Dietary <i>Bacillus subtilis-</i> and <i>Clostridium butyricum</i>-based probiotics supplement improves growth and meat quality, and alters microbiota in the excreta of broiler chickens
Bibliographic record
Abstract
This study investigated the effects of the multi-probiotics consisting of Bacillus subtilis and Clostridium butyricum with varying doses (0%, 0.05%, 0.1%, and 0.2%) on the growth performance, nutrient digestibility, meat quality, and cecal microbes of male broiler chickens. Seven hundred and twenty Ross 308, 1-day-old male broiler chicks were distributed into four dietary groups. Over 35 days of feeding, the average daily gain (ADG) was linearly elevated ( P < 0.05) during days 1–21 and 1–35 as probiotic doses increased. The average daily feed intake (ADFI) tended to be linearly ( P = 0.059) increased from day 22 to 35, and was improved from day 1 to 35 ( P = 0.031). Ascending doses of multi-probiotics tended to ( P = 0.060) reduce Clostridium perfringens counts on day 35 and prompted ( P = 0.001) the proliferation of Lactobacillus. Moreover, broilers fed a 0.1% dose of multi-probiotics had a higher pH and water-holding capacity ( P < 0.05) in the breast meat. In conclusion, the 0.2% multi-probiotics could boost ADG by improving ADFI and modulating the cecal microbe. The dietary 0.1% multi-probiotics contributed to better meat quality.
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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".