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Production of the Persian lime (Citrus latifolia tanaka) has been the main objective of several studies related to the problem of low performance of yield and fruit quality in the orchard, attributed among different technological factors to the minimal application of Good Agricultural Practices (GAP) and to the cultural aspects of the producer. This paper contributes to the recognition of the behavior patterns of GAP for seasonal orchard (SO), to allow the Persian lime producers to make the right decisions assessing and improving the management of their orchards. To identify the behavior patterns in the Persian lime production process an expert system (ES) based on fuzzy logic proposed by Fernández et al. (2014) has been used, in which a set of inference rules based on the knowledge of experts in this field is encoded to explain the interrelationship of the agricultural practices and uncertainties in the production of Persian lime: Pruning, Soil nutrition, Pests Control, Planting density, Tree production, Wind, Rainfall. The ES simulates from agricultural practices and uncertainties, the Persian lime production system in three stages of fruit growth, which represent the fuzzy models of the ES: flowering, bud, and fruit. The manipulation of the agricultural practices in the ES allowed to model production scenarios for SO of Persian lime, and helped to identify behavior patterns in these practices with production yield and fruit quality. The results demonstrate that if prior to fertilization, the practice of "pruning" the tree is performed, orchard productivity increases. However, when the "pruning" (aesthetics or stressful) is performed less than 50mmmonth-1 of rain, even in optimal conditions of application of nutrients and pest control, the production yield is similar. The modeling scenarios of the ES provide information regarding behavior patterns to the producer, and the interrelation of agricultural practices in uncertain environments of rain and wind in order to improve the decision-making process in Persian lime production.
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 companys 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.