Dehydrodimers of Ferulic Acid in Maize Grain Pericarp and Aleurone: Resistance Factors to <i>Fusarium graminearum</i>
Bibliographic record
Abstract
ABSTRACT The relationship between the primary cell wall phenolic acids, dehydrodimers of ferulic acid, and maize grain resistance to Fusarium graminearum, the causal agent of gibberella ear rot, was investigated. Concentrations of dehydrodimers of ferulic acid were determined in the pericarp and aleurone tissues of five inbreds and two hybrids of varying susceptibility and in a segregating population from a cross between a resistant and susceptible inbred. Significant negative correlations were found between disease severity and diferulic acid content. Even stronger correlations were observed between diferulic acid and the fungal steroid ergosterol, which is an indicator of fungal biomass in infected plant tissue. These results were consistent over two consecutive field seasons, which differed significantly for temperature and rainfall during pollination, the most susceptible stage of ear development. No correlation was found between the levels of these phenolics and deoxynivalenol levels. This is the first report of in vivo evidence that the dehydrodimers of ferulic acid content in pericarp and aleurone tissues may play a role in genotypic resistance of maize to gibberella ear rot.
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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) | 0.000 | 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 | 0.000 |
| 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".