Methodological considerations for redesigning sustainable cropping systems: the value of data-mining large and detailed farm data sets at the cropping system level

Abstract

Redesigning cropping and farming systems to enhance their sustainability is mainly addressed in scientific studies using experimental and modeling approaches. Large data sets collected from real farms allow for the development of innovative methods to produce generic knowledge. Data mining methods allow for the diversity of systems to be considered holistically and can take into account the diversity of production contexts to produce site-specific results. Based on the very few known studies using such methods to analyze the crop management strategies affecting pesticide use and their effect on farm performance, we advocate further investment in the development of large data sets that can support future research programs on farming system design.

Keywords

data mining / holistic / Integrated Pest Management / economics / DEPHY network

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Acknowledgements

We thank the farmers and farm advisors in the DEPHY network (Ministry of Agriculture, France), the SCEP-DEPHY research project funded by the AFB (French Agency for Biodiversity, France). Martin Lechenet’s PhD fellowship was funded by Agrosolutions (France). We thank Juliette Young and anonymous reviewers for comments and editings on the manuscript.

Compliance with ethics guidelines

Nicolas Munier-Jolain and Martin Lechenet declare that they have no conflicts of interest or financial conflicts to disclose.

This article does not contain any studies with human or animal subjects performed by any of the authors.

RIGHTS & PERMISSIONS

The Author(s) 2019. Published by Higher Education Press. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0)