Use of multivariate analysis to evaluate the growth of Berganês and crossbreed in the northeastern semiarid

Authors

DOI:

https://doi.org/10.5039/agraria.v14i4a6713

Keywords:

discriminant analysis, factor analysis, biometry, crossbreed, sheep

Abstract

The objective of the present study was to test multivariate tools to evaluate the growth of Berganês and crossbreed in the Northeastern Semiarid region. Biometric measurements were performed at the beginning and at the end of the experiment in uncastrated male lambs belonging to the Berganês (BG), Berganês x Santa Inês (BSI), Dorper x Berganês (DB) genotypes and the Dorper x Santa Inês (DSI), of eight lambs per genotype. The design was completely randomized. Data were subjected to Person correlation analysis. It performed factor analysis based on principal components - (FA), in order to summarize the original set of variables in a few factors and to indicate the variables that most contribute to the evaluation of animal growth. A significant correlation (p < 0.01) was observed for most variables measured at the end of the experiment. The most important characteristics to evaluate the biometric growth of Berganês and crossbreed lambs are associated with the breed pattern and body development of the animals, according to factor analysis. The lambs were classified in their respective genotypes at the end of the experiment according to the discriminant analysis. The multivariate techniques used in this study were handy to understand and differentiate the Berganês genetic group and its crossbreed based on biometric characteristics.

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Published

2021-03-03

How to Cite

José Renaldo Vilar da Silva Filho, João Bandeira Moura Neto, Janaina Kelli Gomes Arandas, Lays Thayse Alves dos Santos, Paulo Alves Nogueira Filho, Francisco Fernando Ramos de Carvalho, Fernando Lucas Torres de Mesquita, & Maria Norma Ribeiro. (2021). Use of multivariate analysis to evaluate the growth of Berganês and crossbreed in the northeastern semiarid. Brazilian Journal of Agricultural Sciences, 14(4), 1-8. https://doi.org/10.5039/agraria.v14i4a6713

Issue

Section

Animal Science