Effects of dried citrus pulp and fermented medicinal plants on growth performance, nutrient digestibility, blood characteristics, and meat quality in growing–finishing pigs
Bibliographic record
Abstract
The present experiment was conducted to determine the effects of dried citrus pulp and fermented medicinal plants in growing–finishing pigs. A total of 96 pigs (62.34 ± 1.96 kg body weight) were randomly allotted into three dietary treatments: (1) control, basal diet (CON); (2) diet containing 10% dried citrus pulp (DCP); (3) diet containing 10% dried citrus pulp supplemented with 0.1% fermented medicinal plants (DCPFMP). From weeks 0 to 5 and 0 to 10, pigs fed the DCPFMP diet had significantly decreased (P < 0.05) average daily feed intake and increased (P < 0.05) gain:feed ratio compared with those fed the CON diet. The apparent total tract digestibility of gross energy was greater (P < 0.05), and serum total cholesterol concentration was decreased (P < 0.05) for pigs fed the DCPFMP diet compared with those fed the DCP diet in week 10. In addition, an increase (P < 0.05) in Longissimus muscle area was observed for pigs fed the DCPFMP diet compared with those fed the CON diet. In conclusion, supplementation with fermented medicinal plants in a diet containing 10% dried citrus pulp improved growth performance and Longissimus muscle area and lowered serum low-density lipoprotein cholesterol and total cholesterol concentrations.
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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) | 0.001 | 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 | 0.001 |
| 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".