Dietary Forage Concentration Affects the Feed Sorting Behavior of Lactating Dairy Cows
Bibliographic record
Abstract
The objective of this study was to determine whether the amount of forage in a total mixed ration influences feed sorting by cows and whether the extent of this sorting changes as they adapt to a new diet. Six lactating Holstein cows, individually fed once per day, were provided each of 2 diets in a crossover design (dry matter basis): 1) a higher forage diet (HF; 62.3% forage), and 2) a lower forage diet (LF; 50.7% forage). Dry matter intake, feeding behavior, and sorting activity were monitored for each cow on each diet for 7 d. Fresh feed and orts were sampled daily for each cow and subjected to neutral detergent fiber (NDF) and particle size analysis. The particle size separator contained 2 screens (18 and 9 mm) and a bottom pan, resulting in 3 fractions (long, medium, and short). Sorting activity [for each fraction, NDF and physically effective NDF (peNDF)] was calculated as the actual intake expressed as a percentage of the predicted intake. Overall, sorting activity was greatest on the LF diet, with cows sorting for short particles but against long particles, medium particles, NDF, and peNDF. On the HF diet, cows sorted against long particles, NDF, and peNDF and sorted for short particles. Treatment x day interactions occurred for sorting for short particles and against peNDF, indicating that it took cows 1 d to adjust their sorting behavior to the LF diet. Cows on the LF diet consumed more dry matter but spent less time feeding, which resulted in a greater intake rate compared with cows on the HF diet. These results indicate that cows rapidly adjust their sorting behavior when subjected to a dietary change, and they exhibit more sorting for short particles and against long particles, NDF, and peNDF when fed an LF diet.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| 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 teacher head, 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".