Effects of preharvest ultraviolet‐C irradiation on fruit phytochemical profiles and antioxidant capacity in three strawberry (<i>Fragaria</i> × <i>ananassa</i> Duch.) cultivars
Bibliographic record
Abstract
BACKGROUND: Ultraviolet-C (UV-C) has proven effective in extending shelf-life, reducing disease incidence and increasing the levels of health-promoting compounds in several crops. While most studies were conducted at the postharvest stage, our study examined the effect of preharvest UV-C application in three strawberry cultivars (Fragaria × ananassa Duch. 'Albion', 'Charlotte' and 'Seascape'). UV-C treatment was applied from the onset of flowering until the fruits reached commercial maturity on plants grown for two consecutive seasons under greenhouse conditions. The phytochemical profiles and antioxidant capacity of the fruits were assessed at harvest. RESULTS: The ellagic acid and kaempferol-3-glucuronide contents were significantly increased only in fruits of the cultivar 'Albion' collected from UV-C-treated plants in season 1. UV-C did not consistently affect the other phenolic compounds that were measured. Based on the results of the ferric-reducing antioxidant power, oxygen radical absorbance capacity and total phenolic content assays, the antioxidant capacity of the three strawberry cultivars was not affected by UV-C. Season and cultivar had a decisive impact on these parameters. CONCLUSION: The effect of preharvest UV-C on the levels of bioactive compounds in strawberry fruits appears to be cultivar- dependent, with season or growing conditions having a significant impact.
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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 | 0.000 | 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 | 0.001 |
| 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".