Contributors: Agroécologie Dijon; Université de Bourgogne (UB)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Université Bourgogne Franche-Comté COMUE (UBFC)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE); Sciences pour l'Action et le Développement : Activités, Produits, Territoires (SADAPT); AgroParisTech-Université Paris-Saclay-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE); Agronomie; Les instituts techniques agricoles (Acta); Laboratoire Agronomie et Environnement (LAE); Université de Lorraine (UL)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE); ANR-14-CE18-0007,CoSAC,Conception de Stratégies durables de gestion des Adventices dans un contexte de Changement (climat, pratiques agricoles, biodiversité)(2014)
نبذة مختصرة : International audience ; Fanners and farm advisors need a decision support system (DSS) to develop multiperformant weed management strategies adapted to economic, social and environmental stakes and farmers' constraints. We worked with future users, farmers, and crop advisors to define the uses and type of DSS they needed, via an online survey, group meetings and workshops. The feedback from future users helped to define the structure of the DSS with two complementary DSS needed: (1) a synthetic tool working with meta-decision rules to help with a complete overhaul of a cropping system, and (2) a precise and detailed tool for fine tuning cropping systems. Here, we present how we interacted with future users to transform an existing research model into a DSS by (1) defining its goal, application field and structure, (2) entering into the DSS knowledge on biophysical processes comprised in the mechanistic weed dynamics model FLORSYS. We selected a more appropriate vocabulary for describing agricultural practices and formats with future users. Based on their feedback, a large range of weed impact indicators was included in the DSS so that farmers can choose the most pertinent for their objectives. Based on workshops with farmers, a decision tree format with numerical values of weed impact indicators was chosen to demonstrate the impacts of multiple cultural practices combinations. The DSS also includes an online calculator predicting weed (dis)services from meta-decision rules which was tested by crop advisors. Responses of the DSS were sometimes not expected by users, but were still considered interesting highlighting the need of agronomical support while using the tool.
No Comments.