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Herbicide resistance is complex: a global review of cross-resistance in weeds within herbicide groups

Published online by Cambridge University Press:  26 November 2024

Dean E. Riechers
Affiliation:
Professor, Department of Crop Sciences, University of Illinois, Urbana, IL, USA
Nader Soltani*
Affiliation:
Adjunct Professor, Department of Plant Agriculture, University of Guelph, Ridgetown, ON, Canada
Bhagirath Singh Chauhan
Affiliation:
Professor, Queensland Alliance for Agriculture and Food Innovation (QAAFI), University of Queensland, Gatton, QLD, Australia
Jeanaflor Crystal T. Concepcion
Affiliation:
Postdoctoral Research Associate, Department of Crop Sciences, University of Illinois, Urbana, IL, USA
Charles M. Geddes
Affiliation:
Research Scientist, Lethbridge Research and Development Centre, Agriculture and Agri-Food Canada, Lethbridge, AB, Canada
Mithila Jugulam
Affiliation:
Professor, Department of Agronomy, Kansas State University, Manhattan, KS, USA
Shiv S. Kaundun
Affiliation:
Researcher, Herbicide Bioscience, Syngenta, Jealott’s Hill International Research Centre, Bracknell, Berkshire, UK
Christopher Preston
Affiliation:
Professor, School of Agriculture, Food and Wine, University of Adelaide, Glen Osmond, SA, Australia
R. Joseph Wuerrfel
Affiliation:
Researcher, Syngenta Crop Protection, Greensboro, NC, USA
Peter H. Sikkema
Affiliation:
Professor, Department of Plant Agriculture, University of Guelph, Ridgetown, ON, Canada
*
Corresponding author: Nader Soltani; Email: soltanin@uoguelph.ca
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Abstract

Herbicides have been placed in global Herbicide Resistance Action Committee (HRAC) herbicide groups based on their sites of action (e.g., acetolactate synthase–inhibiting herbicides are grouped in HRAC Group 2). A major driving force for this classification system is that growers have been encouraged to rotate or mix herbicides from different HRAC groups to delay the evolution of herbicide-resistant weeds, because in theory, all active ingredients within a herbicide group physiologically affect weeds similarly. Although herbicide resistance in weeds has been studied for decades, recent research on the biochemical and molecular basis for resistance has demonstrated that patterns of cross-resistance are usually quite complicated and much more complex than merely stating, for example, a certain weed population is Group 2-resistant. The objective of this review article is to highlight and describe the intricacies associated with the magnitude of herbicide resistance and cross-resistance patterns that have resulted from myriad target-site and non–target site resistance mechanisms in weeds, as well as environmental and application timing influences. Our hope is this review will provide opportunities for students, growers, agronomists, ag retailers, regulatory personnel, and research scientists to better understand and realize that herbicide resistance in weeds is far more complicated than previously considered when based solely on HRAC groups. Furthermore, a comprehensive understanding of cross-resistance patterns among weed species and populations may assist in managing herbicide-resistant biotypes in the short term by providing growers with previously unconsidered effective control options. This knowledge may also inform agrochemical company efforts aimed at developing new resistance-breaking chemistries and herbicide mixtures. However, in the long term, nonchemical management strategies, including cultural, mechanical, and biological weed management tactics, must also be implemented to prevent or delay increasingly problematic issues with weed resistance to current and future herbicides.

Information

Type
Review
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© His Majesty the King in Right of Canada, 2024. Published by Cambridge University Press on behalf of Weed Science Society of America
Figure 0

Figure 1. Control of Digitaria sanguinalis with quizalofop-p-ethyl (left) and clethodim (right) in a field in Ontario, Canada.

Figure 1

Figure 2. Emergence of Lolium rigidum populations collected randomly from crop fields in southeastern South Australia. Each population was treated with the Group 3 herbicides, trifluralin and pronamide, preemergence. These findings demonstrate resistance to trifluralin but not pronamide in the field-collected populations above. Untreated (left); treated with 800 g ha−1 trifluralin (middle); treated with 500 g ha−1 pronamide (right). Each tray contains samples collected from 20 fields with the sample from an individual field sown in a single cell. The same 20 populations are planted in each tray. Each herbicide rate used represents the lowest labeled rate for weed management in no-till grain crop production in Australia.

Figure 2

Figure 3. Control of Amaranthus tuberculatus with metribuzin (560 g ai ha−1) with Group 5 resistance due to enhanced metabolism (left) and an altered target site (right) from two fields in Ontario, Canada.

Figure 3

Figure 4. Representative images of variable Group 15 (G15) herbicide efficacy for controlling a G15-resistant Amaranthus tuberculatus population (CHR) and a sensitive (Urbana, IL) population, 28 d after treatment. Figure 4 was reproduced directly without changes from Strom et al. (2022).