Effect of Eugenol, Vanillin, and β-Resorcylic Acid on Foodborne Pathogen Survival in Marinated Camel Meat
Bibliographic record
Abstract
The combined inhibitory effect of essential oils (EOs) with meat-based marinades has not been fully studied. Therefore, the present study aimed to gauge the effect of a yogurt-based marinade when individually combined with three EOs, namely eugenol (EU), vanillin (VA), or β-resorcylic acid (BR) on camel meat cubes inoculated with Listeria monocytogenes, Salmonella spp., and Escherichia coli O157:H7 during storage. Fresh camel meat cubes of 10 g were inoculated with bacteria and dipped in the mixture of marinade and EO. Overall, the study had six EO treatments (EU 0.5%, EU 1%, VA 0.5%, VA 1%, BR 0.5%, and BR 1%) and two controls (meat without marinade and marinated meat). Treated meat cubes were stored at 4°C or 10°C for 1, 4, and 7 d. Adding only marinade to the camel meat at 10°C decreased the pathogens by 0.8-2.4 log CFU/g. At 10°C, BR decreased L. monocytogenes, E. coli O157:H7, and Salmonella spp. by 2.0, 1.5, and 1.3 log CFU/g, while EU caused a decrease (p < 0.05) of 1.9, 1.2, and 0.9 log CFU/g, respectively. Similarly, VA caused a reduction in these microorganisms of 1.3, 1.1, and 1.0 log CFU/g, respectively (p < 0.05). The combination of marinade and EO resulted in a decrease of the pathogens ranging from 0.9-1.4 and 2.8-3.7 log CFU/g at 4 and 10°C, respectively. The antimicrobial efficacy of EO alone or when combined with marinade was higher at 10°C than at 4°C with all three pathogens at both 0.5% and 1%. Overall, EOs were found to enhance the microbial safety of camel meat. In addition, they are antimicrobials that occur naturally, require a minimum investment, and may prove to be a great asset for marinated camel meat producers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 teacher head, 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".