A tool based on remotely sensed LAI, yield maps and a crop model to recommend variable rate nitrogen fertilization for wheat
Résumé
Inversing the STICS crop model with remote-sensing-derived leaf area index (LAI) and yield data from the previous crop is used to
retrieve some soil permanent properties and crop emergence parameters. Spatialized nitrogen (N) fertilization recommendations are
provided to farmers, for the second and third N applications, following the screening of eleven N application rates under a
range of possible forthcoming climates, with the objective to maximize of the gross margin while respecting some environmental
constraints. As a first field validation, we show (1) the improvement brought by the assimilation of LAI and yield into STICS
to simulate crop and soil variables and (2) the interest of site specific application to maximize both the gross margin and the
agro-environmental criterion.