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Record W4295993181 · doi:10.3168/jds.2021-21468

Effects of intake-based weaning and forage type on feeding behavior and growth of dairy calves fed by automated feeders

2022· article· en· W4295993181 on OpenAlexafffund
Allison Welk, Heather W. Neave, H.B. Spitzer, M.A.G. von Keyserlingk, Daniel M. Weary

Bibliographic record

VenueJournal of Dairy Science · 2022
Typearticle
Languageen
FieldVeterinary
TopicAnimal Behavior and Welfare Studies
Canadian institutionsUniversity of British Columbia
FundersDairy Farmers of ManitobaNatural Sciences and Engineering Research Council of CanadaUniversity of British ColumbiaDairy Farmers of Canada
KeywordsWeaningDry matterHayForageAnimal scienceStarterBiologySilageFood scienceAgronomy

Abstract

fetched live from OpenAlex

The objective of this study was to assess the effects of intake-based weaning methods and forage type on feeding behavior and growth of dairy calves. Holstein dairy calves (n = 108), housed in 12 groups of 9, were randomly assigned to 1 of 3 weaning treatments: milk reduction based on age (wean-by-age), individual dry matter intake (DMI; wean-by-intake), or a combination of individual DMI and age (wean-by-combination). Groups of calves were alternately assigned to 1 of 2 forage treatments: grass hay or a silage-based total mix ration (TMR; n = 6 groups per treatment). Until 30 d of age, all calves were offered 12 L/d of whole milk. Starting on d 31, milk was gradually reduced by 25% of the individual's average milk intake. For wean-by-age calves (n = 31), the milk allowance remained stable until d 62 when milk was again reduced gradually until weaning at d 70. For wean-by-intake calves (n = 35), milk allowance was reduced by a further 25% once calves consumed on average 200, 600, and (finally) 1,150 g of dry matter (DM) per day of calf starter and forage. For wean-by-combination calves (n = 35), milk intake remained stable until calves consumed on average 200 g of DM/d, at which point milk was reduced linearly until weaning at d 70. If calves failed to reach DMI targets by d 62 (n = 10), milk was then reduced gradually until weaning at d 70. Of the 35 wean-by-intake calves, 27 met all 3 DMI targets (successful-intake), and 33 of the 35 calves in the wean-by-combination treatment met the 200 g of DM/d target (successful-combination). Successful-intake and successful-combination calves had greater final body weight (BW) at 12 wk of age than wean-by-age calves (123.7 vs. 122.3 vs. 117.7 ± 3.1 kg, respectively). During weaning, successful-intake calves ate more starter and consumed less milk than successful-combination and wean-by-age calves (starter: 1.19 vs. 0.89 vs. 0.49 ± 0.07 kg of DM/d, respectively; milk: 2.7 vs. 4.2 vs. 5.9 ± 0.17 L/d, respectively). After weaning, successful-combination and successful-intake calves consumed similar amounts of starter; however, wean-by-age calves continued to consume less starter (2.85 vs. 2.78 vs. 2.44 ± 0.10 kg of DM/d, respectively). During weaning, hay and TMR calves ate similar amounts of forage, but hay calves consumed more starter (0.96 vs. 0.75 ± 0.07 kg of DM/d, respectively). After weaning, hay calves continued to consume more starter (2.88 vs. 2.50 ± 0.10 kg of DM/d, respectively), whereas TMR calves consumed more forage (0.33 vs. 0.15 ± 0.02 kg of DM/d, respectively). Hay calves had greater final BW at 84 d compared with TMR calves (124.0 vs. 119.0 ± 1.6 kg, respectively). These results show that the inclusion of a DMI target can improve starter intake and BW for calves that successfully wean, and that forage type can influence the transition onto solid feed. We also found that approximately 10% of calves failed to consume even 200 g of DM/d by 9 wk of age; more research is needed to better understand why some calves struggle to transition onto solid feed.

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)0.001
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 score0.002
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0010.000

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 head0.027
GPT teacher head0.309
Teacher spread0.282 · 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

Citations16
Published2022
Admission routes2
Has abstractyes

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