Altitudinal Variation of Antioxidant Components and Capability in Indocalamus latifolius (Keng) McClure Leaf
Bibliographic record
Abstract
Indocalamus latifolius (Keng) McClure leaf is a popular food material in East Asia due to its antioxidant and anticorrosive activities. To utilize it more effectively, we investigated the discrepancy of antioxidant activities and active compound content in Indocalamus latifolius leaf along with the altitude change. Total flavonoids, phenolics, titerpenoids and eight characteristic active constituents, i.e, orientin, isoorientin, vitexin, homovitexin, p-coumaric acid, chlorogenic acid, caffeic acid, and ferulic acid, were determined by UV-spectrophotometer and synchronous RP-HPLC, respectively. Antioxidant activity was measured using DPPH and FRAP methods. Our data showed that the content of TP and TF, DPPH radical scavenging ability and ferric reduction power of Indocalamus latifolius leaf changed as altitude altered, with the trends of decreasing gradually when lower than 700 m and then increasing to 1,000 m. Chlorogenic acid and orientin were the main characteristic compounds in Indocalamus latifolius leaf and were also affected by altitude. Our result indicated that higher altitude with an adverse environment is conducive to secondary metabolite accumulation for Indocalamus latifolius. It would provide a theoretical basis to regulate the leaf collection conditions in the industrial use of Indocalamus latifolius leaf.
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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 | 0.000 |
| 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 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".