Porosity Changes and Retention of Ginsenosides in North American Ginseng Root Using Different Dehydration Processes
Bibliographic record
Abstract
Air drying (AD), freeze-drying (FD), and vacuum-microwave drying (VMD) were applied to fresh North American ginseng roots to evaluate the effect of different drying techniques on pore characteristics and the subsequent recovery of ginsenoside content. FD ginseng root produced the lowest reductions in both total moisture content and water activity (P < 0.05), with no differences noted between Ontario or British Columbia ginseng. Ginseng roots from Ontario and British Columbia sources were therefore pooled to conduct the root porosity and ginsenoside measurements. Among samples, FD ginseng obtained the highest total porosity followed by VMD and AD, respectively (P < 0.05). All dehydrated samples had a porous structure with sizes that ranged from 0.002 μm to 172 μm, dominated by macropores (>1.5 μm). Pore characteristics of dried ginseng root were shown to affect recovery of ginsenosides, with the general trend being an increase in total porosity resulting in an increase in total ginsenoside recovered. High performance liquid chromatography results obtained on specific ginsenosides showed that AD of ginseng root resulted in the lowest recovery of total ginsenosides, most notably, Rg1 and Rb1, followed by VMD and FD, respectively. There was no specific difference in total ginsenoside recovery from roots dried at increasing power of VMD.
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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) | 0.000 | 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 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".