Synergistic activation of grapevine defense mechanisms against downy mildew by Ascophyllum nodosum extract and Pseudomonas fluorescens CHA0
Bibliographic record
Abstract
Downy mildew, caused by Plasmopara viticola, poses a major threat to grapevine production, necessitating effective and sustainable disease management strategies. Ascophyllum nodosum extract (ANE) and Pseudomonas fluorescens CHA0 possess biostimulant and biocontrol properties, respectively, with reported potential to induce plant defense against various pathogens. However, their combined application and potential synergistic effects in grapevine disease management remain largely unexplored. In this study, their efficacy in controlling downy mildew in grapevines was investigated. Our results demonstrate that both ANE and CHA0, individually and in combination, significantly reduced downy mildew severity. In vitro assays revealed that grape leaves treated with ANE, CHA0, or their combination suppressed disease establishment and progression, with the combined treatment showing the greatest reduction in spore count (~66%), zoospore numbers (~89–93%), and empty sporangia (~53–69%). In vivo greenhouse experiments confirmed these findings, showing that combined foliar applications of ANE and CHA0 reduced downy mildew incidence to approximately 22%, compared to 40–50% with individual treatments and 70% in untreated controls, implying a synergistic interaction between these treatments. In addition to disease suppression, combined ANE and CHA0 applications triggered robust biochemical and molecular defense responses in grapevines. Key defense enzymes, including phenylalanine ammonia lyase, peroxidase, and polyphenol oxidase, showed significantly enhanced activities, accompanied by elevated levels of phenolics and hydrogen peroxide. At the molecular level, the combination significantly upregulated stress-responsive genes such as CHI, GLP2 and GLP7, along with jasmonic acid-responsive genes including LOX9, OSM1, and PR4, suggesting a priming effect that reinforces the plant’s innate immune responses. Overall, these findings highlight the potential of combined ANE and CHA0 treatments in enhancing grapevine resistance to downy mildew through the activation of defense mechanisms and modulation of key biochemical markers. The synergistic interplay between the biostimulant and biocontrol agent offers a promising eco-friendly alternative to conventional chemical-based disease management in viticulture.
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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".