Chemical Profiling of Lentil (Lens culinaris Medik.) Cultivars and Isolation of Compounds
Bibliographic record
Abstract
A high-performance liquid chromatography method was developed to obtain fingerprints of secondary metabolites of 12 lentil cultivars grown under the same environmental condition. Extracts (100% methanol and methanol-water (1:1)) were analyzed by RP-HPLC. Full photodiode array (191-360 nm) data were collected and used for cluster analysis. Methanol and methanol-water extracts showed slightly different clustering patterns. In the dendogram of methanol extracts, CDC Richlea appeared as an isolated group, whereas Indianhead was the isolated group in methanol-water extracts. The cultivar CDC Milestone was selected for further evaluation because of the presence of three peaks (8.9, 16.7, and 32.7 min) that were absent in other cultivars or present in very small amounts. Chromatographic separations of the methanol extract afforded several compounds including the novel 4-chloro-1H-indole-3-N-methylacetamide (13) as well as itaconic acid (3), arbutin (5), gentisic acid 5-O-[beta-d-apiofuranosyl-(1-->2)-beta-d-xylopyranoside] (9), and (6S,7Z,9R)-9-hydroxymegastigma-4,7-dien-3-one-9-O-beta-d-apiofuranosyl-(1-->2)-beta-d-glucopyranoside (14), which are described for the first time from lentils. Structures were determined by high-resolution NMR experiments.
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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 | 0.001 | 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 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".