
pmid: 20348370
Technological meat quality is a significant economic factor in pork production, and numerous publications have shown that it is strongly influenced both by genetic status and by rearing and slaughter conditions. The quality of meat is often described by meat pH at different times postmortem, as well as by color and drip loss, whereas carcass quality is often characterized by lean percentage. A meta-analysis of findings relating to 3,530 pigs reported in 23 publications was carried out to assess the effects of the halothane gene, sex, breed, and slaughter weight of animals on 7 selected variables: pH at 45 min postmortem, ultimate pH, reflectance (L*-value), redness (a*-value), yellowness (b*-value), drip loss, and lean percentage. Two statistical methods were used in the meta-analysis: the method of effect size and the better known random effects model. The method of effect size was associated with Markov chain Monte Carlo techniques for implementing Bayesian hierarchical models to avoid the problems of limited data and publication bias. The results of our meta-analysis showed that the halothane genotype had a significant effect on all analyzed pork quality variables. Between-study variance was evaluated with the Cochran (1954) Q-test of heterogeneity. Meta-regression was used to explain this variance, with covariates such as breed, sex, slaughter weight, and fasting duration being integrated into different regression models. The halothane gene effect was associated with the breed effect only for the following variables: L*-value, b*-value, and drip loss. Slaughter weight contributed significantly only to the explanation of differences in ultimate pH between homozygous genotypes. In response to inconsistencies reported in the literature regarding the difference between the genotypes NN and Nn, results of the meta-analysis showed that the difference between these 2 genotypes was significant for all the analyzed variables except the a*-value.
pig, Male, Meat, Genotype, Swine, Bayes Theorem, 630, Markov Chains, meat quality, meta-analysis, Animals Bayes Theorem Biological Markers Body Composition/ genetics Female Genotype Male Markov Chains Meat/ standards Monte Carlo Method Swine/genetics, [SDV.SA.SPA]Life Sciences [q-bio]/Agricultural sciences/Animal production studies, Body Composition, Animals, Female, [SDV.SA.SPA] Life Sciences [q-bio]/Agricultural sciences/Animal production studies, halothane gene, pig , Monte Carlo Method, Biomarkers
pig, Male, Meat, Genotype, Swine, Bayes Theorem, 630, Markov Chains, meat quality, meta-analysis, Animals Bayes Theorem Biological Markers Body Composition/ genetics Female Genotype Male Markov Chains Meat/ standards Monte Carlo Method Swine/genetics, [SDV.SA.SPA]Life Sciences [q-bio]/Agricultural sciences/Animal production studies, Body Composition, Animals, Female, [SDV.SA.SPA] Life Sciences [q-bio]/Agricultural sciences/Animal production studies, halothane gene, pig , Monte Carlo Method, Biomarkers
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