Profiling the Phenolic Compounds of the Four Major Seed Coat Types and Their Relation to Color Genes in Lentil
Bibliographic record
Abstract
Phenolic compounds can provide antioxidant health benefits for humans, and foods such as lentils can be valuable dietary sources of different subclasses of these secondary metabolites. This study used LC-MS analyses to compare the phenolic profiles of lentil genotypes with four seed coat background colors (green, gray, tan, and brown) and two cotyledon colors (red and yellow) grown at two locations. The mean area ratio per mg sample (MARS) values of various phenolic compounds in lentil seeds varied with the different seed coat colors conferred by specific genotypes. Seed coats of lentil genotypes with the homozygous recessive tgc allele (green and gray seed coats) had higher MARS values of flavan-3-ols, proanthocyanidins, and some flavonols. This suggests lentils featuring green and gray seed coats might be more promising as health-promoting foods.
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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".