicide resistance in weeds endowed by enhanced detoxification: complications for management. Weed Sci. 52:448–453.CrossRefGoogle Scholar
Renton, M. 2009. The weeds fight back: Individual-based simulation of evolution of polygenic resistance to herbicides. Pages 574–580 in Anderssen, R. S. Braddock, R. D., and Newham, L. T. H., 18th World IMACS Congress and MODSIM09. International Congress on Modelling and Simulation. MSSANZ and IMACS, http://www.mssanz.org.au/modsim09/.Google Scholar
R Development Core Team. 2009. R: A language and environment for statistical computing. R foundation for statistical computing- http://www.R-project.org. Accessed: November 25, 2009.Google Scholar
Ritz, C. and Streibig, J. C. 2005. Bioassay analysis using R. J. Stat. Softw. 12:1–22.Google Scholar
Roush, R. T. and McKenzie, J. A. 1987. Ecological genetics of insecticide and acaricide resistance. Annu. Rev. Entomol. 32:361–380.Google Scholar
Steadman, K. J. 2004. Dormancy release during hydrated storage in Lolium rigidum seeds is dependent on temperature, light quality, and hydration status. J. Exp. Bot. 55:929–937.CrossRefGoogle ScholarPubMed
Wauchope, R. D., Sumner, H. R., and Dowler, C. C. 1997. A measurement of the total mass of spray and irrigation mixtures intercepted by small whole plants. Weed. Technol. 11:466–472.Google Scholar
Yuan, J. S., Tranel, P. J., and Stewart, C. N. 2007. Non-target-site herbicide resistance: a family business. Trends. Plant. Sci. 12:6–13.CrossRefGoogle ScholarPubMed
Zhang, Z. H., Weaver, S. E., and Hamill, A. S. 2000. Risks and reliability of using herbicides at below-labeled rates. Weed Technol. 14:106–115.CrossRefGoogle Scholar