Photodynamic Inactivation in agriculture: combating fungal phytopathogens resistant to conventional treatment
Bibliographic record
Abstract
Abstract Botrytis cinerea is a severe threat in agriculture, as it can infect over 200 different crop species with gray mold affecting food yields and quality. The conventional treatment using fungicides lead to emerging resistance over the past decades. Here, we introduce Photodynamic Inactivation (PDI) as a strategy to combat B. cinerea infections, independent of fungicide resistance. PDI uses photoactive compounds, which upon illumination create reactive oxygen species toxic for killing target organisms. This study focuses on different formulations of sodium–magnesium–chlorophyllin (Chl, food additive E140) as photoactive compound in combination with EDTA disodium salt dihydrate (Na 2 EDTA) as cell-wall permeabilizer and a surfactant. In an in vitro experiment, three different photosensitizers (PS) with varying Chl and Na 2 EDTA concentrations were tested against five B. cinerea strains with different resistance mechanisms. We showed that all B. cinerea mycelial spheres of all tested strains were eradicated with concentrations as low as 224 µM Chl and 3.076 mM Na 2 EDTA (LED illumination with main wavelength of 395 nm, radiant exposure 106 J cm −2 ). To further test PDI as a Botrytis treatment strategy in agriculture a greenhouse trial was performed on B. cinerea infected bell pepper plants ( Capsicum annum L). Two different rates (560 or 1120 g Ha −1 ) of PS formulation (0.204 M Chl and 1.279 M Na 2 EDTA) and a combination of PS formulation with 0.05% of the surfactant BRIJ L4 (560 g Ha −1 ) were applied weekly for 4 weeks by spray application. Foliar lesions, percentage of leaves affected, percentage of leaf area diseased and AUDPC were significantly reduced, while percentage of marketable plants were increased by all treatments compared to a water treated control, however, did not statistically differ from each other. No phytotoxicity was observed in any treatment. These results add to the proposition of employing PDI with the naturally sourced PS Chl in agricultural settings aimed at controlling B. cinerea disease. This approach seems to be effective regardless of the evolving resistance mechanisms observed in response to conventional antifungal treatments. Graphical abstract
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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".