Carotenoid Profiles of Potato Breeding Lines and Selected Cultivars
Bibliographic record
Abstract
Lutein and zeaxanthin are becoming established as carotenoids beneficial for protection against common age-associated eye diseases. Thus, 15 potato ( Solanum tuberosum subsp. tuberosum L.) breeding lines, cultivars Atlantic, Spunta, and Yukon Gold; and orange flesh OR-4 were surveyed for carotenoid profiles. Seven carotenoids, including violaxanthin, neoaxanthin, antheraxanthin, lutein, zeaxanthin, β-cryptoaxanthin, and β-carotene, were identified in the 19 genotypes. Violaxanthin and lutein were the prominent carotenoids detected in all genotypes studied. Neoaxanthin and antheraxanthin were found in 26% and 63% of the genotypes, respectively. β-Cryptoaxanthin, zeaxanthin, and β-carotene were found in only 5%, 10%, and 16% of the genotypes, respectively. Lutein varied from 19.8 to 119.0 μg·100 g -1 fresh weight across the 15 white- or yellow-flesh breeding lines. In contrast, zeaxanthin was detected at a low level in only one breeding line and at high level in OR-4. The three cultivars had profiles typical of yellow-flesh potatoes `Spunta' and `Yukon Gold'; while `Atlantic' had a typical white-flesh profile and a trace of zeaxanthin. The carotenoid baseline data established in this study provide information for activities to enhance potato for lutein and zeaxanthin.
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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 | 0.000 | 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".