Breeding Alfalfa for Semiarid Regions in the Northern Great Plains: History and Additional Genetic Evaluations of Novel Germplasm
Bibliographic record
Abstract
Yellow-flowered alfalfa (Medicago sativa subsp. falcata) (also known as sickle medic) has been the cornerstone for breeding alfalfa for dual grazing and hay production in the semiarid regions of the northern Great Plains in the US and Canada. Most, if not all, of the cultivars developed for the northern Great Plains during the 20th century, had parentage tracing back to introductions by Niels Ebbesen Hansen that were obtained from expeditions to Russia, primarily the province of Siberia, on behalf of the United States Department of Agriculture during the early 1900s. The M. falcata genome contains alleles for high levels of drought-tolerance, winter hardiness, and tolerance to grazing, but is generally deficient for commercial seed production traits, such as non-shatter, compared with common alfalfa (M. sativa). A naturalized population, tracing to USDA plant introductions to Perkins County South Dakota by N.E. Hansen in early 1900, and subsequently, facilitated by the determined seed increase and interseeding of a population by a local rancher, Norman ‘Bud’ Smith, has shown highly desirable in situ characteristics for improving rangelands in the northern Great Plains. This includes adequate seed production to build a seed bank in the soil for natural seedling recruitment and population maintenance/expansion and support the production of a commercial seed source. This review documents the seminal events in the development of cultivars to date and describes novel germplasm with potential for new cultivars in the future.
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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".