Impact of Harvest Month and Drying Process on the Nutritional and Bioactive Properties of Wild Palmaria palmata from Atlantic Canada
Bibliographic record
Abstract
from Quebec were harvested in October 2019 and June 2020, and dried (40 °C, ≃5 h) or stored as frozen controls (-80 °C). The chemical (lipids, proteins, ash, carbohydrates, fibers), mineral (I, K, Na, Ca, Mg, Fe), potential bioactive compound (carotenoids, polyphenols, β-carotene, α-tocopherol) compositions, and the in vitro antioxidant activity and angiotensin-converting enzyme (ACE) inhibition potential of water-soluble extracts were determined. The results suggested a more favorable macroalgae composition in June with a higher content of most nutrients, minerals, and bioactive compounds. October specimens were richer only in carbohydrates and carotenoids. No significant differences in antioxidant or anti-ACE inhibitory activities were found between the two harvest months. The drying process did not significantly impact the chemical and mineral compositions, resulting in only small variations. However, drying had negative impacts on polyphenols and anti-ACE activities in June, and on carotenoids in October. In addition, a concentration effect was observed for carotenoids, β-carotene and α-tocopherol in June. To provide macroalgae of the highest nutritional quality, the drying process for June specimens should be selected.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".