Effects of Alfalfa Particle Size and Specific Gravity on Chewing Activity, Digestibility, and Performance of Holstein Dairy Cows
Bibliographic record
Abstract
Two experiments were carried out to test the effects of alfalfa particle size and functional specific gravity (FSG) on chewing activity, digestibility, rumen kinetics, and production of lactating dairy cows fed corn silage based rations. In experiment 1, water-holding capacity (WHC), insoluble dry matter, hydration rate, and FSG changes were determined in alfalfa hay (varying in particle size) and corn silage. Reduction of particle size increased bulk density, FSG, and the rate of hydration, and decreased WHC of alfalfa. In experiment 2, 9 midlactation Holstein dairy cows fed total mixed rations containing 3 sizes of alfalfa hay (with geometric mean 7.83, 4.04, and 1.14 mm) were used in a replicated 3 x 3 Latin square design. The diets contained 20, 20, 35, 7, 7.5, 10, 0.3, 0.1, and 0.1% of DM alfalfa, corn silage, barley, soybean meal, beet pulp, wheat bran, dicalcium phosphate, vitamin premix, and salt, respectively. The geometric means (GM) of rations were 3.34, 2.47, and 1.66 mm in long, medium, and fine alfalfa treatments, respectively. Reduction of particle size increased daily NDF intake (kg), but decreased the proportion of physically effective factor (pef) and physically effective NDF (peNDF) in the ingested rations. Reduction of particle size increased the FSG of rations and intake of DM but reduced digestibility of NDF and ash. Reduction of particle size decreased ruminal mean retention time (RMRT), but increased the ruminal particulate passage rate. Milk and FCM yield were not affected by treatments. The rumen pH, total chewing activity, rumination, eating time, and milk fat were reduced as particle size decreased, but milk protein increased. This study showed that reduction of forage particle size increased bulk density, FSG, and hydration rate of alfalfa and was the most influential factor affecting DMI, milk composition, and chewing behavior. Reduction of forage particle size had minimal impact on digestibility and milk production.
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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) | 0.000 | 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".