Optimizing regeneration protocols for native Seeds of Success–collected milkvetch (<i>Astragalus</i>spp.) genetic resources
Bibliographic record
Abstract
Abstract The USDA ARS National Plant Germplasm System conserves and promotes the use of important agricultural and ecological plant germplasm. In these collections, ~23,000 accessions representing 147 plant families have been acquired through the Bureau of Land Management Seeds of Success program. Unlike many of the cultivated crops in the collections, a significant proportion of these species lack basic biological information necessary for seed regeneration and long-term conservation. To fill knowledge gaps, we studied 5 native milkvetch (Astragalus L. [Fabaceae]) species to optimize germination protocols, characterize phenological and phenotypic traits, and test pollinator efficiency using various pollinator treatments. Germination trials tested 3 cold stratification (0, 2, or 6 wk in 4 °C [40 °F]) and 2 germination temperature (low: 15/25 °C [59/77 °F] and high: 20/30 °C [68/86 °F]) treatments in a full factorial design. Germination trial seedlings were outplanted at 2 sites (Prosser and Pullman, Washington) in fall 2020. We evaluated 3 pollination methods using honeybee (Apis mellifera Linnaeus [Apidae]), alfalfa leafcutting bee (Megachile rotunda Fabricius [Megachilidae]), and open pollination. Cold stratification increased germination in A. drummondii but had little effect on the other 4 species. Germination at the lower incubation temperatures was as effective, if not better, than germination at the higher temperatures. Only Canadian milkvetch (Astragalus canadensis L.) and two-grooved milkvetch (A. bisulcatus (Hook.) A. Gray) had sufficient survival in the Pullman location to move forward with pollinator treatments. Differences were not found in pollinator treatments for seed set or yield (P > 0.05). Astragalus canadensis and A. bisulcatus performed generally better than other species evaluated with the highest number of established and surviving plants, good seed set, and highest seed yields. This research provides critical information on germplasm management and suggests the need for further research on protocol development.
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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 | 0.001 | 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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".