Light and Temperature Regulation of Flowering in <i>Rosa chinensis</i> under Controlled Cultivation
Bibliographic record
Abstract
Rosa chinensis serves as a model for studying floral transition in perennial woody ornamentals. This study explores how light and temperature regulate flowering patterns, floral quality, and genotype × environment interactions under controlled and field conditions. Molecular analysis shows that the Rc CO -Rc FT module and RcPIF -FLC-like axis integrate environmental cues, with RcPHYA , RcCRY2 , RcPIF4 , and RcHsfA6 acting through downstream regulators such as RcSOC1. Transcriptomic and epigenetic data confirm convergence of these networks, enabling synchronized flowering, while high temperature and short-day conditions disrupt activators. Phenotypic trials demonstrate that temperature and light shape floral morphology, longevity, and symmetry. A case study at the Royal Botanic Gardens Kew illustrates how precise environmental management ensures display value and conservation. The findings support breeding climate-resilient rose cultivars using marker-assisted selection, transcriptome-based screening, and CRISPR/Cas9 editing, providing practical strategies for sustainable cultivation, ornamental display, and adaptation to climate change.
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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".