BioClay™ prolongs RNA interference‐mediated crop protection against <i>Botrytis cinerea</i>
Bibliographic record
Abstract
One of the most promising tools for the control of fungal plant diseases is spray-induced gene silencing (SIGS). In SIGS, small interfering RNA (siRNA) or double-stranded RNA (dsRNA) targeting essential or virulence-related pathogen genes are exogenously applied to plants and postharvest products to trigger RNA interference (RNAi) of the targeted genes, inhibiting fungal growth and disease. However, SIGS is limited by the unstable nature of RNA under environmental conditions. The use of layered double hydroxide or clay particles as carriers to deliver biologically active dsRNA, a formulation termed BioClay™, can enhance RNA durability on plants, prolonging its activity against pathogens. Here, we demonstrate that dsRNA delivered as BioClay can prolong protection against Botrytis cinerea, a major plant fungal pathogen, on tomato leaves and fruit and on mature chickpea plants. BioClay increased the protection window from 1 to 3 weeks on tomato leaves and from 5 to 10 days on tomato fruits, when compared with naked dsRNA. In flowering chickpea plants, BioClay provided prolonged protection for up to 4 weeks, covering the critical period of poding, whereas naked dsRNA provided limited protection. This research represents a major step forward for the adoption of SIGS as an eco-friendly alternative to traditional fungicides.
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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) | 0.001 | 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".