490 Estimating enteric methane emission from beef heifers with different residual feed intake using greenfeed and respiration chambers
Notice bibliographique
Résumé
Greenhouse gas emission from the livestock sector is mainly contributed from enteric methane (CH4) production. Improving feed efficiency to reduce CH4 emission while maintaining productivity as well as accurate and robust measurement is of great environmental and economic importance. The objectives of this study were to: compare CH4 emissions measured using respiration chambers (RC) and the GreenFeed (GF) emission monitoring system and evaluate the relationship between residual feed intake (RFI) and enteric CH4 production. Sixteen crossbred replacement heifers (8 low-RFI, 8 high-RFI, 377 kg initial BW) were used to measure enteric CH4 emission. Heifers were group-housed in a pen and fed barley silage ad libitum and their individual feed intakes were recorded by automated feeding bunks. Heifers also received pellets dispensed from the GF emission monitoring system, used to attract and keep the animals in the unit for emission measurement. Enteric CH4 emission of individual animals was measured over two 25-d periods using RC (2 days/period) and GF systems (all days when not in chambers). Data were analyzed using the mixed procedure of SAS and differences are discussed at P ≤ 0.05. Estimates of CH4 (g/d) were greater for GF than RC (P < 0.001), but for CH4 yield the systems only differed for the high-RFI cattle (P = 0.01). Average CH4 emission was 202 and 222 g/d (P = 0.02) from the GF system, and 156 and 164 g/d (P = 0.40) in RC for the low- and high-RFI heifers, respectively. As expected, high-RFI heifers consumed 6.9% more feed (P = 0.03) compared to their more efficient counterparts (7.1 vs 6.6 kg DM/d). However, when adjusted for feed intake, CH4 yield (g/kg DMI) was similar for high- and low-RFI heifers (GF: 27.7 and 28.5, P = 0.25; RC: 26.5 and 26.5, P = 0.99). Intake declined for both groups when they were moved to the RC, and as such DMI was similar (P = 0.29) between groups when they were in the chambers. Our study found that the two measurement techniques differ in estimating CH4 emission, partially due to differences in conditions (lower feed intakes of cattle while in chambers, fewer days measured in chambers) during measurement. Furthermore, high- and low-efficiency cattle produce similar CH4 yield but different daily CH4 emission. We conclude that, when intake of animals is known, the GF offers a robust and accurate means of estimating CH4 emissions from animals under field conditions.
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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 | 0,000 | 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) | 0,001 | 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 ».