Comparative metabolomics reveals complex metabolic shifts associated with nitrogen-induced color development in mature pepper fruit
Bibliographic record
Abstract
Pigments derived from red pepper fruits are widely used in food and cosmetics as natural colorants. Nitrogen (N) is a key nutrient affecting plant growth and metabolism; however, its regulation of color-related metabolites in pepper fruit has not been fully elucidated. This study analyzed the effects of N supply (0, 250, and 400 kg N ha -1 ) on the growth, fruit skin color, and targeted and non-target secondary metabolites of field-grown pepper fruits at the mature red stage. Overall, 16 carotenoids were detected, of which capsanthin, zeaxanthin, and capsorubin were the dominant ones. N application at 250 kg ha -1 dramatically increased contents of red pigment capsanthin, yellow-orange zeaxanthin and β-carotene, with optimum fruit yield. A total of 290 secondary metabolites were detected and identified. The relative content of most flavonoids and phenolic acids was decreased with increasing N supply. Correlation analysis showed that color parameters were highly correlated with N application rates, carotenoids, flavonoids, phenolic acids, lignans, and coumarins. Collectively, N promoted carotenoid biosynthesis but downregulated phenylpropanoid and flavonoid biosynthesis, which together determined the spectrum of red color expression in pepper fruit. Our results provide a better understanding of the impact of N nutrition on pepper fruit color formation and related physiology, and identification of target metabolites for enhancement of nutritional quality and consumer appeal.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".