Greenhouse Performance of Anemone and Ranunculus Under Northern Climates: Effects of Temperature, Vernalization, and Storage Organ Traits
Bibliographic record
Abstract
Optimizing the growing conditions of Anemone coronaria and Ranunculus asiaticus for cut-flower production under northern greenhouse conditions requires a better understanding of the environmental and cultivation practices influencing emergence, flowering, and flower quality. This study evaluated the effect of storage organ reuse, along with vernalization conditions, growth temperature, growing season, and planting method (in-ground vs. containers) on plant phenology and flower yield and quality. Flower quantity and quality were unaffected by storage organ age, confirming that these organs can be stored and reused the following season. Vernalization at temperatures of 7 °C or 10 °C advanced flowering compared to warmer vernalization in all cultivars, and increased flower yield compared to non-vernalization. Growth under cool conditions (15/10 °C day/night) extended the production period and improved floral quality by promoting longer stems and delaying senescence. Short to moderate photoperiods (11–13 h in the winter vs. 15 h in the spring) and low light intensity, typical of winter, promoted stem elongation and marketable flower yield, whereas increasing photoperiod and temperature in late spring shorten the flowering period. Ground beds provided cooler and more buffered soil conditions, improving flowering duration and yield compared to container-grown plants during springtime. These findings highlight the importance of integrating temperature management, vernalization, and tailored cultivation practices to enhance flower quality, prolong the production, and improve sustainability of cut-flower production under northern climates in both species.
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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".