Co-development of a decision support system for integrated weed management: Contribution from future users

被引:18
|
作者
Colas, F. [1 ,5 ]
Cordeau, S. [1 ]
Granger, S. [1 ]
Jeuffroy, M-H [2 ]
Pointurier, O. [1 ]
Queyrel, W. [1 ]
Rodriguez, A. [3 ]
Villerd, J. [4 ]
Colbach, N. [1 ]
机构
[1] Univ Bourgogne Franche Comte, INRA, AgroSup Dijon, Agroecol, F-21000 Dijon, France
[2] Univ Paris Saclay, AgroParisTech, INRA, UMR Agron, F-78850 Thiverval Grignon, France
[3] Acta, F-31450 Baziege, France
[4] Univ Lorraine, INRA, LAE, F-54500 Vandoeuvre Les Nancy, France
[5] INRA, UMR SADAPT 1048, F-75005 Paris, France
关键词
Integrated weed management; Participatory design; Decision aid; Agroecology; Multivariate output display; Conceptual framework; CROPPING SYSTEMS; PARTICIPATORY APPROACH; MAKING PROCESSES; FARMERS; DESIGN; MODEL; SIMULATION; SOIL; SUSTAINABILITY; BIODIVERSITY;
D O I
10.1016/j.eja.2020.126010
中图分类号
S3 [农学(农艺学)];
学科分类号
0901 ;
摘要
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.
引用
收藏
页数:13
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