Seed dormancy in <i>Camellia sinensis</i> L. (Theaceae): effects of cold-stratification and exogenous gibberellic acid application on germination
Bibliographic record
Abstract
There are several different opinions regarding dormancy in tea (Camellia sinensis L.), but there is no strong evidence available to conclude whether or not these seeds are dormant. Freshly matured tea seeds collected from Hangzhou, China, at the natural dispersal time did not germinate in light at daily alternative temperature regimes of 10/15, 15/20, 20/25, or 25/35 °C, or at a constant temperature of 25 °C. Seeds were permeable to water and the embryos did not grow prior to radicle emergence, thus, the seeds have no physical, morphological, or morphophysiological dormancy. When cold-stratified at 4 °C for 1, 2, and 3 months, 64%, 88%, and 93% of the seeds germinated, respectively. Intact fresh seeds failed to germinate after treatment with 0, 10, 500, and 1000 ppm GA3, whereas 3%, 4%, 61%, and 86% of cracked seeds germinated, respectively. Thus, the seeds have nondeep and intermediate physiological dormancy. Seeds cold-stratified for 2 months that were buried at soil depths of 0, 1, and 5 cm in pots showed that seeds at 1 cm depth established significantly higher number of seedlings (P < 0.05) than at other two depths. Because tea seeds are susceptible to summer temperature drying, these seeds do not establish a persistent seed bank.
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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 | 0.001 |
| 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".