Bibliographic record
Abstract
Lentil (Lens culinaris Medikus) is an annual cool-season legume with a variety of seed coat colours. Seed coat colour is an important grading factor that affects the market value of lentils. In lentil, two independent loci gray ground colour (Ggc) and tan ground colour (Tgc) determine the four basic seed coat background colours; brown (Ggc Tgc), gray (Ggc tgc), tan (ggc Tgc) and green (ggc tgc). The zero tannin locus (tan) is epistatic to the tgc locus, producing clear seed coats. Lentil is a good source of protein, carbohydrates, dietary fiber components, minerals, vitamins, and secondary metabolites that include phenolic compounds. Phenolic compounds produce different pigments in plants and bring health benefits to humans. The overall objective of this study was to determine the relationship between seed coat colour and phenolic compounds in lentil. In the first study, comparison of the phenolic profiles of four seed coat background colours in lentil (i.e., brown, gray, tan, and green) was performed using an optimized liquid chromatography-mass spectrometry (LC-MS) method. The results showed that for the levels of various phenolic compounds in lentil seeds varied with the seed coat colour. Specifically, seed coats of lentil genotypes carrying the homozygous recessive tgc allele (green and gray seed coats) had higher amounts of flavan-3-ols, proanthocyanidins, and some flavonols. In the second study, a comparison was made between the phenolic profiles of lentil seed coats that do not express the Tgc phenotype (genotype Tgc tan) and those that express Tgc (genotype Tgc Tan). The LC-MS analysis detected several compounds that were not influenced by tan, notably the phenolic acids, flavones, some flavonols, and some of dihydroflavonols. In contrast, myricetin, dihydromyricetin, and flavan-3-ols, and proanthocyanidin oligomers were detected only in Ggc Tgc Tan lines and therefore appear to be controlled by tan. The molecular analysis showed that tan is a basic-helixloop- helix (bHLH) transcription factor that could interact with the regulatory genes in the phenylpropanoid pathway for the enzymes flavonoid-3’,5’-hydroxylase (F3’5’H) and dihydroflavonol reductase (DFR). The third study measured the effect of long term storage on specific changes in phenolic compounds in lentil seeds. Increases in phenolic acids and flavones occur in green lentil seeds during storage, possibly because of the breakdown of more complex species into smaller subunits. More interestingly, a significant decrease in 27 flavan-3- ols and proanthocyanidins also occurs. Polymerization of flavan-3-ols and proanthocyanidins and their conjugation to cellular constituents could reduce their extractability and produce dark pigments in long stored lentil seeds. In conclusion, these studies determined that there is a relationship between phenolic compounds, specifically flavan-3-ols and proanthocyanidins, and seed coat colour genes tgc and tan in lentil. The findings of this study will help to develop future breeding strategies for lentil cultivars with aesthetic properties and nutritional benefits that appeal to consumers.
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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 | 0.001 |
| 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".