Effect of dairy cow personality traits and concentrate allowance on their response to training and adaptation to an automated milking system
Bibliographic record
Abstract
The objectives of this study were to determine: (1) if dairy cow personality traits and concentrate allowance are associated with the behavior and performance of cows during training to use an automated milking system (AMS); and (2) if these factors were associated with the behavior and performance of cows after AMS training. Twenty-nine mid- to late-lactation Holstein cows (218 ± 49 DIM), who were milking on a rotary parlor and had never previously been milked in an AMS, were enrolled in this study. Cows were assigned to 1 of 2 dietary treatments, consisting of a basal partial mixed ration (PMR) common to both treatment groups, with a concentrate allowance (on a DM basis) of (1) 2.0 kg/d in the AMS (L-Tx), or (2) 6.0 kg/d in the AMS (H-Tx). Cows were trained to use the free-traffic AMS, with supervised milkings, over 72 h and were milked in this system for 63 d after training was complete. Variables relating to feeding behavior, milking activity, and production were measured from the start of AMS training until the end of the study. Between 42 and 63 d after AMS introduction, 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 components analysis of behaviors observed during the personality assessment revealed 2 factors (interpreted as boldness and activeness traits) that together explained 85% of the variance; each cow received a score for each trait. Associations between dietary treatment and personality traits with feeding behavior, milking activity, and production were analyzed using mixed-effect linear and logistic regression models. Cows with greater scores for the active trait produced less milk during the 3 d of AMS training compared with cows with lower scores. Within the H-Tx, more active cows had a 3.92 times greater risk of kicking off teat cups during AMS training than less active cows. However, during the 8 wk after training, more active cows had a 1.37 times lesser risk of teat cup kickoffs than those that were less active. Cows on the H-Tx produced 4.4 kg/d more ECM compared with cows on the L-Tx in the 8 wk after training. During the 8 wk after AMS training the cows on the H-Tx consumed an average of 21.4 kg/d of PMR and were delivered 4.6 kg/d of AMS concentrate, whereas the L-Tx cows consumed 23.4 kg/d PMR and were delivered 2.0 kg/d of AMS concentrate. The results indicate that both dairy cow personality traits and AMS concentrate allocation influence their response to AMS training and subsequent feeding and milking behavior and production.
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 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) | 0.000 | 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".