Low Phytic Acid Lentils (Lens culinaris L.): A Potential Solution for Increased Micronutrient Bioavailability
Bibliographic record
Abstract
Phytic acid is an antinutrient present mainly in seeds of grain crops such as legumes and cereals. It has the potential to bind mineral micronutrients in food and reduce their bioavailability. This study analyzed the phytic acid concentration in seeds of 19 lentil ( Lens culinaris L.) genotypes grown at two locations for two years in Saskatchewan, Canada. The objectives of this study were to determine (1) the levels of phytic acid in commercial lentil genotypes and (2) the impact of postharvest processing and (3) the effect of boiling on the stability of phytic aid in selected lentil genotypes. The phytic acid was analyzed by high-performance anion exchange separation followed by conductivity detection. The Saskatchewan-grown lentils were naturally low in phytic acid (phytic acid = 2.5-4.4 mg g(-1); phytic acid phosphorus = 0.7-1.2 mg g(-1)), with concentrations lower than those reported for low phytic acid mutants of corn, wheat, common bean, and soybean. Decortication prior to cooking further reduced total phytic acid by >50%. As lowering phytic acid intake can lead to increased mineral bioavailability, dietary inclusion of Canadian lentils may have significant benefits in regions with widespread micronutrient malnutrition.
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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 | 0.001 | 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".