Effect of Drying Kinetics, Volatile Components, Flavor Changes and Final Quality Attributes of Moslae herba during the Hot Air Thin-Layer Drying Process
Bibliographic record
Abstract
Moslae herba is considered to be a functional food ingredient or nutraceutical due to its rich bioactive components. The present research was carried out to investigate the effects of different temperatures (40 °C, 50 °C and 60 °C) on the drying characteristics, textural properties, bioactive compounds, flavor changes and final quality attributes of Moslae herba during the hot air-drying process. The results showed that the Midilli model could effectively simulate the drying process of Moslae herba. The effective moisture diffusivity ranged from 3.14 × 10−5 m2/s to 7.39 × 10−5 m2/s, and the activation energy was estimated to be 37.29 kJ/mol. Additionally, scanning electron microscopy (SEM) images of Moslae herba samples showed the shrinkage of the underlying epidermal layers and glandular trichomes. In total, 23 volatile compounds were detected in Moslae herba. Among them, the content of thymol increased from 28.29% in fresh samples to 56.75%, 55.86% and 55.62% in samples dried at temperatures of 40 °C, 50 °C and 60 °C, respectively, while the other two components, p-cymene and γ-terpinene, decreased with an increase in the temperature. Furthermore, both radar fingerprinting and principal component analysis (PCA) of the electronic nose (E-nose) showed that the flavor substances significantly altered during the drying process. Eventually, drying Moslae herba at 60 °C positively affected the retention of total phenolics, total flavonoids and the antioxidant capacity as compared with drying at 40 °C and 50 °C. The overall results elucidated that drying Moslae herba at the temperature of 60 °C efficiently enhanced the final quality by significantly reducing the drying time and maintaining the bioactive compounds.
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How this classification was reachedexpand
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) | 0.000 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".