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Record W7112362313

Effects of Annual and Perennial Forage Systems on Forage Biomass and Quality, and Soil Microorganisms

2025· article· en· W7112362313 on OpenAlexfundno aff

Bibliographic record

VenueUniversity Library (University of Saskatchewan) · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgroforestry and silvopastoral systems
Canadian institutionsnot available
FundersAlberta Beef ProducersMinistry of Agriculture - Saskatchewan
KeywordsForagePerennial plantBromus inermisSecaleBrassicaTrifolium alexandrinumBromusHordeum vulgareBiomass (ecology)
DOInot available

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.442
Threshold uncertainty score0.628

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.007
GPT teacher head0.167
Teacher spread0.160 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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