Impact of Chlorella vulgaris and probiotic supplementation on performance, immunity and intestinal microbiota of broiler chickens
Bibliographic record
Abstract
Chlorella vulgaris has antioxidant, antimicrobial, and anti-inflammatory properties, as well as the probiotic that is important for keeping the intestinal microbiota balanced. The objective was to test the impact of supplementation with microalgae and/or probiotics on broiler chickens' performance, immunity, and intestinal microbiota. The experimental design was in randomized blocks in a 4x2 factorial scheme, with four levels of inclusion of C. vulgaris (0; 0.25; 0.50 and 1%) associated or not with a commercial probiotic with five replications of 26 chickens per experimental unit. The results showed that probiotics improved feed conversion. Probiotics increased the productivity index only at 0.25% C. vulgaris supplementation. There was a reduction in spleen weight at 42 days of age in chickens fed with probiotics, but the different treatments did not alter serum antibodies. Sampling age had a significant impact on richness addressed by the number of observed genera and diversity addressed by the Shannon index. The most abundant phylum in the chicken intestinal tract was Firmicutes followed by Bacteroidetes and Proteobacteria. Bifidobacterium spp. was found in animals receiving 1% microalgae and probiotics on day 42, suggesting that this genus has benefited from microalgae supplementation. It is concluded that the probiotic and C. vulgaris have the potential to improve performance without causing major changes in the immunity and cecal microbiota.
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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 | 0.001 |
| 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 | 0.001 | 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".