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Record W2744205385 · doi:10.2527/asasann.2017.247

247 Effect of 3- vs. 9-d whole-plant corn allocation with or without fiber supplementation on cow performance, grazing preference, and ruminal fermentation

2017· article· en· W2744205385 on OpenAlexaffabout
Brendan M. Anderson, G.B. Penner, Kathy Larson, J. J. McKinnon, H.A. Lardner

Bibliographic record

VenueJournal of Animal Science · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsGrazingAnimal scienceHuskBiologyCompletely randomized designFermentationForageHayNeutral Detergent FiberAgronomyFood scienceBotany

Abstract

fetched live from OpenAlex

Grazing whole-plant corn is becoming increasingly common on western Canadian beef farms as a winter feeding method. This 2-yr study evaluated the impact of provision of 3- or 9-d (3D or 9D, respectively) whole-plant corn allocation (Zea mays, P7332R; yr 1, TDN = 69.5%, CP = 8.6% [DM basis]) with or without fiber (FIB or NFIB, respectively) supplementation on cow performance, grazing preference, and ruminal fermentation. Supplemental fiber (hay, TDN = 60.2%, CP = 12.9% [DM basis]) was provided at 15% of DMI in 3DFIB and 9DFIB systems. Ninety-six Angus cows (BW = 664.4 kg ± 20.05), including 16 ruminally cannulated cows, were allocated to 1 of 4 replicated (n = 2/yr) systems for 84 and 88 d in yr 1 and 2, respectively. Cow BCS and BW were recorded at the start and end of the study, and grazing preference and ruminal fermentation data were collected at the start, middle, and end of the grazing allocation. Grazing preference was determined based on plant part (stem, husk, leaf, and cob) disappearance. Data were analyzed as a completely randomized design with a 2 × 2 factorial arrangement using the mixed model of SAS. Year was included as a random effect and time within an allocation as a repeated measure. Cow BCS and ADG were not affected (P > 0.05). As grazing progressed within an allocation, the proportion of cob, husk, and leaf decreased (P < 0.01), while the stem increased (P < 0.01). For 3D cows, ruminal NH3-N concentration did not differ within an allocation, whereas NH3-N increased for 9D cows (allocation × timing, P < 0.05). Total short chain fatty acid concentration was greater (95.2 vs. 85.6 mM, P < 0.05) and acetate was greater (62.2 vs. 55.1 mM, P < 0.05) for FIB than NFIB. Butyrate concentration decreased from 13.8 to 6.5 mM from the start until the end of the 9D grazing allocation, but concentrations did not differ for 3D (allocation × timing, P < 0.05). Minimum pH increased during the grazing allocation, but the magnitude of the increase was greater for 9D than 3D (allocation × timing, P < 0.05). The duration that ruminal pH was <5.8 was not affected by allocation or provision of FIB but decreased (P < 0.01) from 143 min/d at the start of grazing allocation to 0 min/d at the end. The provision of fiber alters ruminal fermentation, and extending the duration of the grazing allocation increases the selection of plant structures and differences in ruminal pH within a grazing allocation.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.036
GPT teacher head0.283
Teacher spread0.247 · 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
Published2017
Admission routes2
Has abstractyes

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