Dietary multiprotease supplementation on growth performance and nutrient digestibility in turkey poults fed high-soybean meal diet
Bibliographic record
Abstract
This study was conducted to investigate the effect of dietary protease supplementation on growth performance, apparent total tract digestibility ( ATTD ) of nutrients, and standardized ileal digestibility (SID) of amino acids (AA) in turkey poults fed a diet with high soybean meal (SBM) inclusion. A total of 200 one-day-old male poults were allocated to four floor pens (50 poults/pen) and fed experimental diets for a 7-day conditioning period, with no statistical analysis performed. On d7, 140 turkey poults were selected and allocated to 28 cages (5 poults/cage; 7 replicates/treatment) and assigned to one of 4 dietary treatments in a 2 × 2 factorial design with two diet compositions [with and without highly digestible protein (meat and bone meal and enzymatically treated soybean meal)] and two protease dosages (0 and 500 g/ton). Feed and turkeys were weighed on d0, d7, d14, d21, and d25 to determine growth parameters. On days 23 and 24, excreta samples were collected; and on d25, all turkeys were euthanized to collect ileal digesta samples. From d7 to 14, turkey poults fed protease supplemented diets tended to have greater ( P < 0.1) body weight, weight gain, and feed conversion compared to no-supplemented poults, independent of dietary composition. No differences in body weight, body weight gain, daily feed intake, or feed conversion ratio were observed on day 25. Protease supplementation had the greatest SID of most indispensable amino acids (except Ile, Leu, and Phe) by an average of 2.21% (P < 0.05), all dispensable amino acids by an average of 4.47%, as well as the ATTD of dry matter and crude protein. Overall, greater nutrient digestion with protease supplementation may explain the transient growth improvement observed between d7-14. Protease supplementation provides a potential strategy to reduce starter diet costs (i.e. less complex diets) without negatively impacting growth performance.
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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) | 0.001 | 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".