A new look at energy discounts: using published studies to calculate discounted net energy values for dairy cows fed ad libitum
Notice bibliographique
Résumé
Correct assessment of the energetic density of a diet fed to dairy cows is fundamental to accurate prediction of performance. Feeding experiments using lactating Holstein cows fed ad libitum, as reported by North American research facilities in peer-reviewed publications since 1990 in which the actual NEl density of the diet could be calculated from performance, and three dietary energy prediction systems [i.e., NRC (1989), NRC (2001) and an approach developed at the University of California at Davis (UCD)] were used to determine if the NEl discount (i.e., depression) in diets above maintenance (M) energy intake (i.e., 1 ×M) is linear or curvilinear. The principle used was that the expected NEl of the diets could be estimated using the three systems (at 3 ×M ), as well as the NEl calculated from observed performance of the cows, and the deviation (or difference) between the actual and estimated dietary NEl density could be regressed against the actual NEl output (×M) to determine the form of the expected decline in the NEl density of the diet as the energy output (relative to maintenance energy intake) of the cows increased. Results show that output of NEl (×M) is not a predictor of the deviation of the actually calculated NEl level of the diet vs. that estimated by any system. This was unexpected, as all three NEl estimation systems presume a linear decline in the deviation as level of NEl output (×M) increases. In contrast to NEl output (×M), intake of DM (g kg-1 body weight) was a weak predictor (r2 = 0.36 to 0.39 depending on system) of the diet NEl density deviation. The best predictors of diet NEl deviation in all three systems were DM intake (g kg-1BW) and NEl output (×M) combined, where r2 values were much higher (0.76 to 0.79), and there was little evidence of prediction bias in any system. Results suggest that the NEl density of a diet is a function of the inherent characteristics of the diet (i.e., its intrinsic digestibility), its level of consumption, and the genetic merit (and/or stage of lactation ) of the cows that eat it. The lack of a relationship between the deviation of the actually calculated vs. predicted NEl concentration shows that the three NEl prediction equations examined are fundamentally incorrect in their assumption that the NEl concentration of diets declines as the NEl output (×M) of the cows consuming them increases. However, the inaccurate estimates of the actual NEl densities by the systems can be corrected by application of appropriate equations that consider the anticipated level of DM intake and NEl output. Key words: Discount, net energy for lactation
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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 | 0,033 | 0,100 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,006 | 0,007 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,006 | 0,007 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,003 |
| 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 ».