Mass Spectrometry-Based Untargeted Metabolomics Reveals the Importance of Glycosylated Flavones in Patterned Lentil Seed Coats
Bibliographic record
Abstract
Lentil seed coats are rich in antioxidant polyphenols that are important for plant defense and have potential as valorized byproducts. Although biochemical differences among lentil seed coat colors have been previously studied, differences among seed coat patterns remain largely unexplored. This study used mass spectrometry-based untargeted metabolomics to investigate polyphenol differences among lentil seed coat patterns to search for biochemical pathways potentially responsible for seed coat pattern differences. Comparing patterned with non-patterned green lentil seed coats, 28 significantly upregulated metabolites were found in patterned seed coats; 19 of them were identified as flavones. Flavones were virtually absent in non-patterned seed coats, thereby strongly suggesting a blockage in their flavone biosynthetic pathway. Although the black pattern is not readily discernible on black seed coats, many of the same flavones found in green marbled seed coats were also found in black seed coats, indicating that black seed coats likely have a marbled pattern.
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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".