Control of Postharvest Fungal Rots on Grapes Using Essential Oil of Foeniculum vulgare Mill.
Bibliographic record
Abstract
Fungal rots, caused by Botrytis cinerea and Colletotrichum acutatum, are the main causes of postharvest decay of table grapes in Brazil. The aim of this study was to assess the chemical composition and the fungicidal effect of Foeniculum vulgare essential oil in vitro, on mycelial growth (contact and volatile phase) and conidia germination, and in vivo on postharvest grapes against both fungi. The major compounds found in F. vulgare essential oil were trans-anethole (79.14%), fenchone (11.94%) and estragole (5.76%). The mycelial growth (contact phase) and conidia germination of B. cinerea were inhibited completely at concentrations of 50 and 100 ppm (µL mL-1), respectively. For C. acutatum, mycelial growth (contact phase) and conidia germination were inhibited completely at concentrations of 100 and 200 ppm, respectively. The volatile phase had a fungistatic effect on mycelial growth of both fungi at different concentrations tested, and the pure essential oil (100%) presented fungicidal effect against B. cinerea. In vivo tests were carried out using grapes of Vitis spp. cv. “Isabella” and the concentrations of essential oil tested were efficient, reducing the incidence of disease caused by B. cinerea and C. acutatum at postharvest, both in preventive and curative treatment. The concentration 200 ppm completely inhibited the incidence of both fungi. In conclusion, F. vulgare essential oil presented fungicidal action against postharvest fungal rots on grapes.
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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) | 0.000 | 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 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".