Volatile metabolites from the headspace of onion bulbs inoculated with postharvest pathogens as a tool for disease discrimination
Bibliographic record
Abstract
Gas chromatography and mass spectrometry was used to analyze volatiles in the headspace of 'Fortress' onion bulbs inoculated with Fusarium oxysporum, Botrytis allii, Erwinia carotovora subsp. carotovora, Aspergillus niger, or Penicillium aurantiogriseum. A total of 130 volatile metabolites were detected, of which 28 occurred more than four times in seven replicates and two incubation periods. Out of 28 relatively consistent compounds, 12 compounds were specific to one or more diseases or inoculations. Ethyl cyclobutane was specific to bulbs inoculated with F. oxysporum, while styrene was common to A. niger, E. carotovora subsp. carotovora, and F. oxysporum, with the highest abundance in the latter. N-3-Aminophenyl acetamide was common to E. carotovora subsp. carotovora, P. aurantiogriseum, and the water inoculated control. 2-Azabicyclo[3.2.0]hept-6-ene was detected in bulbs inoculated with A. niger, E. carotovora subsp. carotovora, and P. aurantiogriseum. Discriminant analysis models based on metabolic fingerprints (normalized abundances of 27 relatively consistent metabolites and normalized abundances of 150 mass ions) correctly classified up to 100% of the observations based on resubstitution (models) and up to 100% based on cross-validation, depending on the disease. Factor analysis identified combinations of metabolites to discriminate diseases or inoculations. The disease discriminatory compounds identified as metabolic markers and the discriminant analysis models can be used to discriminate bulb diseases of 'Fortress' onion, at the beginning of or during storage, after further validation under commercial conditions.
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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) | 0.000 | 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 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".