Level of Acrylamide Precursors Asparagine, Fructose, Glucose, and Sucrose in Potatoes Sold at Retail in Italy and in the United States
Bibliographic record
Abstract
ABSTRACT The free amino acid asparagine and the reducing sugars glucose and fructose has been reported to serve as precursors for the heat‐induced formation of potentially toxic acrylamide in a variety of plant‐based food. To contribute to our knowledge about the levels of these precursors, we used ion‐exchange chromatography to measure free asparagine and high‐performance liquid chromatography (HPLC) to measure free glucose, fructose, and sucrose in 9 potato varieties sold at retail in Italy and in 22 varieties sold in the United States. Asparagine levels (in mmol/kg of fresh wt) ranged from 1.17 for the Agata potatoes to 57.65 Russet potatoes, a 49.3‐fold variation from lowest to highest value. The corresponding levels for fructose ranged from 1.73 (Fingerling Ozette) to 33.63 (Red), a 19.4‐fold variation from the lowest to the highest value. For glucose, the concentration ranged from 1.11 (Jelli) to 34.73 (Yukon Gold B) potatoes, a 31.3‐fold variation from lowest to highest value. The corresponding values for sucrose ranged from 1.16 (Fingerling Ozette) to 40.61 (Marabel) potatoes, a 35fold variation. The American potato varieties Kennebec, White, and Fingerling Ozette and the Italian potato varieties Agria, Merit, and Marabel had very low levels of both asparagine and reducing sugars. The results may enable consumers, restaurants, and processors to select commercial potatoes with low levels of acrylamide precursors for baking or frying.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".