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Record W4293738905 · doi:10.3168/jds.2022-21918

Fibrous coproducts of corn and citrus as forage and concentrate sources for dairy cows

2022· article· en· W4293738905 on OpenAlexafffund
Wesley de Rezende Silva, Flaviane R. Carvalho, Rayana B. Silva, R.A.N. Pereira, Carla Luiza da Silva Ávila, T.J. DeVries, Marcos Neves Pereira

Bibliographic record

VenueJournal of Dairy Science · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsUniversity of Guelph
FundersFundação de Amparo à Pesquisa do Estado de Minas GeraisConselho Nacional de Desenvolvimento Científico e TecnológicoUniversidade Federal de LavrasCoordenação de Aperfeiçoamento de Pessoal de Nível SuperiorUniversity of Guelph
KeywordsDry matterSilageNeutral Detergent FiberCoproductForageLatin squareDistillers grainsChemistryDairy cattleAnimal scienceTotal mixed rationLactationFood scienceAgronomyBiologyRumenMathematicsFermentationIce calving

Abstract

fetched live from OpenAlex

This study evaluated the effect on dairy cows of the partial replacement of whole plant corn silage (WPCS) with corn ear fibrous coproduct (CEFC) in diets with concentrate coproducts from citrus and corn on dry matter intake (DMI), lactation performance, digestibility, and chewing behavior. Holstein dairy cows (n = 20) in 5, 4 × 4 Latin squares (21-d periods) were fed a combination of strategies for feeding fibrous coproducts in a 2 × 2 factorial arrangement of the following treatments: (1) forage feeds: the partial replacement of WPCS (CS) with CEFC (CO), and (2) concentrate feeds: the partial replacement of wet corn gluten feed (GF) with a blend of pelleted citrus and corn distillers dried grains (CD) to have isonitrogenous diets. The concentrations of physically effective neutral detergent fiber (NDF; pe NDF >8 ) were (% of dry matter): 21.8% for CS, 19.2% for CO, 20.7% for GF, and 20.2% for CD. Cows fed diet CS-CD had the highest yield of energy-corrected milk (30.0 kg/d) relative to the other diets (28.4 kg/d). Milk fat concentration was reduced on CO relative to CS. Cows fed the CO diets had higher DMI (21.2 vs. 20.2 kg/d) and digestible organic matter intake and tended to have a lower ratio of energy-corrected milk to DMI than cows fed CS. Diets CO reduced the daily intake of pe NDF >8 and the intake as percent of body weight of pe NDF >8 , forage NDF, and total NDF relative to CS. Cows fed CO had greater meal frequency and lower daily meal time, meal duration, meal size, and duration of the largest meal than cows fed CS. The CO diet reduced rumination and total chewing in minutes per day and minutes per kilogram of DMI. When expressed per unit of pe NDF >8 intake, rumination and total chewing were not affected by forage source. The total-tract starch digestibility coefficient was lower for cows fed CO than CS, but the intake of digestible starch was higher on CO than CS. Cows fed GF had reduced milk yield (29.6 vs. 30.8 kg/d), tended to have reduced DMI (20.4 vs. 21.0 kg/d), and had reduced digestible organic matter intake than cows fed CD. Feed efficiency was not affected by source of concentrate. The type of concentrate did not affect the intake of forage NDF and pe NDF >8 , but cows fed GF had higher intake of total NDF as percent of body weight than cows fed CD. The GF increased meal frequency and reduced meal size and largest meal duration and size. Cows fed GF had higher rumination and total chewing than cows fed CD (min/d, min/kg of DMI, and min/kg pe NDF >8 ). Starch digestibility was higher and the intake of digestible starch tended to be higher on cows fed GF than CD. Plasma urea-N was higher, milk urea-N tended to be higher, and N utilization efficiency tended to be lower on cows fed GF than CD. Ruminal microbial yield was not affected by any treatment. All strategies evaluated were nutritionally viable and CEFC was a feasible partial replacement for WPCS.

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: Bench or experimental · Consensus signal: Bench or experimental
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)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.022
GPT teacher head0.247
Teacher spread0.224 · 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 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

Citations10
Published2022
Admission routes2
Has abstractyes

Explore more

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