A comparative metabolomics investigation of flavonoid variation in faba bean flowers
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Bibliographic record
Abstract
INTRODUCTION: Faba bean (Vicia faba L.) flowers are edible and used as garnishes because of their aroma, sweet flavor and attractive colors. Anthocyanins are the common plant pigments that give flowers their vivid colors, whereas non-anthocyanin flavonoids can serve as co-pigments that can modify the color intensity of flowers. OBJECTIVES: To explore the polyphenol diversity and differences in standard and wing petals of faba bean flowers; and identify glycosylated flavonoids that contribute to flower color. METHODS: Flower standard and wing petals from 30 faba bean genotypes (eight color groups with a total of 60 samples) were used for polyphenol extraction. Samples were analyzed using a targeted method and a semi-untargeted analysis using liquid chromatography-high resolution mass spectrometry (LC-HRMS) combined with photodiode array (PDA) detection. Compound Discoverer software was used for polyphenol identification and multivariate analysis. RESULTS: The semi-untargeted analysis guided by the PDA detected 90 flavonoid metabolites present in faba bean flower petals. Ten anthocyanins largely influenced the flower colors, but other flavonoids (63 flavonols and 12 flavones) found with variable levels in different flower color groups appeared to also influence color, especially in mixed colors. CONCLUSION: Analysis of the different colored faba bean flowers confirmed that the color variation between the flowers was mainly controlled by anthocyanins in brown, red and purple-red flowers. Of the other flavonoids, multiglycosylated kaempferols were abundant in white and brown flowers, monoglycosylated kaempferols were common in red and purple-red flowers, and quercetin and apigenin glycosides were abundant co-pigments in purple-red flowers.
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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 it