Glycoalkaloid and Chlorophyll Changes in Eight Potato Varieties Exposed to Light
Bibliographic record
Abstract
Red and white skin potatoes (`Cal Red', `Cal White', `Durango', VC1015, `Yukon Gold', `Latona', A94381, and `Satina') were harvested from plots in commercial fields in Kern and San Joaquin Counties and at the Univ. California Research Center at Tulelake. After washing and sorting, potatoes were held in plastic trays in the dark (black plastic bags) or exposed to light (90 cm below cool-white fluorescent GE Watt-Miser 34W bulbs, ≈1300 lux) at 20 °C. After 0, 3, 6 and 9 days, potatoes were scored for appearance of greening (1 to 5 scale), evaluated for external color (L * a * b * color values), skin chlorophyll concentration, and glycoalkaloid concentrations. For the latter, freeze-dried slices of tuber were extracted and analyzed by colorimetry and HPLC for alpha-solanine and alpha-chaconine. Initial glycoalkaloid concentrations varied among cultivars, with `Cal Red' consistently having the highest concentrations. Tubers stored in the dark had no or a slight increase in glycoalkaloid concentrations. Light exposure resulted in increased glycoalkaloid concentrations in all cultivars, but to varying degrees. Some varieties had negligible changes while others increased as much as eightfold. The average increase was 300%. Generally, `Cal White' had the largest light-induced increases in glycoalkaloids.
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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".