Comparative Study on Phytochemical Profiles and Antioxidant Capacities of Chestnuts Produced in Different Geographic Area in China
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study aimed to systematically assess the phenolic profiles and antioxidant capacities of 21 chestnut samples collected from six geographical areas of China. All these samples exhibit significant differences (p < 0.05) in total phenolic contents (TPC), total flavonoids content (TFC), condensed tannin content (CTC) and antioxidant capacities assessed by DPPH free radical scavenging capacity (DPPH), ABTS free radical scavenging capacities (ABTS), ferric reducing antioxidant power (FRAP), and 14 free phenolic acids. Chestnuts collected from Fuzhou, Jiangxi (East China) exhibited the maximum values for TPC (2.35 mg GAE/g), CTC (13.52 mg CAE/g), DPPH (16.74 μmol TE/g), ABTS (24.83 μmol TE/g), FRAP assays (3.20 mmol FE/100 g), and total free phenolic acids (314.87 µg/g). Vanillin and gallic acids were found to be the most abundant free phenolic compounds among other 14 phenolic compounds detected by HPLC. Overall, the samples from South China revealed maximum mean values for TPC, CTC, DPPH, and ABTS assays. Among the three chestnut varieties, Banli presented prominent mean values for all the assays. These finding will be beneficial for production of novel functional food and developing high-quality chestnut varieties.
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.
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) | 0.001 | 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