Rapid Screening of Ergot Alkaloids in Sclerotia by MALDI-TOF Mass Spectrometry
Bibliographic record
Abstract
Ergot is a common disease of wheat and other cereal grains that is predominantly caused by Claviceps purpurea in the field, often affecting crop yield in addition to the environment. Infected grain can be contaminated with dark sclerotia, which contain fungal metabolites such as ergot alkaloids. The occurrence of ergot alkaloids in cereal grain is a major health concern for humans and livestock. Effective and rapid screening of these mycotoxins is crucial for producers, processors, and consumers of cereal-based food and feed grain. Established methods of ergot alkaloid screening based on LC-MS or GC-MS require laborious processes. A novel method using matrix-assisted laser desorption ionization (MALDI)-time-of-flight (TOF) MS was developed to identify four ergot alkaloids. Using dihydroxybenzoic acid as the matrix, ergosine, ergocornine, ergocryptine, and ergocristine were readily detected in individual sclerotia of C. purpurea. The accuracy of the identified ergot alkaloids was further confirmed by tandem MS analysis. MALDI-TOF MS is suitable for high-throughput screening of ergot alkaloids because it permits rapid and accurate identification, simple sample preparation, and no derivatization or chromatographic separation.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".