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Record W4214689416 · doi:10.3168/jds.2021-21286

Performance and visceral tissue growth and development of Holstein calves fed differing milk replacer allowances and starch concentrations in pelleted starter

2022· article· en· W4214689416 on OpenAlexafffund
T.T. Yohe, T.S. Dennis, L.N. Buss, Emily Croft, J.D. Quigley, T.M. Hill, F.X. Suárez-Mena, K.M. Aragona, A.H. Laarman, J.H.C. Costa, M.A. Steele

Bibliographic record

VenueJournal of Dairy Science · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsUniversity of AlbertaUniversity of Guelph
FundersNational Cancer InstituteDairy Farmers of ManitobaNatural Sciences and Engineering Research Council of CanadaMitacsOhio State University
KeywordsStarterWeaningDry matterAnimal scienceStarchStrawRumenBiologyNeutral Detergent FiberFood scienceChemistryFermentationAgronomy

Abstract

fetched live from OpenAlex

The objectives of this study were to investigate how milk replacer (MR) allowance and differing concentrations of starch and neutral detergent fiber in starter alters visceral tissue and overall growth of the calf. Calves were randomly assigned to 1 of 4 dietary treatments (n = 12 per treatment) arranged in a 2 × 2 factorial based on daily MR allowance (MRA) and amount of starch in pelleted starter (SPS) as follows: 0.691 kg of MR/d [dry matter (DM) basis] with starter containing low or high starch (12.0% and 35.6% starch, respectively) and 1.382 kg of MR/day (DM) with starter containing low or high starch. All calves were housed in individual pens with straw bedding until wk 5 when bedding was covered to minimize intake. Calves were fed MR twice daily (0700 and 1700 h) containing 24.5% crude protein (DM) and 19.8% fat (DM), and had access to pelleted starter (increased by 50 g/d if there were no refusals before weaning, and then 200 g/d during and after weaning) and water starting on d 1. Calves arrived between 1 and 3 d of age and were enrolled into an 8-wk study, with calves undergoing step-down weaning during wk 7. Intakes were measured daily, and body weight (BW) and blood samples were recorded and collected weekly. Calves were dissected in wk 8 for visceral tissue measurements. Overall, there was increased MR DM intake for the high- (0.90 ± 0.01 kg/d; ± SE) compared with the low-MRA (0.54 ± 0.01 kg/d) calves, whereas starter DM intake increased in low- (0.47 ± 0.05 kg/d) compared with high-MRA (0.20 ± 0.05 kg/d) calves, which was driven by increases in wk 6, 7, and 8. High-MRA calves had increased BW during wk 2, 3, 4, 5, 6, and 7. The difference in BW disappeared by wk 8, with overall average daily gain having a tendency to be increased in high (0.57 ± 0.04 kg/d) compared with low-MRA (0.50 ± 0.04 kg/d) calves, whereas average daily gain was increased in high-MRA calves during wk 2 and 3 and increased in low-MRA calves during wk 7 and 8. There were several differences throughout visceral tissue measurements, but most notably, an increase in rumen mass (i.e., full, empty, and digesta weights) in low- compared with high-MRA calves, as well as in low- compared with high-SPS calves was observed. The length, width, and 2-dimensional area of rumen papillae were also increased in low- (area: 0.88 ± 0.03 mm 2 ) compared with high-MRA (0.46 ± 0.03 mm 2 ) calves. The majority of differences were attributed to increased MR allowance, which contributed to reduced pelleted starter intake by more than 50% and reduced rumen development, whereas differences in starch intake from the completely pelleted starter had minimal effects on overall growth and tissue measurements.

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)0.001
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 score0.008
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
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 head0.021
GPT teacher head0.243
Teacher spread0.221 · 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

Citations10
Published2022
Admission routes2
Has abstractyes

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