Effects of Annual and Perennial Forage Systems on Forage Biomass and Quality, and Soil Microorganisms
Notice bibliographique
Résumé
Annual and perennial forage systems which include leguminous species can serve as valuable feed sources for beef producers, due to their diverse growth forms, yield, and nutritional traits. However, limited research has compared the effects of these forage systems on the soil and its associated microbial communities. This study hypothesized that the different vegetative traits of annual and perennial forage systems would lead to variations in biomass yield and nutritive quality, resulting in distinct microbial communities under grazed and ungrazed conditions. The forage systems included (i) CDC Austenson barley (Hordeum vulgare L.) + 4010 pea (Pisum sativum L.) + Winfred forage brassica (Brassica oleracea L.× Brassica rapa L.) + Gorilla forage brassica (Brassica napus L.) (BRPEBRAS), (ii) AC Hazlet fall rye (Secale cereale L.) + Frosty berseem clover (Trifolium alexandrinum L.) (FRCLOV), (iii) AC Success hybrid bromegrass (Bromus riparius Rehm. × Bromus inermis Leyss.) + PS3006 alfalfa (Medicago sativa L.) (HBGALF), and (iv) AC Armada meadow bromegrass (Bromus riparius Rehm.) + AAC Mountainview sainfoin (Onobrychis viciifolia Scop.) (MBGSF). The 2-yr (2022 and 2023) study employed a random complete block design, consisting of n = 3 replicated paddocks/treatment, with the paddock average serving as the experimental unit. Soils were sampled prior to grazing, then 10 steers in 2022 and 13 steers in 2023, were turned out to graze. Forage biomass yields were the greatest in BRPEBRAS and HBGALF (P < 0.01), while botanical composition showed the least weed pressure in the perennial forages HBGALF and MBGSF (P < 0.01). Forage nutritive values were consistently greater in annuals where crude protein and energy were higher (both P < 0.01), and fibre fractions were lower (P < 0.01) than in perennials. In ungrazed forage systems, soil extracellular enzyme activity (EEA) of N-acetyl-β-glucosaminidase was greater in perennials in 2023 (P = 0.02). Potential C mineralization was consistently higher in perennials, but no differences were seen in microbial biomass C (MBC). The microbial metabolic quotient (qCO2) increased from 2022 to 2023 and was greatest in 2023 perennial forage systems (P < 0.01). The abundance of fungal microbial phospholipid fatty acid (PLFA) indicators tended to be greater in perennials. Soil microbial community composition (mol% PLFA) of annuals tended to have a greater proportion of bacteria while perennials had greater fungi. Comparing grazed and ungrazed perennial forage system soils in 2023 showed that grazing did not affect EEA, MBC or microbial metabolic quotient. Grazing tended to decrease short-term potential C mineralization, where decreases were seen at 7 d in MBGSF (P = 0.08). Few grazing differences were seen in PLFA abundance and community composition due to grazing. Within the constraints of the current study, the forage systems evaluated demonstrated varied potential to support grazing through yield and quality measures, and perennial forage systems tended to support greater fungal communities and have higher potential C metabolism compared to annual forage systems.
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 distillée sur la base complète
Imitation des enseignantsNi 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.
Scores Codex et Gemma par catégorie
| 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 | 0,001 |
| 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 tête enseignante, 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 ».