PSXIII-12 Estimation of zinc response in terms of growth performance and plasma zinc in pigs by meta-analysis.
Notice bibliographique
Résumé
Abstract Zinc is an essential nutrient for many metabolisms including protein, carbohydrate and lipid metabolism. Current EU legislation allows up to 150 ppm of total Zn/kg of feed, but the NRC estimate that 100 mg Zn/kg can fulfill the requirement. When pig is fed excess, a large part of this Zn is excreted causing environmental issues and participating in overall antibioresistance. The purpose of this study was to carry out a meta-analysis of the available literature information to determine the response different criteria to dietary Zn concentration. Plasma Zn, growth performance and bone data were search. Studies that used at least three concentrations of Zn in the diet were selected, this resulted in 65 Zn dose–response experiments. Then, only experiment where increasing Zn concentration add an impact on Y criteria were kept. Because of differences between experiments (e.g., age, genetic, duration) the response criteria were standardized with the highest response receiving a value of 100% and the other express in relative to this control. Also only experiment with doses lower than 1200 ppm were kept. This results in 13 dose-response for Average daily gain (ADG), 11 for Average Daily Feed Intake (ADFI), 24 for plasma zinc and only 6 for bone Zn which has not been studied due to a lack of data. The linear-plateau (LP) and quadratic-plateau (QP) models were tested to estimate the Zn requirement using ADG, ADFI and Plasma Zn. Due to scarcity of data, it was not possible to assess the impact of diet-related factors that influence the dietary Zn response such as phytate, calcium and copper. As expected, a Zn concentration below the requirement resulted in important reductions in both growth performance and plasma Zn. Model type has an important impact on the estimated requirement while the fit was similar. Using ADG and ADFI as response criteria, the Zn requirement was estimated at 58 ± 5.6 ppm for ADG with the LP and 80 ± 11 ppm with the QP. For ADFI the requirements were 52 ± 4.7 ppm and 64 ± 8.7 ppm for LP and QP respectively. Finally, for plasma Zn the requirements were higher than for growth performance; 86 ± 6.2 ppm and 114 ± 12 ppm. Using the LP model, increasing the Zn level from 20 to 40 ppm resulted in an increase in ADG, ADFI and plasma Zn by 21, 16 and 49%. Based on the outcome of this study, the requirements varied between 52 ppm for ADG with the QP model to 126 ppm for plasma Zn with the QP model. This latter value is higher than the 100-ppm recommendation of NRC (2012), but lower than the 150-ppm maximum level allowed for swine in Europe.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
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 | 0,022 | 0,022 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,002 |
| Méta-épidémiologie (sens large) | 0,012 | 0,060 |
| Bibliométrie | 0,005 | 0,005 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,004 | 0,001 |
| Science ouverte | 0,003 | 0,002 |
| Intégrité de la recherche | 0,003 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 0,001 |
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 ».