Rapid identification of <i>Fusarium</i> species causing head blight in Canada using MALDI-TOF mass spectrometry
Bibliographic record
Abstract
Fusarium head blight is a limitation to grain production and can be caused by several different Fusarium species. We evaluated the ability of matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF MS) to perform species identifications. The method generates a unique peptide mass fingerprint (PMF) for each sample that can be matched to a reference library. We first created a reference library of PMF profiles for Fusarium species from across Canada. Then, we tested the library to perform identifications using two validation panels. The first panel consisted of 820 fungal isolates from wheat (2021–2023 harvest years) and the second was 74 fungal isolates from oat and barley (2022 harvest year). The species identity of samples from the validation panels was confirmed with high-throughput quantitative PCR using species-specific DNA markers. The first validation panel was mostly F. graminearum and there was 95% overlap between the MALDI-TOF MS and DNA-based identifications. The second panel was mostly F. poae and the identifications from the two methods had 86% overlap. Our findings indicate that MALDI-TOF MS biotyping is sensitive enough to identify Fusarium strains to their species complexes and certain Fusarium strains to the species level.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".