Characterization of Changes in Polyphenols, Antioxidant Capacity and Physico-Chemical Parameters during Lowbush Blueberry Fruit Ripening
Why this work is in the frame
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Bibliographic record
Abstract
Changes in major polyphenols, antioxidant capacity, and selected physico-chemical parameters were examined in lowbush blueberry during fruit ripening. Polyphenols (phenolic acids, flavonols, flavan-3-ols, and anthocyanins), density, soluble solid content, pH, titratable acidity, sugars, organic acids, and antioxidant capacity were determined in fruits of four maturities: green, pink/red, blue, and over-mature. Highest concentrations of flavonols, flavan-3-ols, and phenolic acids were in green fruits: 168 ± 107, 119 ± 29 and 543 ± 91 mg/100 g dry weight (DW) respectively. Highest anthocyanin levels were found in blue and over-mature fruits (1011-1060 mg/100 DW). Chlorogenic acid was the most abundant phenolic acid and quercetin-3-O-galactoside the most abundant flavonol in all maturities. Epicatechin was the most abundant flavan-3-ol in green fruits (80 ± 20 mg/100 DW), and catechin was the most abundant in other maturity stages. Increase of glucose and fructose and decrease of organic acids were observed during fruit ripening. Among six organic acids found, quinic acid (1.7-9.5 mg/100 mg DW) was the most abundant throughout the fruit ontogeny. Soluble solids, pH, and density increased with maturity while, titratable acidity decreased. These findings can be helpful in optimizing harvest and processing operations in lowbush blueberry fruits.
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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 | 0.000 |
| 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