Relationship of fruit color and light exposure to lycopene content and antioxidant properties of tomato
Bibliographic record
Abstract
Tomato (Lycopersicon esculentum Mill.), a potent source of antioxidants in the diet, is characterized by remarkable genetic biodiversity, especially in fruit size and color. Horticultural practices and breeding efforts hold the potential to enhance antioxidant content in tomato fruit, but which antioxidants are most important? Lycopene content, total phenolic content, and radical scavenging capacity were examined in yellow, orange, red, and black-fruited tomato cultivars using lyophilized samples. Color was generally an accurate indicator of lycopene content, with a yellow cultivar containing less lycopene than red cultivars, and two of three red cultivars containing more than an orange cultivar. However, black cultivars as a group did not contain more lycopene than red. Tomato fruit harvested green-mature and exposed to 24 h light during ripening at 25°C in a growth cabinet had a higher lycopene concentration than green-mature fruit exposed for 8 h. 2,2'-azino-bis(3-ethylbenz-thiazoline-6-sulfonic acid (ABTS) radical scavenging activity did not vary among different colored cultivars, and was no different in stored (2 yr) or freshly prepared lyophilized samples. Total phenolic concentration was higher in orange, red, and black fruited cultivars than in yellow. Total phenolic concentration was lower in lyophilized powder samples of orange, red, and black cultivar fruit stored for 2 yr at -20°C relative to freshly prepared samples. Neither lycopene nor total phenolic concentration was well correlated to antioxidant capacity. Key words: High performance liquid chromatography, photoperiod
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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 | 0.000 |
| 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".