Effect of Hexanal Vapor on the Growth of Postharvest Pathogens and Fruit Decay
Bibliographic record
Abstract
The effect of the natural volatile hexanal was studied as an antifungal agent on the major postharvest fungal pathogens Botrytis cinerea, Monilinia fructicola, Sclerotinia sclerotiorum, Alternaria alternata, and Colletotrichum gloeosporioides. The antifungal effect of hexanal vapor was dependent on concentration and treatment duration, but sensitivity of the pathogens varied. All spores of B. cinerea and M. fructicola were killed after exposure to 900 microL/L for 12 h at 20 degrees C, and almost all were killed after a 24-h exposure to 450 microL/L. Only moderate numbers of spores were killed at a concentration of 200 microL/L. Mycelial growth of S. sclerotiorum on agar was completely inhibited after a 12-h exposure to 900 microL/L, but only slight inhibition occurred at 450 microL/L and none at 200 microL/L. Mycelium of A. alternata and C. gloeosporioides appeared more sensitive, with strong inhibition occurring after a 12-h exposure at 450 microL/L. Similar trends in spore viability and mycelial growth were observed at 7 degrees C. The antifungal effect of hexanal vapor was further tested on raspberry fruit naturally infected with B. cinerea and on peach fruit inoculated with spores of M. fructicola. Decay was markedly reduced in raspberry and almost completely controlled in peach after exposure to 900 microL/L hexanal vapor for 24 h. The potential of hexanal for postharvest decay control is discussed.
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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".