Shelf-life study of a vegetable-based juice prepared using a masticating juicer
Bibliographic record
Abstract

 Background Home juicing has seen a rise in popularity because it gives people an appetizing way to get their daily intake of fresh fruits and vegetables. The roles of proper refrigeration, pasteurization, and acidification are all important in regards to determining the shelf life of a freshly made juice. As the general public may not properly understand these implications, this could become a major concern for public health officials. Methods A vegetable-based juice, made with carrots, celery, apples and parsley was made using a masticating juicer. Two versions of the juice were made, one original and one acidified. The pH, total coliforms, and total bacterial levels were monitored in both versions of the juice over a fifteen-day period. Results Analyses were carried out with the two juice samples. The pH values of the two juices were significantly different (p = 0.0000). No statistically significant difference was found in either the total number of aerobic bacteria or coliforms in the acidified and original juices. The relationship between total bacterial count and pH in the both the acidified and neutral juices were statistically significant, r= 0.7659, p= 0.0098 and r=0.7334, p=0.0158, respectively. No statistically significant correlation was found between coliforms and pH. Conclusion Although it was expected that the acidified juice would have had a lower levels of bacterial growth, this research project failed to show this. The total bacterial levels in the acidified juice was greater than 106 CFU/g on Day 8 and the original juice was greater than 106 CFU/g on Day 10. Regardless of the pH, the safest and lowest bacterial levels will be right when the juice is made.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".