Evaluation of the blend of organic acids and medium-chain fatty acids in matrix coating as antibiotic growth promoter alternative on growth performance, nutrient digestibility, blood profiles, excreta microflora, and carcass quality in broilers
Bibliographic record
Abstract
This study was conducted to evaluate the effects of the blend of organic acids (OAs) and medium-chain fatty acids (MCFAs) in broiler chickens. A total of 816 1-d-old male Ross 308 broiler chickens (35 ± 0.44 g) were randomly allocated into 1 of the following 6 dietary treatments (17 broilers per pen with 8 pens per treatment): dietary treatments consisted of corn-soybean meal-based basal diet and the basal diet supplemented with 0.02, 0.03, 0.04, 0.05, and 0.06% blend of OAs and MCFAs. The study lasted 5 wk during which growth performance was determined. In the current study, the inclusion of 0.02, 0.03, 0.04, 0.05, and 0.06% blend of OAs and MCFAs in the basal diet linearly increased (P < 0.05) body weight gain and improved feed conversion ratio (P < 0.0001) on day 7 to 14, day 14 to 35, as well as overall. Increasing inclusion of the blend of OAs and MCFAs levels in the diets also linearly increased (P = 0.001) the digestibility of dry matter on day 35. Broilers fed with different levels of the blend of OAs and MCFAs showed a linear increment (P = 0.042) in Lactobacillus concentration and decrease (P = 0.002) in Escherichia coli concentration. With regard to relative organ weight, a trend of linear reduction (P = 0.052) in bursa of Fabricius weight of broilers fed the blend of OAs and MCFAs was observed. There was a significant linear improvement (P = 0.011) in the IgG concentration associated with the inclusion of the blend of OAs and MCFAs levels in the diets. In conclusion, the blend of OAs and MCFAs supplementation positively influenced growth performance, nutrient digestibility, and excreta microflora in broiler chickens.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".