Patterns and clusters of pesticide reduction strategies in Swiss viticulture

Abstract Viticulture is essential for reducing pesticide use and associated risks. Often the adoption of individual pesticide reduction measures is investigated in isolation, and little is known on broader patterns and the joint adoption of measures. We address this gap by analyzing adoption choices of Swiss grape growers across a large number of pesticide reduction measures, using a contingency analysis and a k-means clustering algorithm. We focus on how measure, farm, and farmer characteristics correlate with this adoption. The analysis uses survey data collected among 436 Swiss grapevine producers. Results indicate that farmers in our sample appear to exploit complementary effects between measures. Moreover, the cluster analysis reveals that Swiss producers can be split into two groups of roughly equal size, with one adopting a greater variety of pesticide reduction measures, and the other relying more on pesticides alone. We further identify significant differences in farm and farmer characteristics that could explain this variation in measure adoption. Our analysis has important implications for research and policy. Firstly, they underline the importance of fostering the adoption of efficient and effective measure bundles. Secondly, they highlight the need for targeted policies to mobilize farmers relying mostly on pesticides to diversify their plant protection practices and thus contribute to overall pesticide reduction.