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Enregistrement W2799791651 · doi:10.3168/jds.2017-13839

Silage review: Recent advances and future uses of silage additives

2018· review· en· W2799791651 sur OpenAlex

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Notice bibliographique

RevueJournal of Dairy Science · 2018
Typereview
Langueen
DomaineAgricultural and Biological Sciences
ThématiqueRuminant Nutrition and Digestive Physiology
Établissements canadiensAgriculture and Agri-Food Canada
Organismes subventionnairesnon disponible
Mots-clésSilageMicrobial inoculantLactobacillus buchneriFermentationLactic acidFood scienceLactobacillusBiologyButyric acidChemistryBiotechnologyBacteriaLactobacillus plantarum

Résumé

récupéré en direct d'OpenAlex

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.

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.

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Autre devis · Signal consensuel: aucune
GenreSignal candidat: Synthèse · Signal consensuel: Synthèse
Score de désaccord entre enseignants0,991
Score d'incertitude au seuil0,400

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,001
Communication savante0,0000,001
Science ouverte0,0010,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,042
Tête enseignante GPT0,318
Écart entre enseignants0,276 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle