Recent Progress in the Synergistic Bactericidal Effect of High Pressure and Temperature Processing in Fruits and Vegetables and Related Kinetics
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
BACKGROUND: Traditional thermal processing is a widely used method to ensure food safety. However, thermal processing leads to a significant decline in food quality, especially in the case of fruits and vegetables. To overcome this drawback, researchers are extensively exploring alternative non-thermal High-Pressure Processing (HPP) technology to ensure microbial safety and retaining the sensory and nutritional quality of food. However, HPP is unable to inactivate the spores of some pathogenic bacteria; thus, HPP in conjunction with moderate- and low-temperature is employed for inactivating the spores of harmful microorganisms. Scope and approach: In this paper, the inactivation effect of high-pressure and high-pressure thermal processing (HPTP) on harmful microorganisms in different food systems, along with the bactericidal kinetics model followed by HPP in certain food samples, have been reviewed. In addition, the effects of different factors such as microorganism species and growth stage, process parameters and pressurization mode, and food composition on microbial inactivation under the combined high-pressure and moderate/low-temperature treatment were discussed. KEY FINDINGS AND CONCLUSIONS: The establishment of a reliable bactericidal kinetic model and accurate prediction of microbial inactivation will be helpful for industrial design, development, and optimization of safe HPP and HPTP treatment conditions.
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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) | 0.001 | 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