Evaluation of antimicrobial activities of commercial herb and spice extracts against selected food-borne bacteria
Bibliographic record
Abstract
The aim of this study was to evaluate and compare the antimicrobial properties of extracts of thirty commercial herbs and spices commonly used in the production of ready meals. Various extracts of spices were evaluated for their antimicrobial activities against Escherichia coli, Listeria innocua, Staphylococcus aureus and Pseudomonas fluorescens using a microdilution broth method. Ethanol and hexane extracts of oregano, clove, sage, rosemary and celery showed relatively strong antimicrobial activities against all bacteria tested. In contrast, water extracts displayed little or no antimicrobial activity. Flow cytometry revealed that cell membrane structures were damaged by spice and herb active extracts, while analysis of intra- and extracellular ATP contents of bacteria indicated that an increase in extracellular ATP was partially due to intracellular leakage. Extract combinations assessed using the checkerboard method did not display synergistic effects, however, some additive effects were observed when oregano was combined with sage or rosemary against L. innocua or S. aureus. This study has demonstrated that some commercial spice extracts have antimicrobial activity against food-borne bacterial species and may be considered as potential antibacterial agents for addition to ready meals.
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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 | 0.001 | 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".