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Study of Meat and Carcass Quality-Related Traits in Turkey Populations through Discriminant Canonical Analysis
The present research aimed to determine the main differences in meat and carcass quality traits among turkey genotypes worldwide and describe the clustering patterns through the use of a discriminant canonical analysis (DCA). To achieve this goal, a comprehensive meta-analysis of 75 documents discus...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10606380/ https://www.ncbi.nlm.nih.gov/pubmed/37893720 http://dx.doi.org/10.3390/foods12203828 |
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author | Salgado Pardo, José Ignacio Navas González, Francisco Javier González Ariza, Antonio León Jurado, José Manuel Galán Luque, Inés Delgado Bermejo, Juan Vicente Camacho Vallejo, María Esperanza |
author_facet | Salgado Pardo, José Ignacio Navas González, Francisco Javier González Ariza, Antonio León Jurado, José Manuel Galán Luque, Inés Delgado Bermejo, Juan Vicente Camacho Vallejo, María Esperanza |
author_sort | Salgado Pardo, José Ignacio |
collection | PubMed |
description | The present research aimed to determine the main differences in meat and carcass quality traits among turkey genotypes worldwide and describe the clustering patterns through the use of a discriminant canonical analysis (DCA). To achieve this goal, a comprehensive meta-analysis of 75 documents discussing carcass and meat characteristics in the turkey species was performed. Meat and carcass attributes of nine different turkey populations were collected and grouped in terms of the following clusters: carcass dressing traits, muscle fiber properties, pH, color-related traits, water-retaining characteristics, texture-related traits, and meat chemical composition. The Bayesian ANOVA analysis reported that the majority of variables statistically differed (p < 0.05), and the multicollinearity analysis revealed the absence of redundancy problems among variables (VIF < 5). The DCA reported that cold carcass weight, slaughter weight, sex-male, carcass/piece weight, and the protein and fat composition of meat were the traits explaining variability among different turkey genotypes (Wilks’ lambda: 0.488, 0.590, 0.905, 0.906, 0.937, and 0.944, respectively). The combination of traits in the first three dimensions explained 94.93% variability among groups. Mahalanobis distances cladogram-grouped populations following a cluster pattern and suggest its applicability as indicative of a turkey genotype’s traceability. |
format | Online Article Text |
id | pubmed-10606380 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-106063802023-10-28 Study of Meat and Carcass Quality-Related Traits in Turkey Populations through Discriminant Canonical Analysis Salgado Pardo, José Ignacio Navas González, Francisco Javier González Ariza, Antonio León Jurado, José Manuel Galán Luque, Inés Delgado Bermejo, Juan Vicente Camacho Vallejo, María Esperanza Foods Article The present research aimed to determine the main differences in meat and carcass quality traits among turkey genotypes worldwide and describe the clustering patterns through the use of a discriminant canonical analysis (DCA). To achieve this goal, a comprehensive meta-analysis of 75 documents discussing carcass and meat characteristics in the turkey species was performed. Meat and carcass attributes of nine different turkey populations were collected and grouped in terms of the following clusters: carcass dressing traits, muscle fiber properties, pH, color-related traits, water-retaining characteristics, texture-related traits, and meat chemical composition. The Bayesian ANOVA analysis reported that the majority of variables statistically differed (p < 0.05), and the multicollinearity analysis revealed the absence of redundancy problems among variables (VIF < 5). The DCA reported that cold carcass weight, slaughter weight, sex-male, carcass/piece weight, and the protein and fat composition of meat were the traits explaining variability among different turkey genotypes (Wilks’ lambda: 0.488, 0.590, 0.905, 0.906, 0.937, and 0.944, respectively). The combination of traits in the first three dimensions explained 94.93% variability among groups. Mahalanobis distances cladogram-grouped populations following a cluster pattern and suggest its applicability as indicative of a turkey genotype’s traceability. MDPI 2023-10-19 /pmc/articles/PMC10606380/ /pubmed/37893720 http://dx.doi.org/10.3390/foods12203828 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Salgado Pardo, José Ignacio Navas González, Francisco Javier González Ariza, Antonio León Jurado, José Manuel Galán Luque, Inés Delgado Bermejo, Juan Vicente Camacho Vallejo, María Esperanza Study of Meat and Carcass Quality-Related Traits in Turkey Populations through Discriminant Canonical Analysis |
title | Study of Meat and Carcass Quality-Related Traits in Turkey Populations through Discriminant Canonical Analysis |
title_full | Study of Meat and Carcass Quality-Related Traits in Turkey Populations through Discriminant Canonical Analysis |
title_fullStr | Study of Meat and Carcass Quality-Related Traits in Turkey Populations through Discriminant Canonical Analysis |
title_full_unstemmed | Study of Meat and Carcass Quality-Related Traits in Turkey Populations through Discriminant Canonical Analysis |
title_short | Study of Meat and Carcass Quality-Related Traits in Turkey Populations through Discriminant Canonical Analysis |
title_sort | study of meat and carcass quality-related traits in turkey populations through discriminant canonical analysis |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10606380/ https://www.ncbi.nlm.nih.gov/pubmed/37893720 http://dx.doi.org/10.3390/foods12203828 |
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