Impact of Three Different Dehydration Methods on Nutritional Values and Sensory Quality of Dried Broccoli, Oranges, and Carrots
Bibliographic record
Abstract
Radiant Energy Vacuum (REV)-dried broccoli, oranges, and carrots prepared by the optimal drying protocols determined in this study were compared to the freeze-dried and air-dried samples based on the nutritional values before and after drying. An accelerated shelf-life study for REV-dried broccoli, oranges, and carrots was also conducted. For all the samples, REV drying significantly shortened the processing time. The REV-dried samples had much higher retention of the nutritional values (vitamin C, β-carotene) compared to the conventional air-drying process, and the values were also competitive to those of the freeze-dried samples. Although freeze-drying resulted in the best rehydration property, the REV-dried samples still earned the highest scores in the sensory test. In the accelerated shelf-life study conducted on the REV-dried samples, the moisture content and water activity stayed at the same level, but the nutritional values showed a downward trend. The sensory properties fluctuated in the shelf-life but still gained positive feedback from the panelists. Moreover, the testing method for β-carotene content was uniquely designed in this project and could be a semi-quantitative method to refer to.
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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) | 0.001 | 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 | 0.001 |
| 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".