MétaCan
Menu
Back to cohort
Record W4229082730 · doi:10.3168/jds.2021-21657

Effects of concentrate allowance and individual dairy cow personality traits on behavior and production of dairy cows milked in a free-traffic automated milking system

2022· article· en· W4229082730 on OpenAlexafffund
A.J. Schwanke, K.M. Dancy, Heather W. Neave, G.B. Penner, Renée Bergeron, T.J. DeVries

Bibliographic record

VenueJournal of Dairy Science · 2022
Typearticle
Languageen
FieldVeterinary
TopicAnimal Behavior and Welfare Studies
Canadian institutionsUniversity of SaskatchewanUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of CanadaOntario Agri-Food Innovation AllianceCanada First Research Excellence FundUniversity of Guelph
KeywordsMilkingAutomatic milkingAnimal scienceDry matterAllowance (engineering)Dairy cattleLactationBiologyIce calvingOperations managementEngineeringPregnancy

Abstract

fetched live from OpenAlex

The primary objective of this study was to determine whether the level of concentrate allowance in an automated milking system (AMS) affects the feed intake, eating behavior, milking activity, and performance of lactating dairy cows. The secondary objective of this study was to describe how the response to concentrate allocation, specifically in feeding and milking behavior, varies with cow personality traits. Fifteen Holstein cows were used in a crossover design with two 28-d periods, each including 14 d of adaptation and 14 d of data collection. The cows were housed in a freestall pen with free-traffic access to the AMS. Treatments consisted of a basal partial mixed ration (PMR) common to both treatment groups, with a concentrate allowance (on dry matter basis) of (1) 3.0 kg/d in the AMS (L-AMS) or (2) 6.0 kg/d in the AMS (H-AMS). Between the 2 treatment periods, each cow was assessed for personality traits using a combined arena test consisting of exposure to a novel environment, novel object, and novel human. Principal component analysis of behaviors observed during the novel environment and object tests revealed 3 factors (interpreted as active, social, and alert-curious) that together explained 76% of the variance, whereas principal component analysis of the novel human test revealed 2 factors (interpreted as active-vocal and fearful of novel humans) that together explained 77% of the variance. When on the H-AMS treatment, PMR dry matter intake (DMI) was less (24.5 vs. 26.0 kg/d) and AMS concentrate delivery was greater (5.9 vs. 3.1 kg/d), as per design. Consequently, total DMI was greater on the H-AMS treatment (30.4 vs. 29.1 kg/d). When on the H-AMS treatment, cows who were more alert-curious consumed more PMR, whereas cows who were more fearful of the novel human were less likely to receive the maximum amount of AMS concentrate available, limiting their total DMI and increasing the day-to-day variability of that intake. Although this was a preliminary study, these data suggest an association between dairy cow personality traits and how cows respond to increased AMS concentrate allowance.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.774
Threshold uncertainty score0.642

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.037
GPT teacher head0.303
Teacher spread0.266 · 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 teacher head, 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

Citations31
Published2022
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Dairy ScienceSame topicAnimal Behavior and Welfare StudiesFrench-language works237,207