Valine and isoleucine supplementation improve performance and serum biochemical concentrations in growing gilts fed low-protein diets
Bibliographic record
Abstract
This study evaluated the effects of valine and isoleucine supplementation in low-crude-protein (CP) diets on performance, serum parameters, and carcass traits in growing gilts. Two-hundred gilts (29.1 ± 1.7 kg) were allotted randomly to one of five diets that included a control CP (177 g kg−1) or four low-CP (135 g kg−1) diets for 45 d. The low-CP diets were added with lysine + threonine + methionine (LCM), LCM+ tryptophan (LCT), LCT + valine (LCV), or LCV + isoleucine (LCI), respectively. Non significant difference in average daily gain was obtained in gilts receiving the control, LCV, or LCI diets, which was higher than that of pigs fed the LCM or LCT diets (P < 0.05). The supplementation of crystalline tryptophan, valine, and isoleucine improved the average daily feed intake and serum levels of total protein, tryptophan, and isoleucine (linear and quadratic effects, P < 0.05) and serum valine concentration (linear effect, P < 0.05). The results indicated that the valine supplementation, or the both combination of valine and isoleucine, could further improve the performance in 29–62 kg gilts fed the 135 g kg−1 CP diet.
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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".