Flexible feeding: Dairy cow personality affects changes in feeding behavior and milk production under feed competition conditions
Bibliographic record
Abstract
The objective of this study was to determine the effect of individual cow personality traits on feeding behavior and production under low levels of feeding competition, and to determine whether personality traits influence how feeding behavior changes in response to greater feeding competition. Forty-two Holstein cows were assigned to 1 automated feed bin per cow (low competition condition) from 15 to 28 d in milk (DIM; period 1, P1), and 2 feed bins per 3 cows (higher competition condition) from 63 to 76 DIM (period 2, P2). A total mixed ration (TMR) was fed into the automated feed bins which recorded each feed bin visit time, duration, and intake. Cow personality traits were assessed at 21 DIM during P1 and at 70 DIM during P2 using a combined arena test, measuring behavioral responses to a novel environment, novel object, and novel human. Principal components analysis of behaviors observed during the P1 combined arena test revealed 1 factor (interpreted as active-explorative) from the novel environment test explaining 51% of the variance, and 3 factors (interpreted as fearfulness, active-explorative, and sociability toward conspecifics) from each of the novel object (76% cumulative variance) and human (75% cumulative variance) tests. The principal components analysis of behaviors observed during the P2 combined arena test revealed 2 factors jointly from the environment, object, and human tests (interpreted as fearfulness and active-explorative) that together explained 68% of the variance. Fearfulness and active-explorative trait scores were correlated across P1 and P2, indicating stability of personality over a challenging period and advancing DIM. In P2 when competition for feed was increased at greater stage of lactation, the more active-explorative cows appeared to make few alterations to their feeding behavior, yet still maintained their milk yield, compared with lower competition in P1. In contrast, cows who were more fearful increased their feed bin visits from P1 to P2, and less fearful cows increased their eating rate, without increased milk production, despite advanced lactation. Overall, the results indicate that cows of different personalities adopt different feeding strategies in response to a change in their environment, and may benefit from tailored management during challenging periods.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".