Abstract
ABSTRACT The objective of this study was to apply multivariate analysis techniques such as principal component and canonical discriminant analyses to a set of performance and carcass data of Santa Inês sheep, to identify the relationships and select the variables that best explain the total variation of the data, in addition to quantifying an association between performance and carcass characteristics. The main components generated were efficient in reducing a cumulative total variation of 25 original variables correlated to four linear combinations, which together explained 80% of the total variation of the data. The first two principal components together explained approximately 65% of the total variation of the variables analyzed. In the first two linear combinations, the characteristics with the highest factor loading coefficients were cold carcass weight (CCW), hot carcass weight (HCW), empty body weight (EBW), average weight (AW), croup width (CW), cold carcass yield (CCY), and hot carcass yield (HCY). The variables selected in the canonical discriminant analysis, in order of importance, were total carbohydrate intake (TCI), total digestible nitrogen intake (TDNI), dry matter intake (DMI), non-fibrous carbohydrate intake (NFI), and fiber detergent neutral intake (NDFI). The first canonical root shows a correlation coefficient of approximately 0.82, showing a high association between the performance variables. The classification errors in the discriminant analysis were less than 5%, which were probably due to the similarity between individuals for the studied traits. The multivariate techniques were adequate and efficient in simplifying the sample space and classifying the animals in their original groups.
Highlights
The good adaptability of sheep to semi-arid conditions was a determining factor for the growth in sheep farming in Brazil (SILVA, 2017b)
Eight variables related to consumption were selected: dry matter intake (DMI), organic matter intake (MOI), crude protein intake (CPI), ether extract intake (EEI), total carbohydrate intake (TCI), non-fibrous carbohydrate intake (NFCI), total digestible nutrient intake (TDNI), total digestible nutrient (TDN) and, in the second, there were 17 variables related to carcass yield, namely: average weight (AW), external length (EL), internal length (IL), chest width (CW), croup perimeter (CP), croup width (CW), leg length (LL), leg perimeter (LP), chest depth (CD), chest perimeter (CP), cold carcass weight (CCW), carcass compactness index (CCI), hot carcass weight (HCQ), hot carcass yield (HCY), cold carcass yield (CCY), empty carcass weight (ECW), and rib eye area (REA)
The analyzed variables were subjected to standardization by mean and standard deviation, to eliminate the differences between units of measurement and thereby avoid redundancies in the application of the aforementioned multivariate techniques
Summary
The good adaptability of sheep to semi-arid conditions was a determining factor for the growth in sheep farming in Brazil (SILVA, 2017b) This favorable condition for sheep allows advances in animal productivity, since this is the main focus of farmers, always seeking to meet market demands (SALES, 2017). Carcass measurements allow comparisons between weight and age at slaughter, in addition to enabling the best choice of more viable feeding systems (SILVA; PIRES, 2000; SILVA et al, 2010) In this market condition and understanding the essential needs for good production performance, the selection of animals is necessary to guarantee a high growth rate, good reproduction, meat quality, and satisfactory carcass yield (MAYER et al, 2017)
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