Replacement of soybean meal with roasted full-fat soybeans from high-protein or conventional cultivars in diets for broiler chickens
Bibliographic record
Abstract
The effects were examined of replacing part or all of the soybean meal in the starter and finisher diets for male broiler chickens with ground, roasted, full-fat soybeans from either a high-protein (AC Proteus) or conventional (Baron) cultivar. The starter (1–21 d) and finisher (22–36 d) diets were formulated by replacing, on an isonitrogenous basis, part or all of the soybean meal in the barley–wheat-based control diets with the roasted soybeans. Digestibility of dry matter, corrected nitrogen and energy were estimated by an index method for the last 2 d of the starter and grower periods. Soybean level influenced body weight gains directly in a quadratic manner, and feed intakes or feed conversions by inversely linear relationships (P < 0.05 and P < 0.01) during the starter period. Performance during the finisher period or during the entire growth period was not influenced (P > 0.05) by dietary soybean source. Dry matter and energy digestibilities at both 21 and 35 d, and nitrogen at 35 d were affected in a quadratic manner (P < 0.05 or P < 0.01) by the soybean level of the diets, whereas, a linear relationship was present for the apparent metabolizable energy (AME) content (P < 0.001). Soybean source had no effect on nutrient utilization, except for dry matter or energy digestibility during the starter period (P < 0.01). In conclusion, the optimal performance should be obtained when the ratio of roasted full-fat soybeans to soybean meal is about 2:1 in the starter feeds for broiler chickens. Key words: Full-fat soybeans, soybean meal, high-protein soybeans, broiler, growth, nutrient digestibilities
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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".