Inferring herbicide non‐target‐site cross‐resistance from dose response and mixture treatments

BACKGROUND: Herbicide cross-resistance is of increasing concern because it compromises the effectiveness of both existing and new chemical options. However, a common misconception is that if a weed population shows dose-response shifts to two herbicides, it is cross-resistant to both. The possibility that individual plants may possess different resistance mechanisms is often overlooked. RESULTS: To better characterise non-target-site cross-resistance, we propose that the accession be treated with mixtures of the two herbicides of interest. A population model could be used to simulate the expected dose responses to the mixtures, assuming different cross-resistance levels in the population, as well as synergistic or antagonistic effects between the two herbicides. The simulated responses can then be compared with the actual responses, and the cross-resistance level approximated. We demonstrated this approach from a mathematical standpoint and validated it with experimental data from glasshouse tests on four well-characterised biotypes of Lolium multiflorum and two commercial herbicides, clodinafop and iodosulfuron. Results also showed that understanding chemical interactions such as synergy and antagonism is crucial to a better estimate of cross-resistance levels. CONCLUSION: Because this method utilises standard dose-response tests, it is potentially easier and less time-consuming than those involving plant cloning or divergent recurrent selection. Quick characterisation of the degree of cross-resistance provides important insights as to whether chemical rotations or mixtures can still effectively control the weed population displaying resistances to multiple herbicides. This approach could be applied more broadly in cross-resistance studies with other xenobiotics.