Effect of wheat cultivar and enzyme supplementation on nutrient availability and performance of laying hens
Bibliographic record
Abstract
This study examined the effect of four wheat cultivars (Belvedere, Glenlea, Norboro, and Walton) grown in the Maritime provinces of Canada and dietary enzyme supplementation on apparent metabolizable energy (AME), digestibility of crude protein (CP), and performance of laying hens, and compared these values to those obtained using a corn-based diet. Forty groups of three adjacent battery cages, each housing two hens, were fed each diet which included the wheat samples (61.0%) or locally obtained corn (65.1%), with or without commercial enzymes containing a mixture of xylanase, protease, and amylase for corn-based diets and a mixture of xylanase and protease for wheat-based diets. Excreta samples were collected at 17 d for analysis of nutrient retention. The diet that the hens consumed had no significant effect on performance. The feed conversion ratio of hens was lowest (1.79) in the final week of the experiment when egg production was highest (97.0%) and feed intake lowest (109 g bird-1 d-1). The diet significantly affected both AME and digestibility of CP. The wheat cultivar influenced the AME and digestibility of CP when these diets were fed to laying hens, with enzyme supplementation reducing the AME and digestibility of CP for diets containing three (Belvedere, Glenlea, and Walton) of the four wheat cultivars. The significant improvement with enzyme supplementation of the corn-based diet is promising and should be the basis of future studies. Key words: Wheat, layers, 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) | 0.000 | 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 | 0.000 |
| 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".