Utilization of wheat spike culture to assess Fusarium head blight disease progression and mycotoxin accumulation
Bibliographic record
Abstract
Fusarium head blight (FHB) caused by Fusarium graminearum Schwabe is a major disease of wheat (Triticum aestivum L.). FHB preferentially infects immature spikes and mycotoxins accumulate in developing grains, reducing yield and nutritional quality. The mycotoxins are type B trichothecene group of compounds including deoxynivalenol (DON), 3-acetyldeoxynivalenol (3-ADON), 15-acetyldeoxynivalenol (15-ADON), and nivalenol (NIV) that also act as virulence factors during FHB infection and disease progression. An enzyme UDP-glucosyl transferase (EC 2.4.1.x) glycosylates DON to deoxynivalenol-3-glucoside (D3G), thus rendering it ineffective as a virulence factor. The present study analysed the association of DON, 3A-DON, and D3G with FHB severity using in vitro spike culture for FHB screening. The mycotoxins in FHB-resistant and -susceptible spikes were extracted using a single step extraction method, and their concentration was determined using an LC-MS/MS method that differentiated all the five mycotoxins. Pairwise comparisons of FHB-resistant and -susceptible spike culture derived variants (SCDV) using Tukey’s method showed significant (P ≤ 0.001) variation for disease severity and accumulation of DON, 3-ADON, and D3G at seven and nine days after fungal inoculation. FHB severity showed a significant positive correlation to the accumulation of DON, 3-ADON, and D3G, but an inverse correlation to the ratio between D3G and DON.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".