Glycoalkaloid Development during Greening of Fresh Market Potatoes (<i>Solanum tuberosum</i> L.)
Bibliographic record
Abstract
Chlorophyll and glycoalkaloid synthesis in potato (Solanum tuberosum L.) tubers occur in direct response to light. The two processes are concurrent, but independent. Color photographic indices to subjectively grade fresh market potatoes for the extent of greening were developed under lighting conditions consistent with those of retail markets. Total glycoalkaloid (TGA) and chlorophyll accumulation for four cultivars were determined over the respective greening scales, thus calibrating the scales for TGA content. On average, TGA concentrations in complete longitudinal sections of tubers (flesh samples) were highest in Dark Red Norland followed by Russet Norkotah, Yukon Gold, and White Rose. TGA concentrations of flesh samples of White Rose and Yukon Gold tubers were somewhat variable and did not increase in direct proportion to greening level and chlorophyll content, particularly at higher levels of greening. TGA concentrations in Dark Red Norland and Russet Norkotah tubers were highly correlated (P < or = 0.001) with greening level and chlorophyll concentrations. When averaged over greening levels, skin samples contained 3.4- to 6.8-fold higher concentrations of TGAs than flesh samples, depending on the cultivar. The TGA concentration in periderm samples ranged from 37 to 160 mg/100 g of dry wt. Regardless of greening level, concentrations of TGAs in the flesh samples (including attached periderm) remained within limits presumed safe for human consumption. Discrimination of greened tubers on the basis of perceived glycoalkaloid toxicity is likely unfounded for the cultivars and greening levels studied.
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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) | 0.000 | 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 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".