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Record W4412990980 · doi:10.1139/cjas-2024-0066

Effects of maturity stage at harvesting of intercropping whole plant faba bean (<i>Vicia faba</i>) with whole plant oat (<i>Avena sativa</i>) silage on the nutritional values for dairy cows

2025· article· en· W4412990980 on OpenAlexafffundvenue
Carlene Nagy, Víctor H. Guevara‐Oquendo, María E. Rodríguez Espinosa, David A. Christensen, H.A. Lardner, Peiqiang Yu

Bibliographic record

VenueCanadian Journal of Animal Science · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgronomic Practices and Intercropping Systems
Canadian institutionsUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of CanadaSaskatchewan Pulse Growers
KeywordsAvenaVicia fabaVicia sativaSilageIntercroppingAgronomyBiology

Abstract

fetched live from OpenAlex

Studies have shown positive results from faba bean forage and legume–cereal intercropping in cow performance. This study aimed to evaluate the effects of maturity stages (MS) on intercropped faba bean ( Vicia faba, CDC Snowbird)–oats ( Avena sativa, CDC Haymaker) silage. Oats and faba beans were seeded together in Outlook, SK, CA. The faba–oat crop was manually harvested from three plots on days 62 (MS1), 72 (MS2), and 82 (MS3). Wilted samples were chopped (1 in. length) and packed into mini silos ( n = 9). The dry matter (DM) content after wilting was 261, 355, and 421 g/kg for MS1, MS2, and MS3, respectively ( P &lt; 0.01). The crude protein (CP) and carbohydrates (CHO) contents (g/kg DM) in the silage were higher for MS2 and MS3 than for MS1 ( P &lt; 0.05). The net energy for lactation (NE Lp3x ) for MS2 and MS3 was 1.17 and 1.23 Mcal/kg, respectively ( P &lt; 0.01). The silage pH was 6.96 for MS1 and averaged 4.66 for MS2 and MS3 ( P &lt; 0.01). The rumen degradable neutral detergent fibre for MS2 and MS3 averaged 157 g/kg DM ( P = 0.02). Harvesting faba bean–oat forage between 72 and 82 days seems promising to produce good quality silage for lactating dairy cows.

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)0.001
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.587
Threshold uncertainty score0.663

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.021
GPT teacher head0.227
Teacher spread0.205 · 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 designBench or experimental
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 routes3
Has abstractyes

Explore more

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