Pollen germination and hand pollination in pitaya (Selenicereus spp.)
Bibliographic record
Abstract
Hand pollination is a necessary assisting method for pitaya (Selenicereus spp.) production to achieve a high yield. With the cultivated area increasing at an exponential rate in recent years, a comprehensive study of the pollination process was conducted. We developed an ideal medium for pitaya pollen in vitro germination in this study, then tested the activity of pollen collected from or stored for various time periods. We discovered that those collected between 2 h before blooming and 6 h after blooming had the higher germination rates (27.2–65.1%), the highest activity was at 2 h after blooming, and that storing them at 4°C for 24 hours reduces their germination rate from 65.2 percent to 35.5 percent and their production to about 82%. As a result, pollinating plants with pollen that has been held for more than 24 hours is not recommended unless a breakthrough in pollen storage is achieved. We also discovered that stigma receptivity and pollen activity are synchronized, which together determines the rate of fruit setting and the size of the fruit. Pollination within 6 hours after flowering offers the optimum fruit setting percentage and size, while pollination at 6:00 pm, 2 hours before blooming, is also a good alternative; however, pollination at 6:00 am the next morning is expected to result in a 23 % drop in productivity. These findings will be beneficial for reproductive biology research, as well as laying the groundwork for hand pollination to boost pitaya output and breeding efficiency.
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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".