Applications of radiation processing in combination with conventional treatments to assure food safety: New development
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Spice extracts under the form of essential oils (Eos) were tested for their efficiency to increase the relative bacterial radiosensitivity (RBR) of Listeria monocytogenes , Escherichia coli and Salmonella typhi in culture media under different atmospheric conditions. The selected Eos were tested for their ability to reduce the dose necessary to eliminate E. coli and S. typhi in medium fat ground beef (23% fat) and Listeria in ready-to-eat carrots when packed under air or under atmosphere rich in oxygen (MAP). Results have demonstrated that depending of the compound added and the combined treatment used, the RBR increased from 2 to 4 times. In order to evaluate the industrial feasibility, EOs were added in ground beef at a concentration which does not affect the taste and treated at a dose of 1.5 kGy. The content of total mesophilic aerobic, E. coli , Salmonella , total coliform, lactic acid bacteria , and Pseudomonas was determined during 28 days. The results showed that the combined treatment (radiation and EOs) can eliminate Salmonella and E. coli when done under air. When done under MAP , Pseudomonas could be eliminated and a shelf life of more than 28 days was observed. An active edible coating containing EOs was also developed and sprayed on ready-to-eat carrots before radiation treatment and Listeria was evaluated. A complete inhibition of Listeria was obtained at a dose of 0.5 kGy when applied under MAP. Our results have shown that the combination of an edible coating , MAP, and radiation can be used to maintain the safety of meat and vegetables.
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.
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 | 0.000 | 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 it