Repetitive vegetative propagation of first-year sea buckthorn (<i>Hippophae rhamnoides</i> L.) cuttings
Bibliographic record
Abstract
Sea buckthorn (Hippophae rhamnoides L.) is used in beverages, pharmaceuticals, cosmetic products, and animal feeds. Although sea buckthorn has been shown to be easy to propagate vegetatively, currently, there is little information on reliable techniques to vegetatively propagate the plant repetitively within a single year. To address this, three experiments were conducted to study whether season and chilling affected the successful rooting of cuttings. Four cultivars, ‘Chuskaya’, ‘Golden Rain’, ‘Lord’, and ‘Sunny’, were used in the season- and chilling-effect experiments. Hardwood and softwood cuttings from field-grown plants did not root from October to December. The percent of rooted cuttings in January was cultivar-dependent. The number and percent of rooted greenhouse-produced cuttings were significantly affected by length of chilling. Most cuttings were produced and the highest percent rooted when the plants chilled for at least 6 wk. ‘Lord’ had the most and ‘Golden Rain’ the least number of rooted cuttings. This study indicated that greenhouse-grown stock plants were a viable source of sea buckthorn cuttings for vegetative propagation. When combined with field-grown sources, it is possible to produce sea buckthorn planting material year-round.
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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) | 0.001 | 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".