Phytochemical Characterization of Commercial Processed Blueberry, Blackberry, Blackcurrant, Cranberry, and Raspberry and Their Antioxidant Activity
Why this work is in the frame
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Bibliographic record
Abstract
Being delicious and containing strong disease-fighting agents, berries represent an increasing proportion of fruits consumed nowadays in our diet. However, berries are highly perishable as fresh and, therefore, they are usually processed into various products to extend their shelf-life and availability throughout the year. Among the fruit-containing products, jam is one of the most common due to its nourishing properties, its low production costs, and its accessibility for a lengthy period. Rather than home preparation, consumers nowadays increasingly prefer to purchase commercial jams from markets due to its convenience. Although fresh berries have been extensively studied for their phenolic compounds, a limited number of studies investigating commercially manufactured jams have been conducted so far. Considering this, the objective of this study was to assess the total phenolic, flavonoid, and anthocyanin content and the antioxidant activity of five commonly consumed commercial berry jams (blueberry (Vaccinium myrtillus), blackberry (Rubus fruticosus) and blackcurrant (Ribes nigrun) mixture, blackcurrant (Ribes nigrun), cranberry (Vaccinium macrocarpon) and raspberry (Rubus idaeus)) collected from the market. Even though a possible loss of phenolics, anthocyanins, and a decrease of radical scavenging activity may occur during jam processing and subsequent storage, our data indicated that the selected commercial jams remained good sources of nutritive molecules with antioxidant properties based on the high levels of total phenolics, flavonoids, anthocyanins, and elevated antioxidant activities determined in this study. Additionally, the samples were characterized by GC-MS for their volatile profiles, and terpenes were found to be the dominating class covering more than 74% of volatile compounds in the jams.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it