Rapid screening of <i>Alternaria</i> mycotoxins using MALDI‐TOF mass spectrometry
Bibliographic record
Abstract
BACKGROUND: Members of the Alternaria genus produce various toxins whose occurrence in agricultural commodities is a major concern for humans and the environment. The present study developed a simple and efficient matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) method for the rapid detection of Alternaria toxins. RESULTS: A new method for the detection of alternariol (AOH), alternariol monomethyl ether (AME) and tentoxin (TEN) by MALDI-TOF MS was developed. Different solid phase extraction (SPE) clean-up methods were tried to optimize the purification of wheat matrix, and an optimal extraction method was designed to recover the three Alternaria toxins. In addition, various MALDI matrices were examined and α-cyano-4-hydroxycinnamic acid (CHCA) matrix gave good repeatability for all three Alternaria toxins. CONCLUSION: This is the first study to report the detection of three important Alternaria toxins concurrently using MALDI-TOF MS and opens up the possibility of rapid screening of Alternaria toxins in several other cereals and food products. © 2016 Her Majesty the Queen in Right of Canada Journal of the Science of Food and Agriculture © 2016 Society of Chemical Industry.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".