Extraction, Chemical Composition, Antiradical Capacity, and Photoprotective Effect of Inonotus obliquus from Eastern Canada
Bibliographic record
Abstract
To promote the rational use of Inonotus obliquus (chaga) from Eastern Canada, a mushroom consumed in infusion as a health drink, the extraction of its constituents was investigated. The extraction was carried out with water or ethanol at room temperature or by heating as well as following exposure to ultrasound. The extracts of the four seasons obtained with the four extraction methods were compared for their contents in carbon, nitrogen (N), sulfur (S), potassium (K), betulin, betulinic acid, potassium, flavonoids, and polyphenols. The antiradical effect as well as the photoprotective effects of all extracts were also investigated. The results show that there is no difference between the quantities extracted from the extracts of the 4 seasons. The results show a significant difference between the mass of the extracts obtained with water and ethanol. Betulinic acid was found to be more abundant in the extracts obtained with water while betulin was more abundant in the extracts obtained with ethanol. The mushroom and the extracts had high C contents, but low N and S contents, typical of protein-poor and carbohydrate-rich materials. Extracts were particularly rich in potassium, five times more than bananas. Heating favors the extraction of polyphenols and flavonoids. The aqueous extracts of chaga harvested in winter had the highest antiradical capacity. With a Sun Protection Factor (SPF) higher than 30 in the UVB wavelength, chaga extracts might be used as sunscreen. Extracts obtained with water had the highest SPF in general. The analysis of this mushroom further highlights this local product that deserves more attention for its potential benefits as a functional food/nutraceutical product. In addition to its nutritional values, this mushroom can also be used for its cosmetic qualities as it can be used as a sunscreen.
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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 | 0.000 | 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 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".