Occurrence of Aflatoxin B1, deoxynivalenol and zearalenone in feeds in China during 2018–2020
Bibliographic record
Abstract
Abstract Background The current study was conducted to investigate the individual and combined occurrence of aflatoxin B 1 (AFB 1 ), deoxynivalenol (DON) and zearalenone (ZEN) in feeds from various Provinces of China during 2018 to 2020. A total of 3,507 feed samples, including 2,090 feed ingredients and 1,417 complete feed samples, were collected from different areas of China for mycotoxins analysis. Results The individual contamination of AFB 1 , DON and ZEN were present in more than 81.9%, 96.4% and 96.9% of feed samples, respectively, with average concentration ranges of AFB 1 between 1.2–27.4 μg/kg, DON between 458.0–1,925.4 μg/kg and ZEN between 48.1–326.8 μg/kg. Notably, 0.9%, 0.5% and 0.1% of feed ingredients, and 1.2–12.8%, 0.9–2.9% and 0–8.9% of complete feeds for pigs, poultry and ruminants with AFB 1 , ZEN and DON that exceeded China’s safety standards, respectively. Moreover, more than 81.5% of feed ingredients and 95.7% of complete feeds were co-contaminated with various combinations of these mycotoxins. Conclusion This study indicates that the feeds in China were universally contaminated with AFB 1 , DON and ZEN during the past 3 years. These findings highlight the significance of monitoring mycotoxin contaminant levels in the domestic animal feed, and the importance of carrying out feed administration and remediation strategies for mycotoxin control.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".