Assessment of Iron Bioavailability in Lentils: Identifying Commercial Harvests with High Fe Bioavailability
Bibliographic record
Abstract
Iron deficiency is the most prevalent nutrient deficiency in the world, a major cause of which is a lack of highly bioavailable dietary iron. Lentils (Lens culinaris) are a pulse crop consumed as a staple food world‐wide, and are higher in iron compared to other staple foods. We screened 28 commercial lentil lines already in use by growers in Saskatchewan, Canada for Fe concentration and relative Fe bioavailability using the in vitro digestion/Caco‐2 cell model. Fe concentration of the lentils ranged from 53.4 – 96.7 ppm Fe with 4 lines having greater than 85 ppm Fe. This indicates that some harvests are essentially biofortified, as values above 85 ppm are considered high in Fe. There were significant differences in relative Fe bioavailability among the 28 commercial lines as measured by the in vitro model. Dehulling the lentils, a practice most common for red lentils, significantly increases the Fe bioavailability. Iron concentration and Fe bioavailability were not correlated in this sample (r=−0.27, p=0.16). These results will be confirmed in vivo using a poultry model. The differences in Fe concentration and relative bioavailability appear to be genetically linked. As Canadian lentils are often exported to regions where Fe deficiency is high, this work represents a unique opportunity to conduct Fe biofortification using the tools of modern agriculture.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 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) | 0.000 | 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 teacher head, 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".