Herbicide resistance evolution can be tamed by diversity in irrigated Australian cotton: a multi‐species, multi‐herbicide modelling approach

Thornby, David; Werth, Jeff; Hereward, James; Keenan, Michelle; Chauhan, Bhagirath Singh

doi:10.1002/ps.4914

Cited by 6 publications

(5 citation statements)

References 42 publications

(77 reference statements)

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“…One of the elements in herbicide resistance management (HRM) is diversity in herbicide programmes. However, as shown by the simulation undertaken by Thornby et al [50], if the frequency of resistance genes to one herbicide (in this case glyphosate resistance) in the population is high, control with the use of three active ingredients (glyphosate, glufosinate and dicamba) may be insufficient to prevent the evolution of resistance.…”

Section: Discussionmentioning

confidence: 99%

Herbicide Resistance of Centaurea cyanus L. in Poland in the Context of Its Management

et al. 2021

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Cornflower (Centaurea cyanus L.), one of the main weeds found among winter crops in Poland, has developed herbicide resistance (HR) to acetolactate synthase (ALS) herbicides, a finding first reported in 2006, and in recent years, farmers have been complaining about inadequate chemical control of this weed. This study aimed to characterise the current state of cornflower HR to ALS inhibitors and synthetic auxins in Poland and the agricultural practices in fields with herbicide-resistant populations. From 2017 to 2020, 159 seed samples together with the field history were collected across the country and biological tests performed in glasshouses. This revealed that 47 populations of C. cyanus were cross-resistant to both tribenuron and florasulam, 28 and 8 populations were single resistant to tribenuron and florasulam, respectively, and 3 populations had developed multiple resistance to both ALS inhibitors and synthetic auxins, i.e., 2,4-D and dicamba. Resistant populations were found mostly frequent in northern Poland, but also in the eastern and western parts of the country. Based on a survey of farmers, the resistant populations were found in winter crops regardless of the tillage system (77% of fields with HR cornflower were mouldboard ploughed). Based on the proposed population treatment (PT) index showing the frequency of herbicide use during three consecutive seasons on farms with HR cornflower, the average PT for all the surveyed farms was 5.4. The highest PT of 7.4 was found in the province of Warmia-Masuria in northern Poland.

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Section: Discussionmentioning

confidence: 99%

Herbicide Resistance of Centaurea cyanus L. in Poland in the Context of Its Management

et al. 2021

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“…With the sequential evolution demonstrated by multiple resistance ( Figure 1A-C) and simultaneous evolution demonstrated by cross-resistance of H and X ( Figure 1D-F), our model is among the first few that address genetic or ecological interactions in the prediction of herbicide resistance, for example, pleiotropic effects (Colbach et al 2016) or multiple weed species (Thornby et al 2018). Other forms of interaction include chemical interaction, such as synergy and antagonism.…”

Section: Stacked Traits and Multiple Post Herbicide Soasmentioning

confidence: 94%

“…In recent years, there has been growing awareness that the sustainability, that is, the long-term effectiveness, of a program is equally important and should be evaluated before it is recommended to growers. Simulation models are useful tools for fulfilling such an evaluation (Neve et al 2014;Renton et al 2014;Thornby et al 2018). Predictions from the models usually include weed population density and the risk of resistance evolution.…”

Section: Introductionmentioning

confidence: 99%

Modeling the sustainability and economics of stacked herbicide-tolerant traits and early weed management strategy for waterhemp (Amaranthus tuberculatus) control

et al. 2020

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Diversity is key for sustainable weed management and can be achieved via both chemical and nonchemical control tactics. Genetically modified crops with two-way or three-way stacked herbicide-tolerant traits allow use of herbicide mixtures that would otherwise be phytotoxic to the crop. Early weed management (EWM) strategies promote the use of PRE herbicides with residual activity to keep the field free of weeds early in the season for successful crop establishment. To evaluate the respective sustainability and practicality of the two chemical-based management tactics (i.e., stacked traits and EWM), we used a population model of waterhemp, Amaranthus tuberculatus (Moq.) Sauer (syn. rudis), to simulate the evolution of resistance in this key weed species in midwestern U.S. soybean [Glycine max (L.) Merr.] agroecosystems. The model tested scenarios with a varying number of herbicide sites of action (SOAs), application timings (PRE and POST), and preexisting levels of resistance. Results showed that both tactics provided opportunity for controlling resistant A. tuberculatus populations. In general, each pass over the field should include at least two effective herbicide SOAs. Nevertheless, the potential evolution of cross-resistance may void the weed control programs embraced by stacked traits and diverse herbicide SOAs. Economic calculations suggested that the diversified programs could double long-term profitability when compared to the conventional system, because of improved yield and grain quality. Ultimately, the essence of a sustainable herbicide resistance management strategy is to be proactive. Although a herbicide-dominated approach to diversifying weed management has been prevalent, the increasing presence of weed populations with multiple resistance means that finding herbicides to which weed populations are still susceptible is becoming increasingly difficult, and thus the importance of reintroducing cultural and mechanical practices to support herbicides must be recognized.

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“…This complexity makes it difficult to anticipate where, under what circumstances, and under what timeframe, herbicide resistance is likely to appear. Modelling approaches have provided an avenue for identifying and predicting situations in which resistance may evolve, including mathematical models of the phenomena affecting resistance [12][13][14][15], models of population genetics [16][17][18], and individual-based models addressing the interactions between weed life cycle, spatial distribution, multiple species and agricultural practices [19][20][21].…”

Section: Introductionmentioning

confidence: 99%

Predicting global herbicide resistance hotspots using a 30-year-old database and machine-learning techniques

Brocklehurst,

Liu

2023

Preprint

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The evolution of herbicide resistance in weeds is a problem affecting both food production and ecosystems. Numerous factors affect selection towards herbicide resistance, making it difficult to anticipate where, under what circumstances, and under what timeframe, herbicide resistance is likely to appear. Using the International Herbicide-Resistant Weed Database to provide data on locations and situations where resistance has occurred, we trained models to predict where resistance is most likely in future. Validation of the global models with historical data found a prediction accuracy of up to 78%, while for well-sampled regions, such as Australia, the model correctly predicted more than 95% of instance of resistance and sensitivity. Applying the models to predict instances of resistance over the next decade, future hotspots were detected in North and South America and Australia. Species such asConyza canadensis,Eleusine indica, andLactuca serriolaare expected to show substantial increases in the number of resistance occurrences. The results highlight the potential of machine-learning approaches in predicting future resistance hotspots and urge more efforts in resistance monitoring and reporting to enable improved predictions. Future work incorporating dimensions such as weed traits, phylogeny, herbicide chemistry, and farming practices could improve the predictive power of the models.

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Herbicide resistance evolution can be tamed by diversity in irrigated Australian cotton: a multi‐species, multi‐herbicide modelling approach

Cited by 6 publications

References 42 publications

Herbicide Resistance of Centaurea cyanus L. in Poland in the Context of Its Management

Herbicide Resistance of Centaurea cyanus L. in Poland in the Context of Its Management

Modeling the sustainability and economics of stacked herbicide-tolerant traits and early weed management strategy for waterhemp (Amaranthus tuberculatus) control

Predicting global herbicide resistance hotspots using a 30-year-old database and machine-learning techniques

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