Eliciting expert knowledge for fuzzy evaluation of agricultural production systems

Public concern nowadays is an important frame of reference for the development of agricultural production systems. The development of such systems, therefore, involves both society level and production system level. Following Zadeh's principle of incompatibility, information obtained at production system level is interpreted at society level in linguistic terms. Fuzzy models promise to be a valuable tool as they link measurable information to linguistic interpretation using membership functions. The objective of this paper is to outline a procedure which deals with criticism regarding the inherent subjectivity in the construction of membership functions when using expert knowledge. The procedure guarantees the selection of appropriate expert knowledge, and provides a guideline supporting the selection of methods to elicit expert knowledge and construct membership functions. Also on the basis of the results in an illustrative example, it is concluded that the procedure outlined in this paper suitably deals with criticism regarding membership functions and, therefore, enables a practical implementation of fuzzy evaluation of agricultural production systems. Current research implements the procedure to build a fuzzy model which evaluates egg production systems in relation to public concern about the welfare of laying hens