Genetic evaluation for latent variables derived from factor analysis in broilers

Paiva, José Teodoro de; Oliveira, Hinayah Rojas de; Nascimento, Moysés; Nascimento, Ana Carolina Campana; Silva, H T; Henriques, Renata Felisberto; Lopes, Paulo Sávio; Silva, F F; Veroneze, Renata; Ferraz, José Bento Sterman; Eler, Joanir Pereira; Mattos, E. C.; Gaya, Leila de Genova

doi:10.1080/00071668.2019.1680801

Cited by 8 publications

(6 citation statements)

References 28 publications

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“…Multivariate techniques proved to be adequate for the evaluation of high dimensional data analyses because it decreases the complexity involved in the univariate analyses of multiple variables, being a useful tool to investigate variable relationship (Macciotta et al, 2012;Teixeira et al, 2015;Conte et al, 2016;Paiva et al, 2020). Among other multivariate techniques, factor analysis can reduce the dimensionality, while capturing a certain amount of the overall variance in the observed variables and generating satisfactory results in pig research (Silva et al, 2011;Teixeira et al, 2015Teixeira et al, , 2016.…”

Section: Multivariate Factor Analysismentioning

confidence: 99%

Depicting latent variables considering different pig genetics and nutritional plans in crossbred pigs

Henriques¹,

Silva²,

Veroneze³

et al. 2022

Revista Brasileira De Zootecnia

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Breeding and geneticsFull-length research article Depicting latent variables considering different pig genetics and nutritional plans in crossbred pigsABSTRACT -We aimed to reduce the dimensionality of quantitative traits in pigs applying factor analysis. Quantitative variables were collected, and the factor analysis extracted five factors with biological meaning related to performance, carcass quality, carcass yield, meat quality, and initial pH. These factors were posteriorly used as dependent variable to evaluate the effects of genetic groups (Piau, Duroc, and Pietrain crossbreds), nutritional plans (low, medium and high lysine levels) and sex. An interaction effect between genetic group and sex was observed in performance, in which Duroc crossbred showed the greatest scores. The Pietrain genetic group showed greater values of carcass quality compared with Duroc and Piau, while Piau crossbred pigs had greater values for meat quality compared with Pietrain and Duroc. A greater carcass yield was observed in Pietrain crossbred compared with Duroc pigs. Pigs fed under low lysine level had the lowest performance values. Carcass yield was affected by nutritional plans, in which the medium lysine level showed the greatest values. Meat quality was improved by the nutritional plan with high lysine level compared with the low lysine level. Initial pH showed increased means when using nutritional plans with low and medium lysine levels in diet composition. With regard to sex effects, a greater carcass quality was found for gilts compared with barrows. The reduction of the data dimensionality allowed the joint evaluation of genetic group, nutritional plan, and sex based on new latent variables that represented the original dataset under easier framework based on factors' biological interpretation.

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Section: Multivariate Factor Analysismentioning

confidence: 99%

Depicting latent variables considering different pig genetics and nutritional plans in crossbred pigs

Henriques¹,

Silva²,

Veroneze³

et al. 2022

Revista Brasileira De Zootecnia

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“…The descriptive statistics and phenotypic correlations among the 14 traits are shown in Tables 1 and 2, respectively. More information about population and data can be found in Paiva et al (2020).…”

Section: Phenotypic Datamentioning

confidence: 99%

Searching for causal relationships among latent variables concerning performance, carcass, and meat quality traits in broilers

Silva

Paiva

Botelho

et al. 2021

J Animal Breeding Genetics

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Over the years, increasing body weight has been the main selection objective of broiler breeding programs. The selection resulted in birds with higher growth rates and feed efficiency, while production costs were minimized (Alnahhas et al., 2016). However, changes in consumer preferences associated with new industries demands have increased the relevance of meat quality traits in the modern broiler market (Alnahhas et al., 2014). The inclusion

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“…In animals, FA was successfully used to obtain estimates of genetic parameters between common latent factors in cattle and dairy buffaloes (Aspilcueta-Borquis et al 2012 ; Macciotta et al 2006 ; 2012 ). Paiva et al ( 2019 ), used formed latent variables, identified as pseudo-phenotypes, in the genetic evaluation of broiler chickens under Bayesian structure. Latent variables also allowed to simultaneously study a set of important characters in pigs, for later use in GS Analyses (Teixeira et al 2016 ).…”

Section: Introductionmentioning

confidence: 99%

Factor analysis applied in genomic selection studies in the breeding of Coffea canephora

Paixão

Nascimento

et al. 2022

Euphytica

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Brazil stands out worldwide in the production of coffee. The observed increases in its productivity and morpho agronomic traits are the results of the improvement of several methodologies applied in obtaining improved cultivars, among which the predictive methods of genetic value stand out. These contribute significantly to the selection of higher genotypes, increasing the genetic gain per unit time. In this context, genomic-wide selection (GWS) is a tool that stands out, since it allows predicting the future phenotype of an individual based only on molecular information. Performing joint selection of traits is the interest of most breeding programs, and factor analysis (FA) has been used to assist in this end. The aim of this study was to evaluate the use of FA in the context of GWS, in genotypes of Coffea canephora . It was found that FA was efficient to elucidate the relationships between the traits and generate new variables. The factors formed can assist in the selection, as in addition to allowing joint interpretations, they present good estimates of predictive capacity, heritability and accuracy. Furthermore, high agreement was observed between the individuals selected based on the factors and those selected considering the individual traits. Additionally, it was observed agreement between the top 10% individuals selected based on the “vigor factor” and each variable individually. However, the selection based on “vigor factor” presented individuals with more suitable size from the phytotechnical point of view.

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Genetic evaluation for latent variables derived from factor analysis in broilers

Cited by 8 publications

References 28 publications

Depicting latent variables considering different pig genetics and nutritional plans in crossbred pigs

Depicting latent variables considering different pig genetics and nutritional plans in crossbred pigs

Searching for causal relationships among latent variables concerning performance, carcass, and meat quality traits in broilers

Factor analysis applied in genomic selection studies in the breeding of Coffea canephora

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