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. 2009 Oct;103(4):318-25.
doi: 10.1038/hdy.2009.64. Epub 2009 Jun 3.

Evolution of glyphosate resistance in a Lolium rigidum population by glyphosate selection at sublethal doses

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Evolution of glyphosate resistance in a Lolium rigidum population by glyphosate selection at sublethal doses

R Busi et al. Heredity (Edinb). 2009 Oct.

Abstract

The majority of the documented cases of field-evolved herbicide-resistant weed biotypes established that single major genes confer glyphosate resistance. However, the contribution of minor genes endowing substantial plant survival at sublethal herbicide doses may be a potential complementary path to herbicide resistance evolution in weed populations under selection. Here, we subjected a number of susceptible individuals of Lolium rigidum to recurrent glyphosate selection to test the potential for sublethal glyphosate doses to additively select for glyphosate resistance. After 3-4 cycles of glyphosate selection in two distinct environments, the progenies of the initially susceptible population were shifted toward glyphosate resistance. The results indicate progressive enrichment of minor gene trait(s) contributing toward plant survival in the glyphosate-selected progenies. After three generations of selection, the estimated LD(50) values were doubled compared with the original population and up to 33% plant survival was obtained in the glyphosate-selected progeny at the recommended glyphosate label rate. This level of resistance probably was the maximum shift achievable with sublethal glyphosate dose selection in this small population. Cross-pollination was a crucial factor enabling the rapid rate of accumulation of minor glyphosate resistance gene trait(s) that are likely to be present at a relatively high frequency in a small susceptible population. The mechanistic basis of the moderate glyphosate resistance level selected by sublethal glyphosate doses remains unknown and warrants future research. Studying the main factors influencing the evolution of resistant weed populations is crucial for understanding, predicting and managing herbicide resistance.

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