B vitamin quantification in lentil seed tissues using ultra-performance liquid chromatography-selected reaction monitoring mass spectrometry
Bibliographic record
Abstract
Abstract Lentils are an important source of macronutrients, including protein and fiber, as well as micronutrients such as vitamins and minerals, especially in a plant-based diet. Quantifying variation among genotypes, including wild germplasm, is desirable to better understand the genetics of differential B vitamins content for breeding of this trait and to understand their potential contributions to the lentil crop. We analyzed thirty-four cultivated and three wild genotypes for vitamins B1, B2, B3, B5, B6, B7, and B9. Seeds were assayed whole, and separated into cotyledons only, or seed coats only. Variation for all B vitamins was observed across the cultivars. Overall, cotyledons had higher concentrations of B1 and B3, while seed coats had higher concentrations of B2, B5, B6, and B9. Wild accessions had the highest concentrations of vitamin B9 and were also among the highest for vitamin B2. These results demonstrate the differential distribution of B vitamins across seed tissues and lentil genotypes, and that dehulling prior to consumption results in the loss of B vitamins otherwise available in whole seeds. They also indicate there is genetic variability which could be used to increase B-vitamin levels in lentil via breeding.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".