Effect of microwave and infrared drying over polyphenol content in <i>Vaccinium meridionale</i> (Swartz) dry leaves
Bibliographic record
Abstract
Abstract In the present work the drying of blueberry (mortiño) leaves (Vaccinium meridionale‐Swartz) was done using a hybrid equipment with infrared drying and normal microwave drying. During the drying tests there was a record of moisture content versus time; samples of leaves were taken during the drying time to analyze total phenol (PT) content, FRAP assay and catechin measures by HPLC‐DAD. The PT analysis shows that its content in dry blueberries, increased 12 times more with the microwave drying than infrarred drying. While FRAP assay shows that dry blueberries antioxidant capacity increased nine times more with microwave process in comparison to infrared process. In the catechins content by HPLC‐DAD in dry blueberries, a better result for concentration was found in microwave process than in infrared process. Similar result occurred for (−) epicatechin. Finally, (+) catechin concentrations in blueberry leaves were compared with commercial materials such as tea leaves and mate leaves. Practical applications The consumption of nutraceutical products rich in polyphenols has become important in the last decades. In this research, the effect of microwave and infrared drying on the content of polyphenols on blueberry leaves (Vaccinium meridionale, Swartz) was studied because it was found in previous studies that the leaves contain a potential of polyphenols that can be used to develop nutraceutical beverages similar to tea drinks.
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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".