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Record W4414831313 · doi:10.1093/jas/skaf300.141

78 The impact of intercropping corn with annual forages on forage chemical composition and bred heifer performance during late fall/early winter grazing in Western Canada.

2025· article· en· W4414831313 on OpenAlexaffabout
Connor S. McIntyre, E. J. McGeough, Kim Ominski, Yvonne Lawley

Bibliographic record

VenueJournal of Animal Science · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsForageIntercroppingGrazingHectareMonoculturePastureBiomass (ecology)Livestock

Abstract

fetched live from OpenAlex

Abstract Extended grazing is frequently used by Canadian beef producers to reduce winter feed costs. Corn is a high-energy forage with increased biomass yield per hectare compared to other annual crops. However, corn has low CP concentration which may not meet the nutritional requirements of growing cattle or those in mid-late gestation when grazed alone. The objectives of this study were to compare monoculture corn (COR) on 0.76 m row spacing with corn intercropped with Italian rye and hairy vetch (INT) on 1.52m row spacing by examining forage chemical composition, individual DMI, ADG, blood SUN and enteric methane (CH4) of bred heifers grazing in the late fall/early winter. For both treatments, corn was seeded at the Glenlea Research Station in Manitoba on June 1st while the intercrop was seeded June 28th at the V4 stage of corn growth. In a complete randomized design, each treatment had 2 replicate paddocks with 12, 18-mo old, bred heifers per paddock (n=48) with an average body weight of 419.0 kg. Heifers were turned out to pasture on October 11th for a 12-d adaptation to corn only, followed by an 8-d adaptation to the experimental treatments and then a 41-d experimental period. Corn was sampled on October 16th, and intercrop forage was sampled weekly over the experimental period to determine forage chemical composition. Animal BW (2 d) and blood SUN were determined on d 1, 15 and 41 of the experimental period. Individual DMI was determined using a titanium dioxide marker and fecal recovery method from d 7-13. Data was analyzed with R (version 4.4.1) using a linear mixed effect model (lmer4) with forage treatment as the fixed effect and paddock as a random effect. Corn CP concentration was lower for COR paddocks compared to INT paddocks (4.83% vs 6.75%; P< 0.001), but there was no difference in TDN between treatments (P = 0.09). The mean intercrop CP, nitrate and TDN concentrations were 22.13%, 0.60%, and 68.83% respectively. Daily DMI was 13.41 and 16.50 kg/animal for COR and INT treatments respectively (P = 0.2649). Blood SUN for COR heifers was lower than INT at d 15 and d 41 (P = 0.03, P < 0.001). Heifers grazing COR had 44.5% lower ADG than the INT treatment (0.66 vs 1.19 kg/day; P = 0.04). Results from this study suggest that compared with monoculture corn, corn intercropped with annual forages offered higher nutritive value and improved animal performance during the late fall/early winter grazing season, thus offering a novel alternative grazing option for bred heifers.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.180
Threshold uncertainty score0.361

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.009
GPT teacher head0.238
Teacher spread0.228 · 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 source (direct Gemma or distilled Codex), 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 routes2
Has abstractyes

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