A conceptual framework for the contextualization of crop model applications and outputs in participatory research

Abstract Contextualization of generic scientific knowledge to context-specific farmer knowledge is a necessary step in farmers’ innovation process, and it can be achieved using crop and farm models. This work explores the possibility to simulate a large number of scenarios based on farmers’ descriptions of their environment and practices in order to contextualize the discussion for each participating farmer. It presents a novel framework consisting of six actions divided in three phases, namely, phase I—reaching out to the farmers’ world: (i) project initialization; (ii) determination of the agronomical question anchored in farmers’ context; (iii) characterization of the environment, the management options, and the indicators to describe the system under consideration; phase II—within researchers’ world: (iv) crop model parametrization; (v) translation of model outputs into farmer-proposed indicators; and phase III—back to farmers’ world: (vi) exploration of contextualized management options with farmers. Two communication tools are created during the process, one containing the results of simulations to feed the discussions and a second one to create a record of it. The usefulness of the framework is exemplified with the exploration of soil fertility management with manure and compost applications for sorghum production in the smallholder context of Sudano-Sahelian Burkina Faso. The application of the framework with 15 farmers provided evidence of farmers’ and agronomists’ understanding of options to improve cropping system performance with better organic amendment management. This approach allowed farmers to identify and relate to the scenarios simulated, but highlighted interrogations on how to adapt the crop model outputs to particular situations. Though applied on issues related to tactical change at field level, the framework offers the opportunity to explore broader issues with farmers, such as farm reconfiguration.