Silage review: Recent advances and future uses of silage additives
Notice bibliographique
Résumé
Additives have been available for enhancing silage preservation for decades. This review covers research studies published since 2000 that have investigated the efficacy of silage additives. The review has been divided into 6 categories of additives: homofermentative lactic acid bacteria (LAB), obligate heterofermentative LAB, combination inoculants containing obligate heterofermentative LAB plus homofermentative LAB, other inoculants, chemicals, and enzymes. The homofermentative LAB rapidly decrease pH and increase lactic acid relative to other fermentation products, although a meta-analysis indicated no reduction in pH in corn, sorghum, and sugarcane silages relative to untreated silages. These additives resulted in higher milk production according to the meta-analysis by mechanisms that are still unclear. Lactobacillus buchneri is the dominant species used in obligate heterofermentative LAB silage additives. It slowly converts lactic acid to acetic acid and 1,2-propanediol during silo storage, improving aerobic stability while having no effect on animal productivity. Current research is focused on finding other species in the Lb. buchneri group capable of producing more rapid improvements in aerobic stability. Combination inoculants aim to provide the aerobic stability benefits of Lb. buchneri with the silage fermentation efficiency and animal productivity benefits of homofermentative LAB. Research indicates that these products are improving aerobic stability, but feeding studies are not yet sufficient to make conclusions about effects on animal performance. Novel non-LAB species have been studied as potential silage inoculants. Streptococcus bovis is a potential starter species within a homofermentative LAB inoculant. Propionibacterium and Bacillus species offer improved aerobic stability in some cases. Some yeast research has focused on inhibiting molds and other detrimental silage microorganisms, whereas other yeast research suggests that it may be possible to apply a direct-fed microbial strain at ensiling, have it survive ensiling, and multiply during feed out. Chemical additives traditionally have fallen in 2 groups. Formic acid causes direct acidification, suppressing clostridia and other undesired bacteria and improving protein preservation during ensiling. On the other hand, sorbic, benzoic, propionic, and acetic acids improve silage aerobic stability at feed out through direct inhibition of yeasts and molds. Current research has focused on various combinations of these chemicals to improve both aerobic stability and animal productivity. Enzyme additives have been added to forage primarily to breakdown plant cell walls at ensiling to improve silage fermentation by providing sugars for the LAB and to enhance the nutritive value of silage by increasing the digestibility of cell walls. Cellulase or hemicellulase mixtures have been more successful at the former than the latter. A new approach focused on Lb. buchneri producing ferulic acid esterase has also had mixed success in improving the efficiency of silage digestion. Another new enzyme approach is the application of proteases to corn silage to improve starch digestibility, but more research is needed to determine the feasibility. Future silage additives are expected to directly inhibit clostridia and other detrimental microorganisms, mitigate high mycotoxin levels on harvested forages during ensiling, enhance aerobic stability, improve cell wall digestibility, increase the efficiency of utilization of silage nitrogen by cattle, and increase the availability of starch to cattle.
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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 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,003 | 0,003 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 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 ».