An Untargeted Metabolomics Approach for Correlating Pulse Crop Seed Coat Polyphenol Profiles with Antioxidant Capacity and Iron Chelation Ability
Bibliographic record
Abstract
Pulse crop seed coats are a sustainable source of antioxidant polyphenols, but are typically treated as low-value products, partly because some polyphenols reduce iron bioavailability in humans. This study correlates antioxidant/iron chelation capabilities of diverse seed coat types from five major pulse crops (common bean, lentil, pea, chickpea and faba bean) with polyphenol composition using mass spectrometry. Untargeted metabolomics was used to identify key differences and a hierarchical analysis revealed that common beans had the most diverse polyphenol profiles among these pulse crops. The highest antioxidant capacities were found in seed coats of black bean and all tannin lentils, followed by maple pea, however, tannin lentils showed much lower iron chelation among these seed coats. Thus, tannin lentils are more desirable sources as natural antioxidants in food applications, whereas black bean and maple pea are more suitable sources for industrial applications. Regardless of pulse crop, proanthocyanidins were primary contributors to antioxidant capacity, and to a lesser extent, anthocyanins and flavan-3-ols, whereas glycosylated flavonols contributed minimally. Higher iron chelation was primarily attributed to proanthocyanidin composition, and also myricetin 3-O-glucoside in black bean. Seed coats having proanthocyanidins that are primarily prodelphinidins show higher iron chelation compared with those containing procyanidins and/or propelargonidins.
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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 | 0.000 | 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) | 0.000 | 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".