Rutin treatment delays postharvest chilling injury in green pepper fruit by modulating antioxidant defense capacity
Bibliographic record
Abstract
Green peppers are highly susceptible to low-temperature stress during postharvest storage, leading to significant quality deterioration. This study aimed to elucidate the molecular mechanisms by which rutin treatment regulates metabolic pathways in green peppers under low-temperature stress. Metabolomics and transcriptomics analyses were employed to investigate the effects of rutin treatment on storage quality, reactive oxygen species (ROS) metabolism, and antioxidant levels in green peppers. Results indicated that rutin treatment maintained higher quality and firmness, suppressed increases in relative electrolyte leakage, O 2 •− production rate, and H 2 O 2 content, and mitigated chilling injury (CI). According to the transcriptomics and metabolomics analysis, a total of 4232 differentially expressed genes (DEGs) and 1929 differentially abundant metabolites (DAMs) were found to be enriched in peppers treated with rutin compared to the control group after 4 d of storage. The integrated analysis revealed that rutin treatment inhibited the occurrence of CI in green peppers by enhancing glutathione metabolism, carotenoid biosynthesis, and amino acid metabolism. Major genes and metabolites affected by rutin treatment included GGT , GPx , APX , RRM2 , CrtB , LUT5 , ABA1 , NCED , Nit4 , NOA1 , OAT , HDC , and glutathione, glutathione disulfide, dehydroascorbic acid, zeaxanthin, abscisic acid, abscisic acid glucose ester, aspartate, arginine, proline, and tyrosine. RT-qPCR verification confirmed the altered expression levels of critical genes such as GST , GPx , LUT5 , ABA1 , ASS1 , and OAT . These findings provide a theoretical basis for understanding CI regulation in green peppers and support the application of rutin in postharvest management of fruit and vegetables.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".