Ellagic acid in strawberry (Fragaria spp.): Biological, technological, stability, and human health aspects
Bibliographic record
Abstract
Ellagic acid (EA) is one of the plant phenolics associated with human health benefits. It derives from ellagitannins found in some nuts, seeds, and fruits, especially berries. Strawberries are considered a functional food and nutraceutical source, mainly because of their high concentration of EA and its precursors. This review presents the current state of knowledge regarding EA, focusing on its content in strawberry plants, stability during processing and storage of strawberry-based foods, production methods, and relevance to human health. As alternatives to acid-solvent extraction, fermentation-enzymatic bioprocesses hold great promises for more eco-efficient production of EA from plant materials. Strawberry fruits are generally rich in EA, with large variations depending on cultivar, growth conditions and maturity at harvest. High EA contents are also reported in strawberry achenes and leaves, and in wild strawberries. Strawberry postharvest storage, processing and subsequent storage can influence EA content. EA low concentration in strawberry juice and wine can be increased by incorporating pre-treated achenes. Widespread recognition of strawberries as functional foods is substantiated by evidence of EA biological effects, including antioxidant, antiinflammatory, antidiabetic, cardioprotective, neuroprotective, and prebiotic effects. The health benefits attributed to EA-rich foods are thought to involve various protective mechanisms at the cellular level. Dietary EA is converted by the intestinal microbiota to urolithins, which are better absorbed than EA and may contribute significantly to the health effects attributed to EA-rich foods. Based on the evidence available, strawberry EA shows strong promises for functional, nutraceutical, and pharmaceutical applications. Future research should be directed at quantifying EA in different parts of the strawberry plant and in their byproducts; optimizing EA production from byproducts; understanding the biological actions of EA-derived metabolites in vivo, including the interactions between EA metabolites, other substances and food/biological matrices; characterizing the conditions and microorganisms involved in urolithin production; and developing delivery systems that enhance EA functionality and bioactivity.
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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 | 0.001 |
| 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".