Bacteriological Quality of Salads Sold at Selected Restaurants in Accra, Ghana
Bibliographic record
Abstract
Background: The increasing prevalence of chronic non-communicable diseases has led to a greater emphasis on the consumption of healthy foods, such as vegetables. Vegetable salads from restaurants are generally perceived as safe. We investigated the bacteriological quality of vegetable salads sold in two popular restaurants in Accra. Methods: Twenty salad samples were purchased from two popular restaurants (A and B) with two branches each in Accra, Ghana. Restaurant A had branches at Dansoman and North Industrial Area, while B had branches at Osu and Tesano. Total aerobic colony forming unit (CFU) and biochemical assays were performed by standard culture techniques and protocols, to determine the microbial load and species present. Results: Mean aerobic bacteria count was 1.77E5 and 1.45 E5 CFU/g for Restaurants A, and B respectively. The North Industrial Area branch of A had more CFUs (2.64E5 CFU/g) than the Dansoman branch (0.9E5 CFU/g), and statistically significant (p=0.0010). The Tesano branch of restaurant B had higher CFUs (1.9E5 CFU/g) than the Osu branch (1.0E5 CFU/g), and also statistically significant (p=0.0022). Furthermore, ANOVA across the four branches showed a significant difference (p<0.0001). The main isolates identified from both restaurants were Enterobacter spp. (28.7%), Citrobacter spp. (20.4%), Klebsiella ssp. (18.5%) and Enterococcus spp. (7.4%). Conclusion: Enterobacter species was predominant among others. Education of the restaurant staff, and the application of food safety and handling procedures must be established, and food regulatory institutions must carry out routine inspection at these sites to ensure consumer protection and public health.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".