The biology and ecology of hexaploid wheat (<i>Triticum aestivum</i> L.) and its implications for trait confinement
Bibliographic record
Abstract
This review summarizes the biological and ecological factors of hexaploid wheat (Triticum aestivum L.) that contribute to trait movement including the ability to volunteer, germination and establishment characteristics, breeding system, pollen movement, and hybridization potential. Although wheat has a short-lived seedbank with a wide range of temperature and moisture requirements for germination and no evidence of secondary dormancy, volunteer wheat populations are increasing in relative abundance and some level of seed persistence in the soil has been observed. Hexaploid wheat is predominantly self-pollinating with cleistogamous flowers and pollen viability under optimal conditions of only 0.5 h, yet observations indicate that pollen-mediated gene flow can and will occur at distances up to 3 km and is highly dependent on prevailing wind patterns. Hybridization with wild relatives such as A. cylindrica Host., Secale cereale L., and Triticum turgidum L. is a serious concern in regions where these species grow in field margins and unmanaged lands, regardless of which genome the transgene is located on. More research is needed to determine the long-term population dynamics of volunteer wheat populations before conclusions can be drawn with regard to their role in trait movement. Seed movement has the potential to create adventitious presence (AP) on a larger scale than pollen, and studies tracing the movement of wheat seed in the grain handling system are needed. Finally, the development of mechanistic models that predict landscape-level trait movement are required to identify transgene escape routes and critical points for gene containment in various cropping systems. Key words: Triticum, coexistence, gene flow, genetically-engineered, herbicide-resistant, trait confinement
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".