Effects of litter from antimicrobial-fed broiler chickens on soil bacterial community structure and diversity
Bibliographic record
Abstract
This study examined changes in soil bacterial community composition and diversity in response to fertilization with litter from chickens fed a diet without antibiotics and with bambermycin, penicillin, bacitracin, salinomycin, or mix of salinomycin and bacitracin. Litter (27.5 T/ha) was applied to 24 agricultural plots in the Fraser Valley of British Columbia. Nonfertilized plots were used as a negative control. Soil samples collected from the studied plots were used to quantify Escherichia coli by plate counts, and Clostridium perfringens by qPCR. The 16S rRNA gene sequencing was performed for microbiota analysis. Following litter application in December, the population size of E. coli was 5.4 log CFU/g; however, regardless of treatments, the results revealed 5.2 and 1.4 log CFU/g of E. coli in soil sampled in January and March, respectively. Fertilization with litter from antibiotic-treated birds increased ( P < 0.05) the relative abundance of Proteobacteria, Actinobacteria, and Firmicutes in soil, but decreased Acidobacteria and Verrucomicrobia groups. The alpha diversity parameters were higher ( P < 0.05) in nonfertilized soil compared to the fertilized ones, suggesting that litter application was a major factor in shaping the soil bacterial communities. These results may help develop efficient litter management strategies like composting, autoclaving, or anaerobic digestion of poultry litter before application to land for preservation of soil health and crop productivity.
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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) | 0.000 | 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 | 0.000 |
| 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".