Effect of degree of milling on the cadmium <i>in vitro</i> bioaccessibility in cooked rice
Bibliographic record
Abstract
Cadmium (Cd) contamination in rice grain is common worldwide. This study investigated the effect of degree of milling (DM) on the reduction of Cd in cooked rice grain and porridge (rice-to-water ratios 1:1.6 and 1:10, respectively) and Cd in vitro bioaccessibility. Cd-contaminated rice grains with DMs of 20%, 15%, and 0% were cooked and then subjected to successive digestion in a gastrointestinal environment model. Simulated-digestion juices, including saliva, gastric juice, duodenal juice, and bile juice, were used. The degree of gelatinization of cooked rice was measured and the morphological characteristics of the grain were also examined. The results showed that the Cd in vitro bioaccessibility, although less than 50% in all samples, was gradually increased with an increase of DM. The detected Cd bioaccessibility was higher at half meals (reduced grain content) when compared with full meals (full grain content). As DM increased, the surface of cooked rice grain and porridge became smoother, and the amount of fiber, fat droplets, and starch granules were gradually decreased, whereas degree of gelatinization increased. The results indicate that DM affects the Cd in vitro bioaccessibility in cooked rice by altering the gelatinization of starch. PRACTICAL APPLICATION: Degree of milling (DM) significantly influenced the in vitro bioaccessibility of cadmium (Cd) in cooked rice. This work may offer a potential solution to the rice grain with high Cd content because a limited DM will allow a low bioaccessibility of Cd.
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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".