Assessing innovative cropping systems with DEXiPM, a qualitative multi-criteria assessment tool derived from DEXi

Abstract

Modern intensive agriculture has to face the challenge of feeding the world's growing population while reducing its environmental impacts. Assessing in an ex ante way the sustainability of innovative cropping systems will increase the efficiency of the innovation process. To this aim, DEXiPM (DEXi Pest Management) has been developed for ex ante assessment of the sustainability of arable cropping systems, particularly integrated crop management systems with a limited use of pesticides. It has 75 basic indicators describing the cropping system and the context of the assessment, and 86 aggregated indicators, assessing the usual three dimensions of sustainability in terms of social, environmental and economic issues. DEXiPM was implemented to assess and compare current and innovative winter crop- and maize-based cropping systems for a French region. The evaluation results showed that innovative cropping systems with a limited use of pesticides can have a better overall sustainability, despite the fact that some of the indicators can be negatively impacted. DEXiPM is a relevant tool to evaluate the sustainability of actual cropping systems, to diagnose their strong and weak points and, on this basis, to encourage discussions during the design of innovative cropping systems that will afterwards be tested in fields. The design of DEXiPM is also based on a state of the art on agricultural sustainability which led to point out gaps in knowledge that need to be filled (e.g. the impact of crop management on biodiversity). From the discussions of the design phase and the implementation test, improvements have been highlighted. The version presented here includes them as well as the results of the first feedbacks from users and from an evaluation phase. The coherency of cropping system assessments has been judged by experts and found consistent, constituting the first step of the model evaluation. Sensitivity analysis and comparison with quantitative methods are currently on-going to evaluate the accuracy of the model to rank cropping systems.