Physiological Evaluation of Korea Ginseng, Deoduk and Doragi Pickles
Bibliographic record
Abstract
Abstract The principal objective of this study was to conduct a physiological evaluation of Korea Ginseng, Deoduk and Doragi pickles. Prior to the processing of the 3 kinds of pickles, total phenolic acid contents, lecithin oxidation inhibitory effect, SOD -linked activity and hydroxyl radical scavenging activity of Korea Ginseng, Deoduk and Doragi water extracts were assessed. After the processing of 3 kinds of pickles, we conduct a sensory evaluation and color values assessment. The total phenolic acid contents of Korea Ginseng, Deoduk and Doragi water extracts were 1.66 ～ 1.70 ㎎/㎖, levels which were similar to that of tocopherol(1.81 ㎎/㎖) but significantly lower than that of BHT(4.06 ㎎/㎖)(p<0.05). The lecithin oxidation inhibitory effects of the Ginseng extract(98.86%) were similar to those of BHT(98.90%), but were significantly higher than those of Deoduk(35.70%), Doragi(78.07%) and tocopherol(65.91%). SOD-linked activity of Korea Ginseng water extract (42.58%) was similar to those of BHT(47.86%) and tocopherol(50.47%), but significantly higher than those of Deoduk (17.98%) and Doragi(20.75%). The hydroxyl radical scavenging activity of the Ginseng water extract(87.85%) was similar to that of BHT(8.58%), but significantly higher than that of Deoduk(79.51%), Doragi(77.62%) and tocopherol(78.95%). In the results of our sensory evaluations of the 3 kinds of pickles, the Ginseng pickle evidenced significantly lower acceptance scores in taste, color, flavor, texture, and overall quality. The luminance of the Ginseng pickle was significantly higher than the Deoduk pickles, the value of the Doragi pickle was significantly higher than those of the Ginseng and Deoduk pickles, and the b value of the Deoduk pickle was significantly higher than that of the Ginseng pickle. Key words: physiological evaluation, pickles, Ginseng, Deoduk, Doragi.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".