Postharvest melatonin treatment inhibited longan (<i>Dimocarpus</i><i>longan</i> Lour.) pericarp browning by increasing ROS scavenging ability and protecting cytomembrane integrity
Bibliographic record
Abstract
Abstract Postharvest melatonin treatments have been reported to improve the quality and storability, especially to inhibit browning in many fruits, but the effect had not been systematically investigated on longan fruit. In this study, the effect of 0.4 mM melatonin (MLT) dipping on the quality and pericarp browning of longan fruits stored at low temperature was investigated. The MLT treatment did not influence the TSS content of longan fruits but lead to increased lightness and h° value while decreased a* value of pericarp. More importantly, the treatment significantly delayed the increase in electrolyte leakage and malonaldehyde accumulation, inhibited the activities of polyphenol oxidase and peroxidase, and thus retarded pericarp browning. In addition, the treatment significantly inhibited the production of O2•− and H2O2 while promoted the accumulation of glutathione, flavonoids, and phenolics at earlier storage stages in longan pericarp. Interestingly, the activities of ascorbate peroxidase (APX) and superoxide dismutase (SOD) were significantly upregulated but activities of catalase were downregulated in the MLT‐treated longan pericarp. MLT treatment effectively enhanced APX and SOD activities, increased flavonoid, phenolics, and glutathione content, protected cytomembrane integrity, inhibited the production of O2•− and H2O2 and browning‐related enzymes, and thus delayed the longan pericarp browning.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.001 |
| 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".