Comparative effects of dielectric barrier discharge atmospheric cold plasma and thermal pasteurization on mandarin juice safety and quality during storage
Why this work is in the frame
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Bibliographic record
Abstract
This study systematically evaluated the effects of thermal pasteurization (TP) and dielectric barrier discharge atmospheric cold plasma (DBD ACP) on microbial inactivation, nutritional composition, enzymatic activity, and sensory attributes of fresh mandarin juice during 18 days of storage at 4 °C. TP was applied at 95 °C for 60 s, while DBD ACP treatments were conducted for durations ranging from 30 to 120 s. TP effectively inactivated spoilage microorganisms and quality-degrading enzymes, reducing microbial counts to acceptable levels and enzymatic activities (polyphenol oxidase and pectin methylesterase) to below 20%. However, TP significantly compromised nutritional quality, with notable reductions in ascorbic acid (26%), total phenolics, and antioxidant capacity. Additionally, TP negatively impacted sensory properties, inducing heat-related pigment degradation and the development of off-flavors. In contrast, DBD ACP treatments, particularly at 30–60 s, preserved ascorbic acid, phenolic content, and antioxidant activity, maintaining values statistically similar to those of the untreated juice samples. The 120-s DBD ACP treatment achieved microbial reduction comparable to TP (total plate count: 3.30 log CFU/mL; yeast and molds: 2.40 log CFU/mL), but demonstrated limited efficacy in enzyme inactivation, with residual enzyme activities exceeding 80%. Sensory evaluation indicated that DBD ACP-preserved juice retained its color, aroma, flavor, and taste, with scores closely aligned with those of the control sample. Results suggest that while DBD ACP is effective in preserving nutritional and sensory quality, its limited ability to inactivate enzymes may necessitate a combination with other preservation methods. Overall, DBD ACP represents a promising non-thermal processing technology for the safety and preservation of fresh fruit juices.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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