Características dos componentes de ovos da linhagem Ross de idades diferentes via análise multivariada

Traldi, Ana Beatriz; Silva, Fabiane de Lima; Hongyu, Kuang; Sartorio, Simone Daniela; Menten, José Fernando Machado

doi:10.19084/rca17145

Cited by 2 publications

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“…It is important to note that the PCA and CVA are the main techniques of multivariate analysis in use on several studies in animal production. However, most researchers still use univariate analysis, a limited approach when the need to evaluate several variables exist (Traldi et al, 2018). The present study aimed to evaluate the results of both techniques, PCA and CVA, and their differences in evaluating the genetic divergence between 7 genotypes of colored chicken for meat yield and meat quality characteristics.…”

Section: Introductionmentioning

confidence: 99%

Comparison between two multivariate analyses for the evaluation of genetic divergence for carcass and meat quality traits in alternative lines of chicken

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et al. 2021

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The univariate analysis is becoming harder to use due the increasing number of characteristics of economic importance in agricultural industry. The multivariate approach provides an answer to this issue, allowing to analyze several traits when comparing different methodologies, genetics and products. This study aimed to use and compare the canonical variable analysis (CVA) and principal component analysis (PCA) to evaluate 7 genotypes of alternative lines of chicken (Caboclo, Carijó, Colorpak, Gigante Negro, Pesadão Vermelho, Naked Neck and Tricolor). The study evaluated 840 male chicks reared at 91 days from these genotypes, in a completely randomized design with 4 replicates per genotype. Different traits (23) were measured, and only 7 remained relevant after the multivariate approach: Carcass yield, Breast Yield, Back Yield, Cooking Loss, lightness, yellowness and water holding capacity. Both analyses remained with two variables explaining the variating. The Pearson correlation was used to measure the traits responsible for the most variance between genotypes. On the principal component cooking loss, carcass and breast yields, and the color parameters lightness and yellowness were the most relevant, while on canonical variables it was carcass yield, breast yield, lightness, yellowness and back yield. Both analysis resulted in similar conclusion, allowing to classify the genotypes in three major groups: 1 (Pesadão vermelho, Carijó, Colorpak, Nacked Neck), 2 (Gigante Negro and Caboclo) and 3 (Tricolor). PCA and CVA facilitate the interpretation of data with several traits of importance, showing the main traits responsible for genetic divergence.

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Section: Introductionmentioning

confidence: 99%