Postharvest control of blue mold and gray mold on apples using isolates of<i>Pseudomonas syringae</i>
Bibliographic record
Abstract
Abstract Four isolates of Pseudomonas syringae, MA-4, MB-4, MD-3b, and NSA-6, from the phyllospere of apple trees, were evaluated as biocontrol agents for controlling blue mold [Penicillium expansum] and gray mold [Botrytis cinerea] of apples (Malus domestica) in storage. When separately co-inoculated with the two pathogens, the four isolates at a concentration of 1 × 107 CFU/mL controlled blue mold by 78–94% after incubation at 20°C for 5 days and by 64–70% at 4°C for 28 days. The incidence of gray mold was also significantly reduced by P. syringae isolates MD-3b, NSA-6, and MA-4 under these conditions. However, a higher concentration of P. syringae MA-4 and NSA-6 was required to control gray mold compared to blue mold. Spray treatment with P. syringae MA-4 significantly controlled blue mold on 'Empire' and 'Delicious' apples at 18 and 4°C. Under conditions similar to those of controlled atmosphere in commercial storage, a dip treatment with P. syringae MA-4 significantly controlled blue mold on 'Empire' and 'Delicious' apples and was more effective than the treatment with BioSave™, a commercially available biofungicide. Pseudomonas syringae MA-4 at a concentration of 1 × 108 CFU/mL controlled blue mold as efficiently as the chemical treatment with a combination of thiabendazole and diphenylamine.Key words: biocontrol, postharvest, Malus domestica, Penicillium expansum, Botrytis cinerea. Keywords: biocontrolpostharvestMalus domesticaPenicillium expansumBotrytis cinerea
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".