Influence of Seasonal and Yearly Variation on Phenolic Profiles, Caffeine, and Antioxidant Activities of Green Tea (Camellia sinensis (L.) Kuntze) from Azores
Bibliographic record
Abstract
This study compares the antioxidant properties (RSADPPH–DPPH radical scavenging activity, FRAP–ferric reducing activity power, and FIC–ferrous ion-chelating activity), the total phenolics (TP), total flavonoids (TF), and catechin profiles, as well as the caffeine content of Azorean Camellia sinensis green tea collected in seasons of two different years. The RSADPPH showed some variation between 2019 and 2020, and presented, in general, better results in 2020 as well as during the summer seasons. The FRAP was also noted to be at its highest in July and August of the two investigated years (6.64 and 6.40 µg/mL in 2019 and 5.85 and 5.46 µg/mL in 2020). According to FIC activity, the August 2019 sample exhibited the highest value (76.18%). The TP varied between 291.14 and 326.93 mg gallic acid equivalents (GAE)/g of dried extract (DE) in 2019 and between 300.25 and 320.58 mg GAE/g DE in 2020. Concerning the TF, the values varied between 51.85 and 67.93 mg rutin equivalents (RE)/g DE in 2019 and between 50.27 and 69.57 mg RE/g DE in 2020. Epicatechins derivatives, determined by HPLC, presented higher values in all samples from 2020 compared to 2019, and the same was observed for esterified catechins. The epigallocatechin-3-gallate content was also higher in all samples from 2020 (214.52–240.16 mg/g DE) compared to 2019 (140.91–210.83 mg/g DE). Regarding caffeine content (12.86–20.45 mg/g DE in 2019 and 13.19–29.35 mg/g DE in 2020), the samples from April and June exhibited similar values in both years. In general, green tea samples exhibited better results in 2020 than in 2019, with the exception of FIC activity, while the varied TP and TF contents in certain months reflect the impact of climatic variation on tea quality.
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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 | 0.000 | 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 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".