Quantification of antioxidant capacity and phytonutrients in four Québec-grown potato cultivars
Bibliographic record
Abstract
Four Québec-grown potato (Solanum tuberosum L.) cultivars (cvs; Chieftain, Goldrush, Russet Burbank, and Yukon Gold) were examined for selected antioxidant indices and phytonutrient content. Cultivars showed significant variation in content of antioxidant indices, total soluble protein, and 2 of 9 minerals (copper and iron), in one serving (150 g fresh weight). Total antioxidant capacity was greatest in the cvs. Goldrush (pale yellow flesh) and Russet Burbank (white flesh). Cultivar Yukon Gold (yellow flesh) showed the greatest total carotenoids and total soluble protein. Cultivar Chieftain (white flesh) had the greatest caffeic acid and ferulic acid content and was similar to cv. Russet Burbank for greatest iron content. Cultivar Goldrush showed the greatest content of total phenolics, chlorogenic and ascorbic acids and was similar to cv. Chieftain for greatest rutin content. The cultivars varied in their dietary contribution to recommended dietary allowance of ascorbic acid, copper, and iron (on a per serving basis). All cultivars met the recommended dietary allowance of selenium on a per serving basis. Periderm (skin) of cultivars contributed significantly to certain antioxidants and phytonutrients in one serving, although this contribution of skin was cultivar-dependent. Potato skin can play an important role in increasing the dietary intake of specific antioxidants and phytonutrients. Consumers are advised to eat the entire tuber, including the skin. Dietary preference of one cultivar over another could result in significantly improved dietary intake of the above reported antioxidants and phytonutrients. Combinations of cultivars could also improve the nutrient composition of the diet. Selling potatoes under cultivar names would clearly help consumers make informed choices for dietary consumption.
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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 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".