Abstract
ABSTRACT This study aimed to establish criteria for eliminating redundant variables, to know the magnitude of the data relationship, and to provide information that helps researchers in the use of the technique to analyze and interpret production data and egg quality. The data used in this work was obtained from four successive generations of the quail lineage developed by the Department of Animal Science of the Federal University of Pelotas. The characteristics were measured from the 42nd day of age, when the egg production period began, until 126 days of production, obtaining three 28 day periods (cycles) in the four successive generations, totaling 545 females. Of the twelve original variables, only seven demonstrated potential to be maintained in future experiments, representing a 42% exclusion. The main philosophy of this study was the analysis of the studied variables and made possible the understanding of the relationship and the correlations.
Highlights
Coturniculture has gained space within the poultry industry, because it allows a quick return of the invested capital to the producers, with the main products of this activity being the production of eggs and meat (Teixeira et al, 2013)
One of the bottlenecks of this production system is obtaining genetic material, which for both egg production and meat production depend on importation (Dionello et al, 2008), since Brazil does not have its own genetic material
Genetic evaluations are performed based on data collected through individual performance tests, and the estimation of genetic values via best linear unbiased prediction (BLUP)
Summary
Coturniculture has gained space within the poultry industry, because it allows a quick return of the invested capital to the producers, with the main products of this activity being the production of eggs and meat (Teixeira et al, 2013). In search of a solution to this problem, some institutions have leveraged breeding programs for meat-type quail. Genetic evaluations are performed based on data collected through individual performance tests, and the estimation of genetic values via best linear unbiased prediction (BLUP). Based on these studies, the selection criteria are established for the generations (Viana et al, 2000), guaranteeing the renewal of herds with animals of superior genetic potential, adapted to the production systems in Brazil
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