From hypothesis to practice, use of a log-linear model to predict and evaluate the response of non starch polysaccharide enzymes in poultry feeds
Notice bibliographique
Résumé
Enzymes have been widely used as a feed additive to improve growth performance of poultry and domestic animal. However, it has not been possible to accurately predict and evaluate the response obtained with a given dose of a specific enzyme preparation. The objective of this research was to determine if a new mathematical approach, a log-linear prediction model equation, could be used to predict and evaluate the response of chicks to a dietary enzyme supplementation. Two dose-response experiments with Leghorn chicks and those from several publications were studied to determine whether a simple general equation could be used to predict the relationship between the amount of a feed enzyme added to a diet and chick performance. An in vitro dietary viscosity assay was developed to determine whether it could be used in conjunction with the model as the predictor or evaluator. The results demonstrated that the model was able to accurately predict (high r2 values) the response of chicks fed diets containing the different amounts of an enzyme and different proportions of two cereals. The slope of the model was a measure of the efficacy of the feed enzyme. The efficacy, in turn, was able to correctly evaluate the effects of different feed enzymes when added to a diet and to identify the target cereal for an enzyme. In addition, a Multi-purpose Enzyme Analyzer has been developed based on the model. The analyzer was able to determine the optimal amount of an enzyme and a substituted cereal that should be used in a diet for maximal profit, and to determine the amounts and the expected prices of the enzyme and cereal that will yield a given profit. Therefore, the effect of a feed enzyme could be evaluated using maximal profit as a criterion. Thus, the most profitable effect of different feed enzymes and the cerea s that should be used for a given feed enzyme could be determined. Furthermore, a dietary viscosity assay has been developed. The results indicated that there was a linear relationship between the log of dietary viscosity change measured by the assay and the log of amount of enzyme added to a diet (r2 = 0.99, P < 0.005). The values from the assay were able to predict the response of chicks to a feed enzyme and also evaluate the efficacy of different feed enzymes, especially for those enzymes that hydrolyzed the viscous compounds in the diet. These studies demonstrated that the response of chicks to a feed enzyme and the efficacy of the enzyme could be predicted and evaluated on the basis of a log-linear model using different criteria (performance and economic return), and different type of studies (in vivo and in vitro).
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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 | 0,010 | 0,018 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,002 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,003 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».