Influence of Acacia tortilis leaf meal-based diet on serum biochemistry, carcass characteristics and internal organs of finishing pigs
Bibliographic record
Abstract
Dietary inclusion of tannin-rich leguminous leaf meals beyond threshold levels can impose toxicity and compromise welfare of pigs. The objective of the study was to determine the response of metabolites, carcass characteristics and internal organs of finishing pigs to Acacia tortilis leaf meal inclusion levels. Thirty Large White × Landrace pigs (61.6 ± 1.23 kg bodyweight) were randomly allotted to six dietary treatments, to give five replicates per treatment. The treatments contained 0, 50, 100, 150, 200 and 250 g/kg of A. tortilis leaf meal and were rendered iso-energetic and iso-nitrogenous. An increase in A. tortilis inclusion was related to an initial increase and then a decrease in feed intake (P < 0.05), weight gain (P < 0.001) and feed conversion ratio (P < 0.05). Serum concentrations of iron and activities of aspartate aminotransferase and alkaline phosphatases increased quadratically (P < 0.001) as A. tortilis leaf meal increased. There was a significant linear increase in alanine aminotransferase activity with leaf meal incremental level. Hepatosomatic index, scaled kidney weight and scaled heart weight increased linearly (P < 0.001) as A. tortilis increased. There was a quadratic increase in the relative weight of lungs (P < 0.001) as leaf meal increased. Although quadratic decreases (P < 0.01) in cold-dressed mass and dressing percentage were observed with incremental levels of A. tortilis leaf meal, there was a linear decrease (P < 0.05) in backfat thickness. It was concluded that serum biochemistry, internal organs and carcass characteristics respond differently to increases in A. tortilis inclusion. The A. tortilis leaf meal can be supplemented in finishing pig diets at low levels before feed efficiency and carcass characteristics are negatively affected.
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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 | 0.001 |
| 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".