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Herbicide-resistant late watergrass (Echinochloa phyllopogon): similarity in morphological and amplified fragment length polymorphism traits

Published online by Cambridge University Press:  20 January 2017

Ryouichirou Tsuji ,
Albert J. Fischer ,
Masahiro Yoshino ,
Alvaro Roel ,
James E. Hill  and
Yuji Yamasue
Ryouichirou Tsuji
Affiliation:
Graduate School of Agriculture, Kyoto University, Kyoto 606-8502, Japan
Masahiro Yoshino
Affiliation:
Graduate School of Agriculture, Kyoto University, Kyoto 606-8502, Japan
Alvaro Roel
Affiliation:
Agronomy and Range Science Department, University of California, Davis, CA 95616
James E. Hill
Affiliation:
Agronomy and Range Science Department, University of California, Davis, CA 95616
Yuji Yamasue
Affiliation:
Graduate School of Agriculture, Kyoto University, Kyoto 606-8502, Japan
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Abstract

Late watergrass is a serious weed of California rice that has evolved resistance to molinate, thiobencarb, fenoxaprop-ethyl, and bispyribac-sodium. To obtain an insight into the origin and spread of resistant (R) late watergrass in California rice fields, we evaluated similarities in morphological traits and amplified fragment length polymorphism (AFLP) fingerprints among 15 R strains compared with susceptible (S) strains. All strains were derived by inbreeding from accessions collected in rice fields of the Sacramento Valley, CA. In the field, R plants were shorter than S plants; they also had narrower and shorter flag leaves and thinner culms. Spikelets also appeared smaller and more slender in R plants. There was greater morphological similarity among the 15 R strains than among the eight S strains. The mean coefficients of variation for morphological traits were much smaller among R strains, which in a cluster analysis (Ward's method) were grouped morphologically apart at early clustering stages from the more variable S strains. AFLP electropherograms also showed greater similarity between R strains. R strains were grouped separately from the S strains in a cluster analysis based on calculated Nei and Li coefficients used in an unweighted pair group method using arithmetic means. However, small genetic differences also existed because the R strains were grouped into six clusters, suggesting that R strains were not samples from an identical strain. It was concluded that R strains originated from a preexisting and preadapted mutant late watergrass population in the Sacramento Valley. This study establishes that resistance moved by spikelet dispersal, not independent mutation events, most likely defined the geographical distribution of R late watergrass in California. Prevention and control of this dispersal combined with elimination of seed-producing survivors after herbicide treatment should be relevant components of the integrated management of herbicide-resistant late watergrass in California rice.

Keywords

Bispyribac-sodium, sodium 2,6-bis[(4,6-dimethoxypyrimidin-2-yl)oxy]benzoatefenoxaprop-ethylmolinatethiobencarbearly watergrass, Echinochloa oryzicola Vasinglate watergrass, Echinochloa phyllopogon (Stapf) Koss ECHPHrice, Oryza sativa L.Amplified fragment length polymorphismgenetic diversityherbicide resistancegraminicides

Information

Type
Weed Biology
Information
Weed Science , Volume 51 , Issue 5 , October 2003 , pp. 740 - 747
Copyright
Copyright © Weed Science Society of America 

