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Record W4407792326 · doi:10.3168/jds.2024-25522

Effect of ensiled alpha-amylase–enabled corn grain at 2 concentrations in the diet on lactation performance, chewing activity, ruminal fermentation, nutrient digestibility, and nitrogen partition of dairy cows

2025· article· en· W4407792326 on OpenAlexafffund
Wesley de Rezende Silva, Mariane A Tiengo, Rayana B. Silva, R.A.N. Pereira, T.J. DeVries, Marcos Neves Pereira

Bibliographic record

VenueJournal of Dairy Science · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsUniversity of Guelph
FundersFundação de Amparo à Pesquisa do Estado de Minas GeraisUniversidade Federal de LavrasCoordenação de Aperfeiçoamento de Pessoal de Nível SuperiorUniversity of Guelph
KeywordsLactationNutrientAgronomyFermentationAnimal scienceNitrogenDairy cattleChemistryFood scienceBiology

Abstract

fetched live from OpenAlex

This experiment evaluated the effect of α-amylase-enabled corn (AAC) on cows fed ensiled mature kernels at 2 concentrations in the diet. Twenty individually housed Holstein cows, arranged in 4 × 4 Latin squares (with 21-d periods), were exposed to each of 4 treatments in a 2 × 2 factorial combination of corn concentration (C): high corn concentration (High; 28.7% starch, 24.6% corn, 2.5% citrus pulp) versus low corn concentration (Low; 21.5% starch, 14.1% corn, 13.8% citrus pulp) and type (T): AAC (48.8% vitreousness) versus isogenic control (CTL; 51.1% vitreousness). Kernels were ground weekly, hydrated (62.2 ± 1.3% DM on AAC and 63.1 ± 1.4% DM on CTL), and ensiled for 28 ± 3 d. The statistical model had the effects of square, cow (square), period, C, T, and the C × T interaction. No effect of treatment was detected for milk yield (34.1 kg/d) and DMI (22.8 kg/d). High corn reduced the daily yield of fat (1.209 kg/d vs. 1.297 kg/d) and ECM (33.2 kg/d vs. 34.4 kg/d) and increased milk protein concentration (3.12% vs. 3.09%). When fed with Low, AAC increased ECM/DMI relative to CTL (1.54 vs. 1.49). Meal frequency was reduced on High-AAC (9.8 meals/d) relative to Low-AAC (10.3 meals/d). Cows fed High had greater proportion of daily intake in the morning (49.9% vs. 44.4%) and longer duration of the first daily meal (69.7 min vs. 62.0 min) than cows fed Low. There was a tendency for AAC to increase the total-tract NDF digestibility (49.9% vs. 48.0%), but starch digestibility did not differ (98.4%). Ruminal microbial yield did not differ (335 mmol/d of allantoin in urine). High reduced the ruminal acetate to propionate ratio (2.45 vs. 2.95) and pH (6.59 vs. 6.74) relative to Low. Cows fed High-AAC had lower MUN than Low-AAC (17.4 mg/dL vs. 18.8 mg/dL), and plasma urea-N was lower on High-AAC than on High-CTL and Low-AAC (17.2, 19.0, and 18.7 mg/dL, respectively). High starch reduced urine-N excretion (g/d) and partition (% of daily N intake) relative to Low starch and also tended to reduce fecal-N excretion and partition. Overall, Low starch increased milk solids yield, N loss in urine and feces, and the ruminal acetate to propionate ratio. Cows fed AAC and Low had the highest feed efficiency, and cows fed AAC and High had the lowest proportion of N intake in total excreta.

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 score0.002
Threshold uncertainty score0.004

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 head0.017
GPT teacher head0.273
Teacher spread0.256 · 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

Citations1
Published2025
Admission routes2
Has abstractyes

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