Silicon Enhances the Accumulation of Diterpenoid Phytoalexins in Rice: A Potential Mechanism for Blast Resistance
Bibliographic record
Abstract
ABSTRACT Although several reports underscore the importance of silicon (Si) in controlling Magnaporthe grisea on rice, no study has associated this beneficial effect with specific mechanisms of host defense responses against this fungal attack. In this study, however, we provide evidence that higher levels of momilactone phytoalexins were found in leaf extracts from plants inoculated with M. grisea and amended with silicon (Si(+)) than in leaf extracts from inoculated plants not amended with silicon (Si(-) ) or noninoculated Si(+) and Si(-) plants. On this basis, the more efficient stimulation of the terpenoid pathway in Si(+) plants and, consequently, the increase in the levels of momilactones appears to be a factor contributing to enhanced rice resistance to blast. This may explain the lower level of blast severity observed on leaves of Si(+) plants at 96 h after inoculation with M. grisea. The results of this study strongly suggest that Si plays an active role in the resistance of rice to blast rather than the formation of a physical barrier to penetration by M. grisea.
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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 | 0.000 | 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) | 0.002 | 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".