Flowering Phenology and Synchrony between Volunteer and Cropped Spring Wheat: Implications for Pollen‐Mediated Gene Flow
Bibliographic record
Abstract
Genetically engineered (GE) wheat ( Triticum aestivum L.) volunteers could present a problem in cultivated wheat because they may facilitate movement of a GE trait to other volunteers or non‐GE wheat crops. However, volunteers can emerge periodically throughout the growing season and, thus, flowering overlap with the crop may be largely asynchronous, presenting a significant barrier to gene flow. Field experiments were initiated to determine the influence of volunteer wheat emerging at various densities and emergence times relative to the crop on flowering phenology and synchrony between cropped and volunteer spring wheat populations. Using a novel analytical method that treats individual flowering curves as a series of probability density functions, we characterized flowering phenology and quantified flowering synchrony between cropped and volunteer spring wheat. The results indicated that volunteer wheat initiated and ceased flowering earlier when emergence occurred before crop emergence. Thermal time requirements for completion of 5, 50, and 75% flowering decreased as volunteer emergence was progressively delayed. Flowering was further accelerated when emergence coincided with the crop and, consequently, flowering synchrony between volunteer and crop plants was significantly higher. Levels of flowering synchrony peaked at 86% and were highly dependent on volunteer emergence time relative to the crop. Our results suggest that pollen‐mediated gene flow (PMGF) in spring wheat will be dependent on emergence timing of volunteers and, thus, if hybridization between cultivated wheat and volunteers or neighboring wheat crops is going to transpire, it will most likely occur when volunteer emergence occurs within a hybridization window of 75 growing degree‐days on either side of crop emergence. Coupled with seed‐mediated gene flow, the additional admixture caused by PMGF could be problematic for coexistence between GE and non‐GE wheat.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".