Antimicrobial efficacy of cinnamon, ginger, horseradish and nutmeg extracts against spoilage pathogens
Bibliographic record
Abstract
In the search for alternatives to the use of synthetic fungicides, aqueous spice extracts were evaluated for their effects on the mycelial growth of various spoilage pathogens and their ability to control potato dry rot and carrot cavity spot in vivo. Results showed that cinnamon, ginger and nutmeg significantly inhibited the mycelial growth of Aspergillus niger (Ascomycota), Fusarium sambucinum (Ascomycota), Pythium sulcatum (Oomycota) or Rhizopus stolonifer (Zygomycota), whereas horseradish extract did not lead to the inhibition of any microorganism at the tested concentration. Among the most effective extracts, 0.05 g mL‑1 of cinnamon extract completely inhibited A. niger and P. sulcatum, and 0.10 g mL‑1 of cinnamon extract completely inhibited F. sambucinum. A concentration of 0.05 g mL‑1 of ginger extract also caused 100% inhibition of P. sulcatum. In vivo, cinnamon extract significantly reduced lesions of potato dry rot and carrot cavity spot, and ginger extract reduced lesions of carrot cavity spot. These results indicate that aqueous cinnamon and ginger extracts could provide an alternative to the use of synthetic fungicides to control these pathogens.
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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) | 0.001 | 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".