In the search for low-cost year-round feeds: Pen-level growth performance of local and crossbred Ugandan pigs fed forage- or silage-based diets versus commercial diet
Bibliographic record
Abstract
Smallholder pig farmers in East Africa report that lack of feed, seasonal feed shortages, quality and cost are key constraints to pig rearing. Commercially prepared pig diets are too expensive and people and pigs compete for food. Smallholder farmers typically feed nutritionally unbalanced diets, resulting in low average daily gain (ADG) and poor farmer profits. Our objective was to compare the ADG of Ugandan pigs fed forage- or silage-based or commercial diets. Ugandan weaner-grower pigs were randomly assigned to forage- or silage-based diets or commercial diet. Pigs were weighed every 3 weeks from 9 to 32 weeks of age. Pen-level ADG and feed conversion were compared across diets using multiple linear regression. The ADG of pigs fed forage- or silage-based diets was lower than those fed commercial diets between 9 and 24 weeks of age (p < 0.05). Between 28 and 32 weeks, pigs fed forage-based diets had lower ADG than those on other diets (p < 0.05). Least squares mean ADG (g/pig/day) for pigs fed forage- or silage-based diets or commercial diet were 36, and 52, and 294 respectively at 9–15 weeks; 163, 212, 329 at 15–19 weeks; 112, 362, 574 at 20–24 weeks and 694, 994, and 1233 at 28 to 32 weeks of age. It was concluded that forage- and silage-based diets are unsuitable for small, newly weaned pigs. Feeding forage- or silage-based diets to finishing pigs is more suitable. Forage- and silage based diets are year-round low-cost pig-feeding strategies that will improve the growth performance of East African pigs, thereby increasing pig farmer income and food security.
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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 | 0.001 | 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 | 0.001 | 0.001 |
| 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".