Effects of compound feed additive on growth performance and intestinal microbiota of broilers
Bibliographic record
Abstract
The purpose of this experiment was to determine the effectiveness of compound feed additive (CFA) to replace antibiotics for broiler production. A total of 350 one-day-old Arbor Acres broilers were randomly divided into 7 groups, 5 replications in each group and 10 broilers in each replication. Group A was the control; group B was supplemented with 75 mg/kg chlortetracycline; groups C, D, and E were supplemented with 0.03, 0.06, and 0.09% CFA including glucose oxidase, curcumin, and Lactobacillus acidophilus; group F was supplemented with 0.03% CFA plus 0.50% glucose; group G was supplemented with 0.50% glucose. The feeding period was divided into the early (1-21 d) and later stages (22-42 d). The results showed that average daily gain (ADG) and feed conversion rate (F/G) in group F in later stage were significantly better than those in the control and antibiotic groups; the diarrhea rates in the groups containing CFA in both stages was significantly lower than that in the control and antibiotic groups, indicating that CFA was better than antibiotics to improve growth and decrease diarrhea rate for broilers. Pathogenic E. coli challenge significantly increased diarrhea rates and decreased ADG for broilers; however, CFA addition could alleviate the above negative responses by increasing gut Lactobacillus abundance and decreasing Shigella abundance. It can be concluded that CFA can replace antibiotics to regulate intestinal microbiota, reduce diarrhea rate, and improve broiler growth.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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 teacher head, 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".