French organic vegetable farms are diverse, ranging from complex biodiversity-based systems, with many vegetables, to simple input-based systems with few vegetables, suggesting potentially different impacts on the environment. We used life cycle assessment (LCA) to assess the impact of three contrasted farms: MF, a microfarm with a high crop diversity and a low input level, SP, a medium sized farm specialised in sheltered production with a low crop diversity and a high input level, and OP, a large farm specialised in outdoor production with intermediate input level and crop diversity. To cope with the complexity of organic vegetable farms, we opted for a system LCA, based on farm inputs and output for a one-year period. Using mass-, and area-based functional units, we analysed the impacts on climate change, land competition, biodiversity, and the use of plastic.Per ha, differences between the systems were large for climate change. SP had the highest impacts, whereas OP had the lowest impacts. Expressed per kg, differences between the systems for climate change were much smaller, even ranking differently. OP used much less plastic but performed worse on biodiversity and land competition. Despite its higher yield, SP did not perform better than other farms on impacts per kg for climate change, and plastic use. The impact on on-farm biodiversity, showed contrasting results compared to the other impacts. It highlighted the importance of semi-natural habitats. The quantification of plastic use echoed growing concerns on (micro-)plastic pollution in agricultural soils and landscapes.
Organic vegetable farming systems in France have diverse farm structures, farming practices and socio-economic contexts. From April-July 2019, Pépin et al.
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surveyed 165 farms using an online form. The questions about farming practices or socio-economic context did not require quantitative responses to make them simple and easy to answer. From a list of practices, farmers were asked which one(s) they used most often. Using decision rules, the answers were transformed into variables that are suitable for multivariate analysis. The data set also contains analysed data, including composite indexes derived from survey answers, as well as the number of the cluster to which each farm belonged, created after multivariate analysis and clustering performed on the data set.
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