Use of Natural Antioxidants from Newfoundland Wild Berries to Improve the Shelf Life of Natural Herbal Soaps
Bibliographic record
Abstract
Antioxidants are important bio-regulators and suppressors of oxidation and are useful in enhancing the shelf life of consumer products. Formulated natural herbal soaps contain ingredients with antioxidant activities, but it is unknown how this influences shelf life. Herein, we evaluated whether natural additives or wild berry extracts were effective in improving the quality of natural herbal soaps. Three natural soaps, base bar (BB), forest grove (FG), and hibiscus rosehip (HR), were formulated using several wild berry extracts or natural additives and evaluated against similar commercial brands. The total phenolic content (TPC) of BB and FG infused with partridgeberry and HR with rosemary was 35.22, 44.72, and 33.26 µmole quercetin equivalent/g soap, while the total antioxidant activity (TAA) was 125.20, 119.23, and 126.94 µmole Trolox equivalent/g soap, respectively. Conversely, the commercial brand (BSG) with the highest TPC (56.24 µmole) contained lower TAA (59.68 µmole). As expected, the TPC and TAA of natural soaps were strongly correlated, and the majority (55-82%) of the polyunsaturated di/triacylglycerols remained unsaponified. Some extracts were inhibitory, while others promoted microbial growth. The results indicate that natural antioxidants from some Newfoundland wild berries have applications in improving the shelf life of natural herbal soaps, but care must be taken with the choice of berry used in the final soap formulation.
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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".