The role of starch physicochemical properties in determining the Glycemic Index of potatoes
Bibliographic record
Abstract
Potatoes are a nutrient dense food, despite this, they are often thought of as unhealthy due to their purported high glycemic index (GI). Previously, we found a range of GI values for 8 different potato varieties when freshly cooked (range 52±4 to 81±9, p≤0.05) and that cooling cooked potatoes reduced GI by 20–50%. However, it is unclear if this effect can be seen in potatoes harvested in different years. Thus, the purpose of the present study was to examine the effect of variety and cooling on the GI of potatoes harvested in 2009 and 2010 and to assess the role of starch properties in determining GI. The GI of 4 potato varieties was tested in 10 healthy individuals using standard GI methodology. Each variety was consumed hot or cold (~2 days at 4°C). Cooling reduced GI by 11–54%. ANOVA showed an effect of variety and cooling (p≤0.05). Cooling significantly reduced GI in 1 variety 71±7 (hot) vs. 39±4 (cold) (p≤0.05). A positive relationship between the GI of potatoes harvested in 2009 and those harvested in 2010 was observed (R 2 =0.620, P=0.02). Studies suggest that these differences in GI between varieties and as a result of cooling may be due to a difference in their starch properties. To assess their role in GI, we measured the amounts of rapidly digestible (RDS), slowly digestible (SDS), and resistant starch (RS) in cooked potato. Contrary to some studies, RDS, SDS and RS did not explain the differences in GI we observed in the present study.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 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".