Abstract
Farmers and consultants face an unmanageable amount of diverse knowledge and information for crop management decisions. To determine optimal actions, decision makers require knowledge-based support. In this way, decisions can be improved and heuristics can be replaced over time. The study presents a digital knowledge base with an integrated decision support system (DSS), using the example of nutrient supply, specifically nitrogen (N), fertilization. Therefore, the requirements of farmers and crop consultants for DSS to inform fertilization decisions for winter wheat (Triticum aestivum L.) were elaborated using surveys, expert interviews, and a prototype test. Semantic knowledge was enriched by expert knowledge and combined in a web application, the Crop Portal. To map regional and personal decision making patterns and experiences, the tacit knowledge on the complex advisory problem of N fertilization is made digitally usable. For this purpose, 16 fuzzy variables were specified and formalized. Individual decision trees and their interactions with an integrative knowledge base were used to multiply the consulting reach of experts. Using three consultants and nine model farms from different soil–climate areas in Germany, the Crop Portal was tested under practical conditions and the perceived pragmatic and hedonic quality of the system was evaluated using a standardized questionnaire. The field test showed that the variation in fertilizer recommendations from the ‘digital advisor twin’ ranged from 5 kg N ha−1 to 16 kg N ha−1 when compared with the decisions of the experts in the field. The study presents the participatory development and evaluation of a rule-based DSS prototype in agricultural practice.
Highlights
Development of the web application Crop Portal was characterized by a participative approach and can be presented in three working steps: 1. Analysis of the requirements for the performance of the knowledge base: (a) group interviews with farmers and crop consultants (the crop consultants involved in this study are working with the LKP (Association for Bavarian farmers)); (b) discussion of data relevant to the N fertilization in winter wheat and the possibility of using these to improve the knowledge base in the Crop Portal
To define the requirements for a knowledge base on fertilization, experienced consultants were accompanied in face-to-face and telephone meetings, information letters from the consultancy were viewed, and the common language usage of consultants and farmers was witnessed during exchanges on agricultural issues
Acce5ssoifb2l2e tools and media documented during the advisory meetings expanded the knowledge base (Figure 1)
Summary
Crop production processes are complex, as they are influenced by the environment (soil, climate, weather), crop management (crop rotation, production system, field operations), and the genetics of the crop. These interactions and biological processes create the need for decision making throughout the growing season, but most critically during the vegetation period. Decisions are made on the basis of available information and practical knowledge but, increasingly, through using decision support systems (DSS) [1,2,3]. The ‘weak artificial intelligence’ of DSS can support human reasoning and technical applications in certain domains [4]
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