Characterizing the factors contributing to intraspecific pollen-mediated gene flow between cropped and volunteer spring wheat (Triticum aestivum L.)
Bibliographic record
Abstract
Transgenic crops have been widely adopted throughout many parts of the world.Their popularity is not without concern regarding the ecological and agricultural quandaries associated with their cultivation.Several traits have recently been incorporated into hexaploid wheat (Trticum aestivunt L.) using recombinant DNA technology and therefore, the resulting transgenic lines may require segregation from non-transgenic wheats to satisfy international markets.However, segregation may be complicated by the underlying biological characteristics of wheat plants that collectively allow for the transfer of genes between cropped and volunteer spring wheat populations.To this end, the objectives of this thesis were: i) to identify ahybridization window in spring wheat crops that would facilitate temporal isolation, thus minimizing flowering synchrony and pollen-mediated gene flow (PMGF); ii) to determine whether increasing crop density of spring wheat crops which are taller than volunteer genotypes could reduce flowering synchrony and PMGF between the two populations and; iii) to ascertain whether a relationship exists between flowering synchrony and PMGF such that flowering synchrony could be used to predict PMGF.Synchrony of flowering and PMGF were always greatest when seedling emergence timing of volunteers coincided with the wheat crop.Flowering synchrony ranged between 0%o and 86% depending on emergence timing, and a distinct hybridization window 125_ GDD in length was indentified in which seedling emergence of volunteer wheat plants would result in PMGF regardless of volunteer density.Volunteers emerging after the wheat crop (which cannot be selectively controlled) contributed substantially to PMGF and although plant height appeared to have some merit in reducing flowering synchrony, it had no influence on PMGF.Increasing crop density, on the other hand, resulted in an exponential decline in PMGF in all siteyears.However, further reductions above the recommended planting rate of 250 plants --t *e.e not realized.Overall, this research suggests that the potential for PMGF between volunteer wheat plants and a wheat crop is real and perhaps absolute.Nevertheless, results presented in this thesis lend support for the possibility of coexistence between transgenic and non-transgenic wheat within an appropriate framework that includes the establishment of realistic thresholds for admixture.
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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 | 0.001 | 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".