PERFORMANCE ANALYSIS AND CARCASS CHARACTERISTICS OF SANTA INÊS SHEEP USING MULTIVARIATE TECHNICS

• Published in: Caatinga 2020-10, Vol.33 (4), p.1150-1157
• Main Authors: MILANÊS, TARLAN OLIVEIRA, SOARES, LUCIANA FELIZARDO PEREIRA, RIBEIRO, MARIA NORMA, CARVALHO, FRANCISCO FERNANDO RAMOS DE
• Format: Article
• Language: eng ; por
• Subjects: AGRICULTURE, DAIRY & ANIMAL SCIENCE; AGRONOMY; Body weight; Carbohydrates; Carcasses; Classification; Correlation coefficient; Correlation coefficients; Croup; Discriminant analysis; Dry matter; FISHERIES; FOOD SCIENCE & TECHNOLOGY; FORESTRY; Multivariate analysis; Nuclear factor I; Sheep; Variation; VETERINARY SCIENCES
• ISSN: 0100-316X; 1983-2125; 1983-2125
• DOI: 10.1590/1983-21252020v33n430rc

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. RESUMO O objetivo com este estudo foi aplicar técnicas de análise multivariada, sendo elas: Componentes Principais e Discriminante Canônica, em um conjunto de dados de desempenho e carcaça de ovinos da raça Santa Inês. Para identificar as relações e selecionar variáveis que melhor explicam a variação total dos dados, além de quantificar associação entre os recursos de desempenho e carcaça. Os componentes principais gerados foram eficientes em reduzir variação total acumulada de 25 variáveis originais correlacionadas para quatro combinações lineares, que, juntas, tem capacidade de explicar 80% da variação total dos dados. Os dois primeiros componentes principais juntos explicam aproximadamente 65% da variação total das variáveis analisadas. Nessas du