Effects of different fixation and drying methods on the quality of Dimocarpus longan scented tea
Bibliographic record
Abstract
Scented tea has been demonstrated to possess favourable pharmacological properties and exert a range of beneficial effects on human health. Longan flowers ( Dimocarpus longan ) are rich in nutrients and have a strong aroma; however, to date, no studies have reported the production of scented tea from longan flowers. The present study sought to investigate the impact of varying fixation and drying methods on the nutritional and antioxidant components of longan flowers. The findings indicated that, with the exception of free amino acids, the contents of other components in longan flowers were not affected by the different drying methods. Longan flowers subjected to steam fixation had higher average content of polyphenols and flavonoids, resulting in higher antioxidant and reducing power capacity. Therefore, this study examined the quality of longan scented tea prepared using different fixation and drying methods, promoted further processing of longan scented tea, and provided a reference to comprehensively utilize longan scented tea for benefiting human health. • Steam fixation had minimal impact on the nutritional components of longan flowers. • Steam fixation enhanced the content of antioxidant components and reducing power. • Different drying methods had little impact on longan scented tea process.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".