Impact on the Health-Promoting Potential of Cranberries for Food Applications Through Soilless Cultivation Practices in Piemonte Region (Italy): A Sustainable Opportunity for Nutraceutical Production
Bibliographic record
Abstract
Cranberry (Vaccinium macrocarpon Aiton), a traditional berry crop cultivated in North America, is appreciated for its high amounts of bioactive compounds and polyphenols. The exploration of its cultivation in different geographic areas may support crop diversification and sustainable production of fruits and derived products rich in health-promoting molecules. The present research evaluated the antioxidant capacity, phytochemical profile, and nutritive composition of the ‘Pilgrim’ cranberry cultivar grown in soilless conditions in Northwestern Italy (Bra, Piemonte Region), compared to a reference sample from North America (Canada). Physical–chemical parameters such as weight, fruit size, titratable acidity, and total soluble solids were considered. Additionally, anthocyanins, total phenolics, antioxidant capacity, and proanthocyanidins (PACs) were evaluated using spectrophotometric protocols. Chromatographic techniques (HPLC-MS/MS and HPLC-DAD) were used for detailed profiling of phenolic acids, flavonoids, vitamin C, sugars, organic acids, and PAC types (A- and B-type dimers and trimers). The results highlighted that Italian-grown cranberry fruits, although smaller, showed significantly higher levels of PACs (+61%), anthocyanins (+58%), total polyphenolic compounds (+48%), and antioxidant capacity than North American ones. This may be due to the inhibition of fruit growth by elevated temperatures, resulting in a better synthesis of antioxidants and bioactive compounds. This study may promote the cultivation of cranberries in different climatic regions, as a complementary strategy to international imports, and improve the production of new food applications with a high content of health-promoting molecules. Additionally, the production of antioxidants in plants under challenging conditions may potentially stimulate further studies to address climate change and investigate crop diversification.
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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 | 0.000 | 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".