Ecuaciones de predicción del peso y rendimiento de carcasa de cuyes en base a sus atributos morfométricos

The aim of this study was to validate the use of mathematical equations to predict the weight and yield of the carcass of guinea pigs based on their morphometric measurements. The following measurements were determined in 60 male and female guinea pigs aging 11 to 12 weeks: head width (AC), head length (LC), thoracic depth (PT, thoracic width (AT), body length (LM) and left leg thickness (EP), in addition to live weight (BW). Carcass weight (PC) and yield (RC) were estimated based on carcasses of animals slaughtered after 12 hours of fasting. A multiple regression model and the Stepwise Regression procedure of the SAS statistical software were used to select and assess the contribution of the biometric attributes in determining the prediction equation with optimal goodness-of-fit characteristics for the variables to be predicted. It was found that PV, AC and AT are the best predictors of PC in males (R² = 0.98; Cp-Mallows = 2.35), and PV and AT in females (R² = 0.97; Cp-Mallows = 0.86); while AC and AT are for RC in males (R² = 0.61; Cp-Mallows = 3.24), and only AC in females (R² = 0.55; Cp-Mallows = 0.49). It is concluded that live weight is the morphometric attribute with the highest incidence for the prediction of carcass weight in guinea pigs in both sexes, while thoracic width and head width are for carcass yield in both sexes.