An expert system for predicting orchard yield and fruit quality and its impact on the Persian lime supply chain

In recent years academics and industrials have shown an interest in agricultural systems and their complex and non-linear nature, aiming to improve production yield in the agricultural field. Innovative strategies and methodological frameworks are thus required to assist farmers in decision making for an efficient and effective resource management. In particular, this research concerns the structural problem of the Persian lime supply chain in Mexico, which still leads to low production yield over short time periods with heterogeneous fruit quality and also to the emergence of excessive middleman businesses arising from a fragmentation between orchard and exporting companies that constitute the first two links in the associated supply chain Based on the Persian lime production cycle, an Expert System (ES) using Fuzzy Logic involving an inference engine with IF-THEN type rules is presented in this paper. A Mamdani model codifies the decision criteria related to agricultural practices for growing Persian lime in non-irrigated orchards. The ES allows the farmer to boost production in orchards by modeling application scenarios for agricultural practices. A case study based on an exporting company's fruit supply is discussed, in which the ES proves to be a useful tool to aid the decision making involved in the application of agricultural practices in the orchard. Results show an increase in production yield and fruit quality in the orchard, as well as a better synchronization between orchard and exporting companies, with a significant impact on inventory levels of fresh fruit in the link Persian lime exporting company. (C) 2014 Elsevier Ltd. All rights reserved.