Recent developments in applications of physical fields for microbial decontamination and enhancing nutritional properties of germinated edible seeds and sprouts: a review
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
Germinated edible seeds and sprouts have attracted consumers because of their nutritional values and health benefits. To ensure the microbial safety of the seed and sprout, emerging processing methods involving physical fields (PFs), having the characteristics of high efficiency and environmental safety, are increasingly proposed as effective decontamination processing technologies. This review summarizes recent progress on the application of PFs to germinating edible seeds, including their impact on microbial decontamination and nutritional quality and the associated influencing mechanisms in germination. The effectiveness, application scope, and limitation of the various physical techniques, including ultrasound, microwave, radio frequency, infrared heating, irradiation, pulsed light, plasma, and high-pressure processing, are symmetrically reviewed. Good application potential for improving seed germination and sprout growth is also described for promoting the accumulation of bioactive compounds in sprouts, and subsequently enhancing the antioxidant capacity under favorable PFs processing conditions. Moreover, the challenges and future directions of PFs in the application to germinated edible seeds are finally proposed. This review also attempts to provide an in-depth understanding of the effects of PFs on microbial safety and changes in nutritional properties of germinating edible seeds and a theoretical reference for the future development of PFs in processing safe sprouted seeds.
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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 | 0.001 |
| 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