Distinct stimuli-induced flowering: characterizing the hormonal and genetic regulation in day-neutral Fragaria species
Bibliographic record
Abstract
Strawberry cultivation is an important sector for the Québec horticulture industry in terms of revenue as it represents 47% of Canada’s total production. In Québec, strawberry producers face challenges such as shorter production periods and soilborne diseases that severely impact fruit production. To overcome existing challenges, day-neutral (DN) cultivars are increasingly grown in soilless media, which resulted in extended harvesting season and improved fruit yield. Despite the increasing use of DNs in Québec, very little work has been done on DN strawberry production under local conditions, thus, available information is very limited. In this project, we determined the effect of environmental stimuli that can stimulate flower bud induction (FBI) in the widely grown DN cultivar ‘Albion’ and evaluated the molecular and metabolic mechanism that controls the flowering. The FBI is considered as the most reliable and critical factor for the successful cultivation of the crop as it directly contributes to the qualitative and quantitative characteristics of strawberry fruit. Results demonstrated that low nitrogen (N) supply and long day (LD) photoperiod triggers the FBI process during the later stages in the growing season, while elevated N supply seems to enhance LD-induced effect on flower bud induction in DNs. Flowering in ‘Albion’ was unaffected under LD photoperiod when incandescent light was used as the predominant light source. Whereas flowering increased considerably under LD photoperiod supplied with light-emitting diodes (LEDs). The combination of two narrow-band light sources of far-red (FR) and blue (B) LEDs at a ratio of 1:5, also referred as dominant blue, significantly stimulated FBI and ensures healthy plant quality during transplant production. The supplementation of dominant blue LEDs coupled with LD photoperiod and night interruption amplifies the impact on flowering.Flowering in plants involves distinct molecular mechanisms and hormonal signaling. The flowering pathways have been extensively studied in seasonal strawberry. However, it is poorly understood in DN strawberry cultivars. To understand the mechanism for light quality control of flowering in DN cultivars, we have examined the transcript level of floral-related genes and concentration levels of plant hormones during the FBI process. The transcript level of flowering-related genes i.e., FvFT1 and FvTFL1 were recognized at a higher fold change under dominant blue LEDs, suggesting that both genes are involved in flowering in response to light quality, although, flowering seems to occur independently of FvTFL1. In contrast to ‘Albion’, ‘Alexandria’ displayed strong flowering inhibition in all the FR and B combinations when supplemented during night interruption. Our findings postulate that FR light-controlled phytochromes may be involved in the floral inhibition response in F. vesca through differential regulation of the FvFT1 transcription factor. Further, increased levels of gibberellins and cytokinin in the crown tissue seems to regulate FBI during transplant production in both woodland and cultivated strawberry. Our results highlight that dominant blue LEDs could be a potential light source to improve flowering traits that subsequently can increase fruit production and extend the harvesting season for DN strawberry cultivars
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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".