using modelling to enhance zootechnical and economic performance in drylands goat meat production

This study aimed to develop a mathematical function for the performance of a goat production system for meat production, based on zootechnical and economic indicators. data on the technical and economic parameters used in the models were obtained from the goat herd control file database, which covered the years 2013 to 2017. descriptive statistics were performed using proc univariate, while multiple linear regression models were developed using proc glmselect. multiple linear regression analysis showed an adjusted coefficient of determination, indicating that the variables mortality rate, calving interval, weaning rate, and reproductive efficiency explained 95 percent of the variations in total goat weight at weaning. the results indicated that total weight of offspring at birth and weaning, mortality rate, reproductive efficiency, and gross income affect the system's profitability and can be used as decision-making criteria in meat goat farming. furthermore, feed costs and rainfall also influenced the predicted variables, highlighting the importance of integrating climatic and economic factors in herd management. the multiple linear regression equations developed in this study are a useful and accessible tool for ruminant technicians and producers, allowing simulations and analyses of different production and economic scenarios, contributing to strategic planning and the development of the meat goat production system.