A comparative study of the nutritional values, volatiles compounds, and sensory qualities of pea pastes cooked in iron pot and clay pot
Bibliographic record
Abstract
In the current study, the nutritional values, volatiles compounds, and sensory qualities of pea pastes cooked in iron pot and clay pot were compared. Results showed that the iron pot-cooked pea pastes contained profoundly more iron, total sugar, and starch than the clay pot-cooked ones, and the effects were found related to iron ion by comparing the results between clay pot-cooked pastes with and without iron ion addition. Samples prepared with the two utensils demonstrated similar contents of protein, polyphenol, and tannin, but differed in the composition of some volatile alcohols, alkanes, aldehydes, ketones, esters, and organic acids. The clay pot-cooked samples had higher score of “color,” “mouthfeel,” “taste,” and “overall quality” than the iron pot-cooked pastes. In conclusion, iron pot can allow the production of iron-enriched pea pastes whose sensory qualities are remarkably lower than those of the clay pot-cooked samples but are still in the acceptable range. Practical applications Iron utensil plays an important role in modern food industry due to its durability and convenience to handle. Cooking with iron pot is a simple and useful method of dietary iron fortification for the prevention of iron-deficiency anemia in developing countries. Pea paste is a popular legume food with high nutritional value and good palatability. Traditional pea paste producers believe cooking with clay pots can give rise to product with more desirable features than using iron pots. However, there were no scientific evidences regarding the effects of cooking utensils on pea paste qualities. It has been proved in the current study that iron pot can allow the production of iron-enriched pea pastes whose sensory qualities are remarkably lower than those of the clay pot-cooked samples but are still in acceptable range.
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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) | 0.001 | 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".