Effect of cultivar and enzyme supplementation on nutrient availability and performance of broilers fed Maritime Canadian wheat
Bibliographic record
Abstract
The feeding value of wheat is affected by the content of soluble non-starch polysaccharides (NSP), which varies among cultivars and the environment in which they are grown. Dietary enzymes can reduce the negative effects of NSP and improve the apparent metabolizable energy (AME) content of the wheat. This study examined differences in feeding value of four wheat cultivars grown in 2 crop years in the Maritime provinces of Canada and the need for enzymes. In a growth trial, diets containing one of the Maritime wheats or corn were fed with or without commercial enzymes containing, for wheat-based diets a mixture of xylanase and protease, and for corn-based diets a mixture of xylanase, protease, and amylase. In a broiler chick bioassay, diets containing 80% wheat were fed with or without a commercial enzyme with xylanase and protease activities. Enzymes significantly lowered body weight gain of birds fed Walton wheat in the second year, and improved the grower feed conversion ratio of birds fed Norboro wheat. Enzyme supplementation significantly improved apparent metabolizable energy and digestibility of crude protein. The AME content did not appear to be a direct indicator of performance. There were significant differences in AME content among the wheat samples. Enzymes generally did not improve performance in this study, possibly due to the relatively low in vitro viscosity values of these samples. Maritime wheats were equal or compared favourably with the sample of wheat from Western Canada and to locally obtained corn. Key words: Wheat, broiler performance, apparent metabolizable energy, enzyme
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".