The dietary inclusion of plant extracts improves growth performance, gut microbiota and blood parameters of broilers: a meta-analysis
Bibliographic record
Abstract
A growing body of literature examined the effects of including plant extracts in poultry diets. Most of these studies have focused on changes in growth performance (weight gain, feed intake, feed conversion ratio, etc.) resulting from dietary inclusion of plant extracts. The effects of plant nutraceutical extract on broiler chickens have been reported with different results. Thus, this meta-analysis aimed to gauge the effect of plant nutraceutical extract on broiler chickens’ growth, intestinal components and blood characteristics. Two publicly available databases were searched to find studies evaluating dietary plant nutraceutical extracts on broiler chickens. The study selection was based on predefined criteria and two publicly available databases, ScienceDirect and Google Scholar, were utilised for execution. The analysis comprised 24 studies involving 60 treatment groups eligible for analysis in RevMan software. The results showed that plant nutraceutical extract inclusion significantly reduced feed conversion ratio (p < .05), leading to improved production performance. The pathogenic gut microbiota was also influenced by a significant reduction in Salmonella and Escherichia coli counts (p < .05) in the broilers. Plant nutraceutical-based diets also significantly increased the Lactobacillus and Bifidobacteria (p < .01) in broiler chickens. In addition, blood characteristics had significantly higher haemoglobin and globulin or total cholesterol, whereas triglycerides had a significantly lower impact than the control group. Consequently, plant extracts have the potential to serve as natural alternatives to antibiotics to reduce the risk of antimicrobial resistance and support sustainable poultry production. However, application of latest technologies is required to attain its full potential.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.037 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".