Epidemiology and agronomic predictors of herbicide resistance in rice at a large scale

Abstract

Herbicide resistance is a major weed control issue that threatens the sustainability of rice cropping systems. Its epidemiology at large scale is largely unknown. Several rice weed species have evolved resistant populations in Italy, including multiple resistant ones. The study objectives were to analyze the impact in Italian rice fields of major agronomic factors on the epidemiology of herbicide resistance and to generate a large-scale resistance risk map. The Italian Herbicide Resistance Working Group database was used to generate herbicide resistance maps. The distribution of resistant weed populations resulted as not homogeneous in the area studied, with two pockets where resistance had not been detected. To verify the situation, random sampling was done in the pockets where resistance had never been reported. Based on data from 230 Italian municipalities, three different statistics, stepwise discriminant analysis, stepwise logistic regression, and neural network, were used to correlate resistance distribution in the main Italian rice growing area with seeding type, rotation rate, and soil texture. Through the integration of complaint monitoring, mapping, and neural network analyses, we prove that a high risk of resistance evolution is associated with traditional rice cropping systems with intense monoculture rates and where water-seeding is widespread. This is the first study that determines the degree of association between herbicide resistance and a few important predictors at large scale. It also demonstrates that resistance is present in areas where it had never been reported through extensive complaint monitoring. However, these resistant populations cause medium-low density infestations, likely not alarming rice farmers. This highlights the importance of integrated agronomic techniques at cropping system level to prevent the diffusion and impact of herbicide resistance or limit it to an acceptable level. The identification of concise, yet informative, agronomic predictors of herbicide resistance diffusion can significantly facilitate effective management and improve sustainability.

Adopting epidemiological approaches for herbicide resistance monitoring and management

“…Where systematic, epidemiological studies of herbicide resistance have been performed, they have provided detailed insight into the extent of resistance and the agronomic practices driving resistance evolution (Evans et al, 2016;Mascanzoni et al, 2018). The mean blackgrass infestation severity, surveyed using a rapid density-structured approach on an ordinal scale; 0-Absent, 1-Low, 2-Medium, 3-High and 4-Very high (Queenborough et al, 2011).…”

“…Where systematic, epidemiological studies of herbicide resistance have been performed, they have provided detailed insight into the extent of resistance and the agronomic practices driving resistance evolution (Evans et al , 2016; Mascanzoni et al , 2018). A detailed, epidemiological study of over 130 geo‐referenced Alopecurus myosuroides populations in the UK combined weed abundance monitoring, resistance screening for multiple herbicide active ingredients and collation of up to 11 years of management history per field to identify the key evolutionary drivers of resistance to post‐emergence selective herbicides (Hicks et al , 2018) (Figure 3).…”

Global drivers of herbicide‐resistant weed richness in major cereal crops worldwide

“…Such variation is likely to arise from differences in crop management, herbicide availability and weed composition across countries that lead herbicide resistance to evolve at different rates. 13 , 14 Countries differ in the extent they apply agronomic options that are known to reduce the rate at which weeds evolve herbicide resistance such as boosting crop competitiveness, employing more effective crop rotations, using herbicide mixtures, undertaking strategic tillage and applying precision weed management. 15 , 16 Furthermore, weed species do not all evolve resistance to the same herbicide modes of action or exhibit similar mechanisms of resistance to the same herbicide (e.g.…”

Resistance in smallflower umbrella sedge (Cyperus difformis) to an acetolactate synthase–inhibiting herbicide in rice: first case in India

“…Acetolactate synthase (ALS)-inhibiting herbicides have been widely used for broad-spectrum control of weeds in rice (Mascanzoni et al 2018;Riar et al 2015). These herbicides proved extremely effective in controlling weeds and were readily adopted by rice growers (Choudhary and Dixit 2018;Kumar and Ladha 2011).…”