Resistance-related metabolites in wheat against <i>Fusarium graminearum</i> and the virulence factor deoxynivalenol (DON)
Why this work is in the frame
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Bibliographic record
Abstract
Inoculation with the virulence factor deoxynivalenol (DON) can induce disease symptoms in wheat ( Triticum aestivum L.) spikelets, even though it is not needed for the initial invasion by Fusarium graminearum Schwabe, thus the mechanism of plant defense against both the pathogen and DON, was investigated. Wheat cultivars that are resistant (‘Sumai3’) or susceptible (‘Roblin’) to fusarium head blight (FHB) were inoculated with F. graminearum, DON, or water. Inoculated spikelets were harvested 48 h after inoculation, the metabolites were extracted in methanol–water and chloroform, then derivatized and analyzed by gas chromatography – mass spectrometry. The metabolite peaks were deconvoluted and identified by manually matching the mass spectra with those in the NIST and GMD libraries. The peaks were aligned, and abundances were measured. A total of 117 metabolites were tentatively identified, including several antimicrobial metabolites and signal molecules or their precursors. Out of these 117 metabolites, 15 and 18 were identified as possible resistance-related (RR) metabolites, following F. graminearum (RRIF) and DON (RRID) inoculations, respectively, with 4 metabolites common to both. Canonical discriminant analysis of marginally significant metabolites (105) identified those with constitutive and induced resistance functions. The metabolites with high canonical loading to the canonical vectors were used to explain these functions. The putative roles of these RR metabolites in plant defense, their metabolic pathways, and their potential application for screening of wheat breeding lines for resistance to FHB are discussed.
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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 it