Multivariate Analysis in Food Production: Thermal Regulation Discriminant Analysis in Meat Quality

The objective of this research was to reduce the dimensionality of the original set of variables by eliminating redundant information and enabling the recommendation of variables to be evaluated in future experiments. A total of 240 European quail chicks (Coturnix coturnix Japonica), aged 1 day and with an average weight of 8 ± 0.50 g, were used. It was observed that weight gain (32.75%), liver (37.19%), and intestine (33.54%) exhibited the highest coefficients of variation. On the other hand, cloacal temperature had the lowest coefficient of variation (0.88%), indicating low variability in respiratory rate (16.23%) and surface temperature (3.55%). In total, the three main components together explain 74.65% of the data variation, indicating that, among the 16 variables analyzed, 13 were significant in explaining the observed variability. The variables heart weight, liver, and gizzard were not considered relevant for this study, as their impact on the multivariate analysis was minimal. These results have direct implications for the food industry, as they reveal factors that affect meat quality and consumer acceptance.