Expert system based on a fuzzy logic model for the analysis of the sustainable livestock production dynamic system.

• The ES capitalizes on the knowledge and experience of specialists in livestock production. • The ES shows 86.67% reliability for the control of livestock practices. • The ES demonstrated that food has the greatest weight in livestock production. This essay documents the development of an "Expert System" based on a Fuzzy Logic model, designed to analyze the outcome a number of variables have on the performance of livestock production (milk and meat) in the Huasteca region of Veracruz in order to support the decision-making of a Sustainable Livestock Production Dynamic System (SLPDS). The Expert System takes into consideration the following input variables: Temperature (T), Rain (RA), Breed (B), Health Plan Implementation (HP), Feeding Plan (FP) and Production System (PS). The aforementioned variables then have an impact on three output variables: Lactation Days (LD), Daily Milk Production (DMP) and Intervals between Births (IBB). Once the Fuzzy Logic model has been developed, an assessment of the variables is made through the Response Surface technique, which allows verifying how the variables behave in the system under study, and their impact on the output variables; as well as, testing different scenarios in order to validate the model and to identify the Livestock Production Systeḿs behavioral patterns. Through the application of Fuzzy Logic regarding the modeling of the 6 variables that impact the performance of livestock production, it is possible to capitalize on the knowledge and experience that producers have and what they have learned based on the observation and practice of many years. Therefore, being able to obtain reliable results that can be shared with agricultural producers and technicians for the improvement of the livestock productivity of the Huasteca region in the state of Veracruz. The Expert System is efficient showing an 86.67% reliability by comparing its results with a panel of specialists in livestock production. The test of the different scenarios shows interesting results when exposing the application of good livestock practices in certain conditions (temperature and rainfall) that maximize the milk and meat production of the region under study. [ABSTRACT FROM AUTHOR]