Species Composition and Toxigenic Potential of Fusarium Isolates Causing Fruit Rot of Sweet Pepper in China
Bibliographic record
Abstract
Apart from causing serious yield losses, various kinds of mycotoxins may be accumulated in plant tissues infected by Fusarium strains. Fusarium mycotoxin contamination is one of the most important concerns in the food safety field nowadays. However, limited information on the causal agents, etiology, and mycotoxin production of this disease is available on pepper in China. This research was conducted to identify the Fusarium species causing pepper fruit rot and analyze their toxigenic potential in China. Forty-two Fusarium strains obtained from diseased pepper from six provinces were identified as F. equiseti (27 strains), F. solani (10 strains), F. fujikuroi (five strains). This is the first report of F. equiseti, F. solani and F. fujikuroi associated with pepper fruit rot in China, which revealed that the population structure of Fusarium species in this study was quite different from those surveyed in other countries, such as Canada and Belgium. The mycotoxin production capabilities were assessed using a well-established liquid chromatography mass spectrometry method. Out of the thirty-six target mycotoxins, fumonisins B1 and B2, fusaric acid, beauvericin, moniliformin, and nivalenol were detected in pepper tissues. Furthermore, some mycotoxins were found in non-colonized parts of sweet pepper fruit, implying migration from colonized to non-colonized parts of pepper tissues, which implied the risk of mycotoxin contamination in non-infected parts of food products.
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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 | 0.000 |
| 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 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".