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Record W4406410784 · doi:10.3168/jds.2024-25787

Influence of dairy cow personality traits on response to extended milking intervals and removal of supplemental concentrate in a free-traffic automated milking system

2025· article· en· W4406410784 on OpenAlexafffund
A.J. Schwanke, J.E. Brasier, G.B. Penner, Renée Bergeron, T.J. DeVries

Bibliographic record

VenueJournal of Dairy Science · 2025
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 AllianceOntario Ministry of Agriculture, Food and Rural AffairsCanada Foundation for InnovationOntario Research FoundationCanada First Research Excellence FundUniversity of Guelph
KeywordsMilkingAutomatic milkingAnimal scienceBig Five personality traitsPersonalityBiologyPsychologySocial psychologyLactation

Abstract

fetched live from OpenAlex

Provision of supplemental concentrate in an automated milking system (AMS) is commonly used to encourage voluntary attendance; however, the motivation to voluntarily milk is highly variable between cows. The objectives of this study were to determine whether dairy cow personality is associated with (1) their short-term response to changes in factors believed to motivate voluntary AMS visits, such as udder pressure and provision of supplemental feed (modulated by longer milking intervals or removal of AMS concentrate, respectively); and (2) their milking activity, production, and feeding behavior after returning to pretreatment AMS milking interval and concentrate feed settings (i.e., behavioral flexibility). A total of 31 early-lactation Holstein cows (95 ± 13 DIM), who had been acclimated to, and were using, an AMS for 2 wk, were enrolled in this study. Baseline AMS settings restricted milking intervals to a minimum of 6 h and an AMS concentrate allocation of up to 5.4 kg/d DM. Previously, at 80 DIM, 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 personality assessment revealed 3 factors (interpreted as sociable-explorative, active, and bold) that together explained 81% of the variance. Cow scores for each factor ranged from -2.29 to 2.34. Cows were exposed to each of 2 treatments in a crossover design, with a 6-d baseline period, followed by 2 experimental treatment periods of 6 d each, and finally a 6-d period during which all cows returned to baseline AMS settings (total duration of 24 d/cow). Treatments consisted of (1) increased minimum milking interval of 9 h and an AMS concentrate allowance of up to 5.4 kg DM/d (INT); or (2) supplemental AMS concentrate being removed and a minimum milking interval of 6 h (CONC). During the experimental periods, cows had more voluntary AMS visits on INT compared with CONC (7.3 vs. 5.2 visits/d), and cows who were more active had fewer voluntary AMS visits compared with less active cows (visits/d = -2.2 × activeness score + 6.0). Among cows in the INT-CONC treatment order group, more active cows made fewer voluntary AMS visits (visits/d = -4.1 × activeness score + 5.8) during the baseline 2 period. More sociable-explorative cows had greater milk yield (kg/d = 1.8 × sociable-explorative score + 36) in baseline 2 compared with less sociable-explorative cows. These results suggest that cow personality may not affect the response of cows to factors that affect voluntary AMS visits, although individual personality does influence overall behavior in AMS.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0000.000

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 head0.032
GPT teacher head0.350
Teacher spread0.319 · 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

Citations4
Published2025
Admission routes2
Has abstractyes

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