Expression of coffee florigen <i>CaFT1</i> reveals a sustained floral induction window associated with asynchronous flowering in tropical perennials
Bibliographic record
Abstract
Abstract The behavior of florigen(s) and environment-influenced regulatory pathways that control flowering in tropical perennials with complex phenological cycles is poorly understood. Understanding the mechanisms underlying this process is important for food production in the face of climate change. To explore this, homologs of Arabidopsis florigen FLOWERING LOCUS T ( CaFT1 ) and environment-related regulators CONSTANS ( CO ) , PHYTOCHROME INTERACTING FACTOR 4 ( PIF4 ) and FLOWERING LOCUS C ( FLC ) were isolated from Coffea sp. L. (Rubiaceae). Overexpression of CaFT1 in Arabidopsis showed typical early-flowering and yeast two hybrid studies indicated CaFT1 binding to bZIP floral regulator, FD, demonstrates that CaFT1 is a coffee orthologue of florigen. Expression of CaFT1 and floral regulators were evaluated over one year using three contrasting genotypes: two C. arabica and one C. canephora . All genotypes showed active CaFT1 transcription from February until October, indicating a potential window for floral induction. CaCO expression, as expected, varied over the day period and monthly with day length, whereas expression of temperature-responsive homologs, CaFLC and CaPIF4 , did not correlate with temperature changes. Using coffee as a model, we suggest a continuum of floral induction that allows different starting points for floral activation, which explains developmental asynchronicity and prolonged anthesis events in tropical perennial species. Highlight Coffee florigen CaFT1 and related regulators revealed an extended floral induction window clarifying the asynchronicity and influence of environment for flowering in tropical perennial crops, providing perspectives to its control.
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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".