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Enregistrement W2916473741

Novel forage legumes for sustainable summer pasture mixtures in Saskatchewan

2018· dissertation· en· W2916473741 sur OpenAlexaboutno aff
Samuel Peprah

Notice bibliographique

Revuenon disponible
Typedissertation
Langueen
DomaineAgricultural and Biological Sciences
ThématiquePasture and Agricultural Systems
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésPastureForageAgroforestryAgronomyGeographyForestryEnvironmental scienceBiology
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Two experiments were conducted (2016 and 2017) to determine the potential of perennial binary legume-grass mixtures. Experiment 1 evaluated effect of July and September harvest dates on stockpiled forage dry matter yield, quality and botanical composition of legume and grass species at AAFC SCRDC-Swift Current (Brown soil site) and AAFC Saskatoon (Dark Brown soil site), Saskatchewan. Experiment 2 evaluated forage dry matter yield (DMY), quality, grazing animal preference and performance, and cost-benefits analysis of binary legume-grass mixtures at AAFC SCRDC-Swift Current (Brown soil site) and WBDC-Lanigan (Thin Black soil zone) Saskatchewan. Experiment 1 forage varieties included AC Yellowhead alfalfa (ALF), AC Mountainview sainfoin (MSF), Nova sainfoin (NSF), Shoshone sainfoin (SSF), Delaney sainfoin (DSF), AC Veldt cicer milkvetch (CMV), Great Plains Ecovar Canadian milkvetch (GCM), AC Lamour purple prairie clover (PPC) and Antelope white prairie clover (WPC) in binary mixtures with either Tom Russian wildrye (RWR), AC Success hybrid bromegrass (HBG) or Admiral meadow bromegrass (MBG) in a split-plot arrangement of a randomized complete block design (RCBD). Forage DMY of tame binary mixtures were greater (P = 0.01) at AAFC Saskatoon than AAFC SCRDC site. Forage DMY differed (P = 0.01) among tame binary mixtures ranging from 1,828 (NSF-RWR) to 4,826 kg ha-1 (ALF-HBG) and 4,511 (NSF-RWR) to 10,113 kg ha-1 (CMV-HBG) mixtures at AAFC SCRDC and AAFC Saskatoon, respectively. Forage DMY also differed (P = 0.01) among native binary mixtures ranging from 884 (WPC-RWR) to 3,582 kg ha-1 (PPC-HBG) mixtures at AAFC SCRDC site. Year of harvesting forages at both sites were greater (P < 0.05) in 2016 than 2017. Dry matter yield of mixtures harvested in September were 15 to 20% lower (P = 0.01) than July harvest yields in yr 2 at both study sites. Nutritive value of binary mixtures was 26 to 46% greater (P < 0.05) at AAFC Saskatoon compared to AAFC SCRDC-Swift Current site because of precipitation. Among the binary mixtures, CMV-RWR and GCM-RWR mixtures (native binary mixture) ranked the highest in nutritive value at both sites. RWR was more compatible with forage legumes (> 50 % legumes) compared to MBG and HBG in mixtures with legumes. Most native binary mixtures may not be recommended as fall stockpiled forage due to low CP level not meeting CP requirement of grazing animals and yielding less than 2,000 kilogram per hectare. Based on the 2 yr study, it is not recommended to seed either HBG or MBG in a binary mixtures with a legume in a mixed-row seeding pattern. Experiment 2 evaluated alfalfa (ALF) (Medicago falcata L.; cv. AC Yellowhead) and sainfoin (SF) (Onobrychis viciifolia Scop; cv. AC Mountainview) in binary mixtures with either Russian wildrye (RWR) (Psathyrostachys junceus [Fisch.]; cv. Tom) or hybrid bromegrass (HBG) (B. riparius Rehm × B. inermis Leyss; cv. AC Success) in a randomized complete block design at WBDC-Lanigan and AAFC SCRDC-Swift Current sites. Yearling steers (yr 1, n = 40, BW = 404 kg ± 18 kg; yr 2, n = 48, BW = 400 kg ± 16 kg) at AAFC SCRDC, and heifers (yr 1, n = 64, 364 kg ± 51) and steers (yr 2, n = 48, BW = 338 kg ± 23 kg) at WBDC were randomly allocated to 1 of 4 replicated (n=4) pasture types, (i) ALF-RWR; (ii) ALF-HBG; (iii) SF-RWR; and (iv) SF-HBG mixtures. Forage DMY were greater (P = 0.01) for HBG + legume mixtures at WBDC than at AAFC SCRDC and similar (P > 0.05) for RWR+ legumes mixtures at both sites. Forage DMY differed (P = 0.01) among binary mixtures ranging from 3,638 (SF-RWR) to 5,901 kg ha-1 (ALF-HBG) at WBDC site. In contrast, DMY was similar (P = 0.84) among binary mixtures ranging from 3,931 (ALF-HBG) to 4,140 kg ha-1 (ALF-RWR) at AAFC SCRDC site. Hand plucked samples had greater (P < 0.05) nutritive value in yr 2 at WBDC compared to clipped forage samples. However, at AAFC SCRDC, nutritive values from hand plucked samples were similar (P > 0.05) to clipped samples. Estimated forage dry matter intake (kg d-1) and forage utilization (%) were similar (P > 0.05) among binary mixtures at both sites. Average daily gain (ADG) was similar (P = 0.32) among binary mixtures at AAFC SCRDC. However at WBDC, ADG differed (P = 0.02) among binary mixtures in yr 2 ranging from 0.64 to 1.1 kg d-1 for ALF-HBG and SF-RWR mixtures, respectively. Animal grazing days (AGD) (P = 0.26) and total beef production (TBP) (P = 0.59) at WBDC were similar in both yrs, for all pasture mixtures ranging from 78 to 116 AU ha-1 AGD and 58 to 78 kg ha-1 TBP, respectively. However, at AAFC SCRDC in yr 2, AGD and TBP differed (P = 0.01) with steers grazing ALF-HBG mixtures having greater AGD (121 vs 74 AU ha-1) and TBP (120 vs 67 kg ha-1) compared to steers grazing the SF-RWR (74 AU ha-1) pasture. Despite the late summer and fall grazing, stocker performance was improved at both sites. Costs to seed perennial mixtures differed (P= 0.01) in both yrs and at both sites ranging from $58.78 (ALF-RWR) to 82.06 (SF-HBG) per ha at AAFC SCRDC and $29.00 to 49.09 and 75.95 to 96.03 per ha in yr 1 and yr 2 at WBDC, respectively. Value of gain ($ ha-1) (P = 0.66, yr 1; P = 0.27, yr 2) and net returns (P = 0.42, yr 1; P = 0.47, yr 2) were similar among mixtures at WBDC site. However, value of gain and net returns differed (P = 0.01 vs. P = 0.02) among mixtures in yr 2 at AAFC SCRDC site. These results suggest that beef producers can adopt placing a value on forages for higher profit compared to compensation rates for custom grazing and animal grazing days. Despite differences in agro-climatic condition, all binary mixtures were profitable for late summer and fall grazing in southwest and central Saskatchewan.

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 machine sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,579
Score d'incertitude au seuil0,837

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0010,000
Communication savante0,0010,000
Science ouverte0,0010,001
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0020,000

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 Opus0,014
Tête enseignante GPT0,240
Écart entre enseignants0,227 · 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

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations2
Publié2018
Routes d'admission1
Résumé présentoui

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