Effect of dietary inclusion of safflower meal on ruminal fermentation, growth performance, carcass characteristics, and meat quality of lambs
Bibliographic record
Abstract
This study examines the effect of including graded levels of safflower meal (SM) [0 (SM0), 150 (SM15), or 200 g kg−1 dry matter (SM20)] in diets of Katahdin–Pelibuey lambs on ruminal fermentation, growth performance, and meat quality. Experimental diets were randomly allocated to 24 lambs (29.25 ± 0.55 kg) in a 60 d feeding trial. On day 30, rumen fluid was collected from each sheep at 0, 3, and 6 h after morning feeding to measure pH, ammonia, and volatile fatty acids. Feed intake, nutrient digestibility, growth performance, carcass characteristics, and meat quality were also measured. Feed intake, ruminal volatile fatty acids concentration, dry matter, and crude protein digestibility were not affected (P > 0.05) by diets. Lambs fed on SM15 had higher (P < 0.05) ruminal pH at 3 and 6 h post feeding compared with those on SM0 and SM20. Inclusion of SM increased (P < 0.05) ruminal ammonia concentration at 3 and 6 h post feeding; however, daily gain decreased with increasing levels of SM. Diets did not affect (P > 0.05) carcass and meat quality traits. Feeding SM-containing diets resulted in similar feed utilization, carcass characteristics, and meat quality to the control diet while improving ruminal fermentation parameters.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".