Antifungal activities of different essential oils against anise seeds mycopopulations
Bibliographic record
Abstract
The aim of this study was to investigate the possibility of biological control of fungal species isolated from anise seeds using essential oils from medicinal plants: mint (Mentha spicata L.), sage (Salvia fruticosa L.), rosemary (Rosmarinus officinalis L.), anise (Pimpinella anisum L.), bitter fennel (Foeniculum vulgare spp. piperituum L.) and myrtle (Myrtus communis L.). Ten fungal species isolated from anise seeds: Bipolaris/Drechslera sorociniana, Fusarium subglutinans, F. vertricilioides, F. oxysporum, F. tricinctum, F. sporotrichioides, F. equiseti, F. incarnatum, F. proliferatum and Macrophomina phaseolina, were used in this experiment. The minimum inhibitory concentrations (MIC) were determined by micro-dilution method using selected essential oils (EOs). A qualitative and quantitative chemical analyses of EOs were carried out. All EOs exhibited a significant antifungal activity against all tested fungal isolates. The myrtle EO proved to be the most potent one (MIC 0.0003–3.25 mg/mL, then mint 0.0003–7.75 mg/mL and sage 0.0003–10 mg/mL). All tested fungi were observed to have a susceptibility to all selected essential oils. These results suggest the possibility for application of the EOs in biological control of anise production.
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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".