Changes in Meat Quality and Genetic Parameter Estimation between Fresh and Frozen-Thawed Samples in Crossbred Commercial Pigs
Notice bibliographique
Résumé
ObjectivesThe objectives were: (1) to estimate heritability of important meat quality traits in fresh and frozen-thawed pork; (2) to estimate phenotypic, genetic and environmental correlations of meat quality measurements between and within fresh and frozen-thawed pork; and (3) to analyze the effect of crude fat content on meat quality changes from fresh to frozen-thawed pork in commercial crossbred pigs.Materials and MethodsData from 2,027 crossbred commercial pigs including pork color (L*, a*, and b*), intramuscular pH and drip loss measurements performed on m. longissimus dorsi when fresh and when thawed after frozen storage were used to estimate the genetic parameters for these meat quality characteristics using univariate and bivariate animal models in ASReml. The differences (∆) in the meat quality measurements between fresh and frozen-thawed samples were tested by paired t test (dependent t test) using SAS 9.3 (SAS Inst. Inc., Cary, NC) with a significance level of P < 0.0001.ResultsAll meat quality traits changed significantly (P < 0.0001) from fresh to frozen-thawed status and intramuscular crude fat content exerted a heteroscedastic effect (P < 0.001) on the magnitude of this change. Meat quality measurements of fresh pork were all moderately to highly heritable (h2 = 0.212 to 0.436), with heritability estimates for L* (h2 = 0.434 fresh samples, versus 0.244 frozen-thawed), pH (h2 = 0.221 fresh, 0.183 frozen-thawed) and drip loss (h2 = 0.333 fresh, 0.139 frozen-thawed) were higher when estimated using fresh rather than frozen-thawed data, while heritability estimates of a* (h2 = 0.326 fresh, 0.427 frozen-thawed) and b* (h2 = 0.212 fresh, 0.242 frozen-thawed) were comparable for fresh and frozen-thawed data when their standard errors were considered. Genetic correlations for L*, a*, b* and pH between fresh and frozen-thawed meat were high (rA = 0.665, 0.816, 0.442, and 0.853 for L*, a*, b* and pH, respectively) while genetic correlation for drip loss was moderate (rA = 0.236). Genetic correlations estimated within fresh and frozen-thawed measurements specifically between L* and a* (rA = –0.240 in fresh and –0.440 in frozen-thawed), L* and b* (rA = 0.760 in fresh and 0.483 in frozen-thawed), a* and b* (rA = 0.357 in fresh and 0.450 in frozen-thawed) were all moderate to high, but genetic correlations between a* and pH (rA = 0.082), b* and drip loss (rA = 0.128) in frozen-thawed samples were low. Genetic correlation between pH and drip loss estimated in frozen-thawed samples (rA = –0.096) was smaller than that in fresh samples (rA = –0.187).ConclusionWe concluded that while either fresh or frozen-thawed pork samples can be used for L*, a*, and b* measurements, pH and drip loss should be measured using fresh rather than frozen-thawed pork for genetic selection.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».