Maize replacement with sorghum and a combination of protease, xylanase and phytase on performance, nutrient utilization, litter moisture and digestive organ size in broiler chicken
Bibliographic record
Abstract
We investigated the effects of a combination of protease, xylanase, and phytase in maize- or sorghum-based diets for broilers. Two experiments were conducted with male chicks randomly distributed in a 3 × 2 factorial arrangement with three replacement levels of maize with sorghum (0%, 50%, and 100%) with or without enzymes. In the first trial, 1152 chicks were allotted to 36 floor pens to determine performance, relative organ weight, and litter moisture. A second trial was performed with 150 and 120 chicks allotted in 30 cages with five and four broilers per cage to determine nutrient and energy utilization from 11 to 21 d and from 25 to 35 d, respectively. Enzyme supplementation improved body-weight gain and feed conversion ratio. Total maize replacement with sorghum compromised body-weight gain from 1 to 14 d and from 1 to 35 d. Nitrogen retention was reduced by partial and total maize replacement with sorghum at starter phase and by total replacement at grower phase. Enzyme supplementation improved nitrogen retention at starter phase and apparent metabolizable energy at starter and grower phases. Therefore, partial maize replacement with sorghum is viable and on top application of an enzyme blend containing protease, xylanase, and phytase improves performance and nutrient retention of broilers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".