Past peak lactational performance of Iranian Holstein cows fed raw or roasted whole soybeans
Bibliographic record
Abstract
Responses of past peak lactating Iranian Holstein cows to feeding roasted whole soybean (SB), raw SB or soybean meal (SBM) supplements were evaluated. Treatments consisted of a total mixed ration (TMR) with 34% forage (21% alfalfa hay and 13% corn silage) supplemented with 11.9% SBM or 13.3% roasted SB or raw SB. Diets were offered to 18 multiparous cows assigned randomly to one of three experimental diets for a 49-d trial. Dry matter intake was not significantly different, but total and fat-corrected milk yields were higher for cows fed the roasted SB diet than the other treatments. Milk fat concentration was not significantly different among treatments, but milk fat yield was significantly higher for cows fed the roasted SB and SBM diets. Milk protein concentration was significantly decreased by the raw and roasted SB diets, but milk protein yield was unaffected. Feeding roasted SB significantly reduced rumen ammonia N, plasma urea N and milk urea N concentrations. Ruminal pH, plasma glucose and beta-hydroxybutyrate concentrations were not affected. Compared with the other treatments, roasted SB increased plasma concentration of most essential amino acids, except leucine and phenylalanine. Although caution must be taken in the interpretation of the results due to the limited number of observations in the experiment, feeding roasted SB in a diet with alfalfa hay as the primary forage was beneficial. Key words: Whole soybean, lactational performance, blood metabolite, dairy cows
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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 | 0.000 |
| 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) | 0.001 | 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".