Effects of sustainable agronomic intensification in a forage production system of perennial grass and silage corn on nutritive value and predicted milk production of dairy cattle
Notice bibliographique
Résumé
The objectives were to determine the effects of incrementally applied improved nutrient management, alternative cropping practices, and advanced production technologies in a dual forage system of perennial grass and silage corn on nutrient composition and in vitro ruminal fiber digestibility of the forages and, using these data as inputs into the Cornell Net Carbohydrate and Protein System, to predict milk production, indicators of nitrogen (N) utilization, and N excretion of dairy cattle. Farm management systems (farmlets) included a conventional system with whole manure slurry broadcast to a late maturing corn hybrid and grass harvested with 5 cuts per year (F1); improved nutrient management with a separated manure system where the sludge was applied to corn and the liquid was applied to grass (F2); improved nutrient management and alternative cropping practices with separated manure, an early maturing corn hybrid interseeded with a relay winter cover crop, and grass harvested with 3 cuts per year (F3); and improved nutrient management and alternative cropping practices combined with advanced production technologies that included irrigation and a nitrification inhibitor (F4). The field trial was a randomized complete block design over 2 yr with 4 blocks each divided into grass and corn, 4 subplots within each block for each crop, and 2 replicates within each subplot. Diets were formulation with 60% forage and 40% concentrate where the grass and corn as silage was proportional to yield for land allocations of grass and corn of 80:20, 60:40, 40:60, and 20:80. Data were analyzed using the MIXED procedure of SAS (SAS Institute Inc.). The intensified management systems (F2, F3, and F4) increased the crude protein (CP) concentration of corn with no effects on starch concentration [32.1% dry matter (DM)] compared with the conventional system (F1). Decreasing cuts of grass from 5 to 3 reduced the CP concentration in the spring harvest (15.8% vs. 12.5% DM), and increased fiber concentration and reduced digestibility in the spring, summer, and fall harvests. A common concentrate was formulated for the conventional farmlet and then combined with the forages for each farmlet within each land allocation. Forages grown under intensified management to improve N capture increased the CP concentration of the diets. However, reducing the number of cuts of grass from 5 to 3, combined with the corn and relay crop to increase yield, reduced milk production across all land allocations. To complement the nutritive value of the forages grown under each management system and land allocation, the concentrates were reformulated, which reduced dietary CP, improved the indicators of N utilization (e.g., milk urea N and milk N efficiency), reduced N excretion, and improved milk yield with no differences among the farmlets. Increasing land allocated to corn supported higher milk yield at lower dietary CP concentrations (16.5% vs. 15.4% DM) with improved milk N efficiency and lower N excretion. Intensified agronomic management increased the CP of the combined forages decreasing the need for supplemental CP in the concentrate and could reduce the importation of feed N to the farm.
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 | 0,000 | 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 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 ».