205 Effects of Timothy grass inclusion in 3-phase-feed and individual Precision fed growing- finishing pigs
Notice bibliographique
Résumé
Abstract Finding sustainable feed ingredients is essential for advancing sustainable pig production. Timothy grass, a perennial forage, shows promise as a nutritious ingredient for growing pigs that may also reduce the environmental impact of pork production. This study evaluated the effects of timothy meal inclusion (TI) on pig growth performance and body composition in two feeding systems (FS): conventional group 3-phase feeding (GPF) and individual precision feeding (IPF). Fifty-six pigs [37.4 ± 0.7 kg of body weight (BW)] from a high-performance genotype were randomly assigned to one of four dietary treatments based on FS and TI (with=1, without=0): GPF0, GPF1, IPF0, and IPF1. In the GPF1 treatment, TI was included at 8%, 16%, and 22% rates for the three growth phases, respectively. In IPF1, timothy was gradually increased based on BW to achieve a similar overall inclusion rate as GPF1. Average daily feed intake (ADFI) was recorded daily, and BW was weekly monitored, with body composition measured via dual X-ray at the beginning and end of each phase. Data was analyzed as repeated measures over time with FS, TI, sex, time, and their interactions as fixed effects and the individual as random effect. No significant three- or four-way interactions were found. ADFI increased over time (P< 0.001) but was not affected by FS or TI, although interactions between sex and time were observed (Sex×Time; P< 0.001). BW was not influenced by FS, but TI reduced final BW by 6% (TI×Time, P = 0.001). Overall, TI reduced ADG by 9% (TI×Time, P = 0.030) while also reducing the Gain:Feed ratio by 10% (TI×Time, P = 0.030). However, independent of TI, IPF pigs had 4% better Gain:Feed, with no changes in ADG and ADFI compared to GPF pigs. Protein deposition varied with TI (TI×Time, P=0.010), which reduced protein deposition in phases 1 and 2, and increased it in phase 3, indicating pigs adapted over time, with no difference between FS. Lipid deposition (LD) was influenced by both FS (P =0.048) and TI over time (TI×Time, P< 0.001), with IPF pigs presenting a 10% lower LD than GPF, whereas TI reduced LD by 22% across FS. Differences in LD could be attributed to differences in digestible and net energy between diets. For body composition, TI reduced final body protein by 2% (TI×Time, P=0.003) while also decreasing final body lipids content by 19% (TI×Time, P< 0.001). Body lipids content in IPF was 8% lower than GPF over time (FS×Time, P< 0.001). TI-fed pigs exhibited lower BW due to a reduction in BL mass and a modest reduction in body protein content, making timothy a potential sustainable feed option. IPF-fed pigs were leaner and had better feed efficiency while maintaining protein deposition and ADG than GPF.
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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 | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| 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 ».