PSV-2 Impact of Diseases in Pig Production on Carcass and Meat Quality
Notice bibliographique
Résumé
Abstract Several diseases, including Porcine Respiratory and Reproductive Syndrome (PRRS), are present in pig herds. The effects of diseases on growth performance are generally well known, but there is a lack of information on the consequences on carcass and meat quality. The aim of this project was to assess the impact of diseases present in the nursery and finishing on performances, carcass yields and meat quality. The trial was carried out at the Deschambault Swine Evaluation Station, where a project aimed at evaluating disease resilience is being carried out. A total of 480 castrated piglets from 8 different batches entered the nursery barn every 3 weeks. Pigs were observed daily, and a careful examination of the clinical signs was carried out weekly on each animal, to separate pigs showing signs of disease from those in good health. Ultrasound measurements of back fat thickness, muscle depth and intramuscular fat (IMF) level were performed three different times during growth. When the pigs reached a body weight of approximately 120 kg, carcass quality and meat yield measurements were taken 18 to 24 hours after slaughter. The ultimate pH, color, water loss and marbling were measured on the loin. The presence of PRRS and other diseases had a significant impact on the growth performance of pigs in fattening and demonstrates that the presence of the virus in the herd significantly decreases the average daily gain (ADG). This difference has a direct impact on the number of days in fattening. Results for back fat thickness at the end of fattening show significant differences (P < 0.05) between uninfected pigs (14.7 mm), pigs infected in nursery (13.9 mm) and fattening (12.8 mm) only, and pigs that have been ill both in nursery and fattening (12.4 mm). These results indicate that the presence of diseases leads to a decrease in fat deposition in pigs at the end of fattening. However, results for IMF measured at the end of fattening demonstrate that the presence of diseases had no significant impact on the final IMF level (P > 0.10), varying between 2.05% for healthy pigs and 2.13% for animals that have been sick in nursery and fattening. The results obtained in the slaughterhouse have shown that the presence of diseases does not seem to have an impact on the various measures of meat quality (P > 0.05). Only drip loss shows a significant difference (P < 0.05) between healthy and sick animals. However, the low number of sick pigs in the batches evaluated could have limited the observed effects. The work carried out by the CDPQ has made it possible to quantify the impact of diseases by providing a better understanding of their impact on product quality.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 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) | 0,002 | 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 source (Gemma direct ou Codex distillé), 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 ».