Hostname: page-component-586b7cd67f-vdxz6 Total loading time: 0 Render date: 2024-11-24T06:41:10.394Z Has data issue: false hasContentIssue false
  • English
  • Français

Genetic Aspects of Herbicide-Resistant Weed Management

Published online by Cambridge University Press:  12 June 2017

Michael J. Christoffers
Michael J. Christoffers*
Affiliation:
Department of Plant Sciences, North Dakota State University, Fargo, ND 58105-5051. E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Weed populations develop herbicide resistance when they evolve due to selection pressure. Mutations and gene flow contribute to genetic variability and provide resistant alleles. The speed of resistance gene frequency increase is determined by the inheritance of resistance alleles relative to wild-type susceptibility and is influenced by the interaction between gene expression and selection. The goal of herbicide resistance management is to minimize selection pressure while maintaining adequate weed control. However, the specific nature of each herbicide, weed, and resistance combination determines the practices that optimize undesirable selection pressure. Therefore, generalized management strategies should be recommended with caution and must not be mandated without thorough evaluation on a case-by-case basis.

Keywords

EvolutionselectionDNA, deoxyribonucleic acid
Type
Symposium
Information
Weed Technology , Volume 13 , Issue 3 , September 1999 , pp. 647 - 652
Copyright
Copyright © 1999 by the Weed Science Society of America 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Literature Cited

Bridges, B. A. 1997. Hypermutation under stress. Nature 387:557–558.Google Scholar
Cohen, J. 1998. Failure isn't what it used to be … but neither is success. Science 279:1133–1134.Google Scholar
Falconer, D. S. 1989. Introduction to Quantitative Genetics. Longman House, U.K.: Longman Scientific and Technical. 438 p.Google Scholar
Gillespie, J. H. 1991. The Causes of Molecular Evolution. New York: Oxford University Press. 336 p.Google Scholar
Gould, F. 1995. Comparisons between resistance management strategies for insects and weeds. Weed Technol. 9:830–839.Google Scholar
Holtzman, N. A., Murphy, P. D., Watson, M. S., and Barr, P. A. 1997. Predictive genetic testing: from basic research to clinical practice. Science 278:602–605.CrossRefGoogle ScholarPubMed
Keightley, P. D. 1996. A metabolic basis for dominance and recessivity. Genetics 143:621–625.Google Scholar
Kimura, M. 1980. A simple method for estimating evolutionary rates of base substitutions through comparative studies of nucleotide sequences. J. Mol. Evol. 16:111–120.Google Scholar
Kimura, M. 1983. The Neutral Theory of Molecular Evolution. Cambridge, U.K.: Cambridge University Press. 367 p.CrossRefGoogle Scholar
Levy, S. B. 1998. The challenge of antibiotic resistance. Sci. Am. 278(3): 46–53.Google Scholar
Li, W.-H. 1997. Molecular Evolution, Sunderland, MA: Sinauer Associates. 487 p.Google Scholar
McGaughey, W. H., Gould, F., and Gelernter, W. 1998. Bt resistance management. Nat. Biotechnol. 16:144–146.Google Scholar
Mikula, B. C. 1995. Environmental programming of heritable epigenetic changes in paramutant r-gene expression using temperature and light at a specific stage of early development in maize seedlings. Genetics 140:1379–1387.CrossRefGoogle Scholar
Prina, A. R. 1992. A mutator nuclear gene inducing a wide spectrum of cytoplasmically inherited chlorophyll deficiencies in barley. Theor. Appl. Genet. 85:245–251.Google Scholar
Taddei, F., Radman, M., Maynard-Smith, J., Toupance, B., Gouyon, P. H., and Godelle, B. 1997. Role of mutator alleles in adaptive evolution. Nature 387:700–702.Google Scholar
Wolfe, K. H., Li, W.-H., and Sharp, P. M. 1987. Rates of nucleotide substitution vary greatly among plant mitochondrial, chloroplast, and nuclear DNAs. Proc. Natl. Acad. Sci. USA 84:9054–9058.CrossRefGoogle ScholarPubMed