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References

Literature Cited

Andrews, T. S., Morrison, I. N., and Penner, G. A. 1998. Monitoring the spread of ACCase inhibitor resistance among wild oat (Avena fatua) patches using AFLP analysis. Weed Sci 46:196–199.CrossRefGoogle Scholar
Ban, Y. 1997. DNA isolation with CTAB method. Pages 34–40 in Shimamoto, K. and Sasaki, T. eds. PCR Experiment Protocol for Plants. Tokyo: Shujunsha.Google Scholar
Barrett, S. C. H. 1983. Crop mimicry in weeds. Econ. Bot 37:255–282.Google Scholar
Barrett, S. C. H. and Seaman, D. E. 1980. The weed flora of Californian rice fields. Aquat. Bot 9:351–376.Google Scholar
Cavan, G., Bliss, P., and Moss, S. R. 1998a. Localized origins of herbicide resistance in Alopecurus myosuroides . Weed Res 38:239–245.Google Scholar
Cavan, G., Bliss, P., and Moss, S. R. 1998b. Herbicide resistance and gene flow in wild-oats (Avena fatua and Avena sterilis ssp. ludoviciana). Ann. Appl. Biol 133:207–217.Google Scholar
Cousens, R. and Motimer, M. 1995. Dynamics of Weed Populations. Cambridge, Great Britain: Cambridge University Press. Pp. 243–282.Google Scholar
Darmency, H. and Gasquez, J. 1990. Appearance and spread of triazine resistance in common lambsquarters (Chenopodium album). Weed Technol 4:173–177.CrossRefGoogle Scholar
Fischer, A. J., Ateh, C. M., Bayer, D. E., and Hill, J. E. 2000a. Herbicide-resistant early (Echinochloa oryzoides) and late (E. phyllopogon) watergrass in California rice fields. Weed Sci 48:225–230.Google Scholar
Fischer, A. J., Bayer, D. E., Carriere, M. D., Ateh, C. M., and Yim, K-O. 2000b. Mechanisms of resistance to bispyribac-sodium in anEchinochloa phyllopogon accession. Pestic. Biochem. Physiol 68:156–165.Google Scholar
Fischer, A. J. and Hill, J. E. 1998. Weed control in rice. Pages 54–58 in Annual Report on Comprehensive Rice Research. Davis, CA: University of California–Davis and USDA.Google Scholar
Gressel, J. and Segel, L. A. 1978. The paucity of plants evolving genetic resistance to herbicides: possible reasons and implications. J. Theor. Biol 75:349–371.Google Scholar
Gressel, J. and Segel, L. A. 1982. Interrelating factors controlling the rate of appearance of resistance: the outlook for the future. Pages 3255–3347 in Le Baron, H. M. and Gressel, J. eds. Herbicide Resistance in Plants. New York: J. Wiley.Google Scholar
Gressel, J. and Segel, L. A. 1990. Modelling the effectiveness of herbicide rotations and mixtures as strategies to delay or preclude resistance. Weed Technol 4:186–198.CrossRefGoogle Scholar
Gronwald, J. W. 1991. Lipid biosynthesis inhibitors. Weed Sci 37:435–449.Google Scholar
Harper, J. L. 1956. The evolution of weeds in relation to the resistance to herbicides. Pages 179–188 in Proceedings of the 3rd British Weed Control Conference. London: British Weed Council.Google Scholar
Heap, I., Landes, A., Boutsalis, P., Retzinger, J., and Smeda, R. 2002. International Survey of Herbicide Resistant Weeds, Weed Science Society of America. Available at: http://www.weedscience.org/in.asp. Accessed April 18, 2002.Google Scholar
Hill, J. E. and Hawkins, L. 1996. Herbicides in United States rice production: lessons for Asia. Pages 37–52 in Naylor, R. ed. Herbicides in Asian Rice: Transitions in Weed Management. Palo Alto, CA: Institute for International Studies, Stanford University.Google Scholar
Iqbal, M. J., Aziz, N., Saeed, N. A., Zafar, Y., and Malik, K. A. 1997. Genetic diversity evaluation of some elite cotton varieties by RAPD analysis. Theor. Appl. Genet 94:139–144.Google Scholar
Jasieniuk, M., Brûlé-Babel, A. L., and Morrison, I. M. 1996. The evolution and genetics of herbicide resistance in weeds. Weed Sci 44:176–193.Google Scholar
Jasieniuk, M. and Maxwell, B. D. 1994. Population genetics and the evolution of herbicide resistance in weeds. Phytoprotection 75:(Suppl.). 25–35.Google Scholar
Kennedy, R. A., Barrett, S. C. H., Vander Zee, D., and Rumpho, M. E. 1980. Germination and seedling growth under anaerobic conditions in Echinochloa crus-galli (barnyard grass). Plant Cell Environ 3:243–248.Google Scholar
Maxwell, B. D. and Ghersa, C. 1992. The influence of weed seed dispersion versus the effect of competition on crop yield. Weed Technol 6:196–204.Google Scholar
Maxwell, B. D., Roush, M. L., and Radosevich, S. R. 1990. Predicting the evolution and dynamics of herbicide resistance in weed populations. Weed Technol 4:2–13.Google Scholar
Nei, N. and Li, W. 1979. Mathematical model for studying genetic variation in terms of restriction endonucleases. Proc. Natl. Acad. Sci. USA 76:5269–5273.Google Scholar
Ryan, G. F. 1970. Resistance of common groundsel to simazine and atrazine. Weed Sci 18:614–616.Google Scholar
Stankiewicz, M., Gadamski, G., and Gawronski, S. W. 2001. Genetic variation and phylogenetic relationships of triazine-resistant and trazine-susceptible biotypes of Solanum nigrum—analysis using RAPD markers. Weed Res 41:287–300.Google Scholar
Thill, D. C. and Mallory-Smith, C. A. 1997. The nature and consequence of weed spread in cropping systems. Weed Sci 45:337–342.Google Scholar
Vos, P., Hodgers, R., and Bleeker, M. et al. 1995. AFLP: a new technique for DNA fingerprinting. Nucleic Acids Res 23:4407–4414.CrossRefGoogle ScholarPubMed
Ward, J. H. 1963. Hierarchical grouping to optimize an objective function. J. Am. Stat. Assoc 58:236–244.Google Scholar
Warwick, S. I. 1991. Herbicide resistance in weedy plants: physiology and population biology. Annu. Rev. Ecol. Syst 22:95–114.Google Scholar
Warwick, S. I. and Marriage, P. B. 1982a. Geographical variation in populations of Chenopodium album resistant and susceptible to atrazine. I. Between- and within-population variation in growth and response to atrazine. Can. J. Bot 60:483–493.CrossRefGoogle Scholar
Warwick, S. I. and Marriage, P. B. 1982b. Geographical variation in populations of Chenopodium album resistant and susceptible to atrazine. II. Photoperiod and reciprocal transplant studies. Can. J. Bot 60:494–504.Google Scholar
Yabuno, T. 1966. Biosystematic study of the genus Echinochloa . Jpn. J. Bot 19:277–323.Google Scholar
Yamasue, Y. 1997. Biometric analysis of Echinochloa weeds. Pages 233–237 in Proceedings of the 16th Asian Pacific Weed Science Society Conference. Kuala Lumpur, Malaysia: Malaysian Plant Protection Society.Google Scholar
Yamasue, Y. 2001. Strategy of Echinochloa oryzicola Vasing for survival in flooded rice. Weed Biol. Manag 1:28–36.Google Scholar