Breeding Intermediate Wheatgrass for Grain Production
Bibliographic record
Abstract
Intermediate wheatgrass [IWG; Thinopyrum intermedium (Host) Barkworth & D. R. Dewey] is a perennial grass with the unique distinction of having been, for more than 30 years, the target of active breeding for use as a grain crop for human consumption. Improving the grain production characteristics of a perennial forage grass to economically viable levels is a long-term endeavor that was undertaken because of the potential for profound benefits to farmers, human society, and the environment. Even before research as a perennial grain, IWG has had a history of improvement as a forage species, and as one of wheat's closest perennial relatives it has also been used to transfer desirable traits into annual wheat. Since initial work in the 1980s, long-term breeding programs have been initiated in Kansas, Minnesota, and Utah (United States), Manitoba (Canada), and Uppsala (Sweden). Coupling advances in molecular technologies, many of these programs have harnessed the power of genomic selection and other cutting-edge tools to rapidly improve IWG. This has resulted in estimated gains of up to 8% per year for spike yield, and across eight breeding cycles grain yield has increased 9% per cycle, yet another 23 breeding cycles may be required before IWG yields are comparable to annual wheat. In addition to improving key domestication and agronomic traits, molecular research has provided a wealth of information about the genomic regions controlling trait expression through linkage mapping and genome-wide association studies. These results suggest that leveraging new molecular and breeding tools could potentially lead to de novo domestication of new crops in approximately 40 years or less.
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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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".