Molecular genetic characterization of Central European soybean breeding germplasm
Bibliographic record
Abstract
Abstract Soybean is the most important oilseed and protein crop worldwide, but in Europe, the acreage is comparably low. Thus, Europe strongly depends on imports of soy products and consequently recent efforts aim at expanding the acreage of soybean, particularly in Central Europe. The aim of this study was, therefore, to assist these breeding efforts by characterizing Central European soybean germplasm, employing a genotyping‐by‐sequencing approach yielding 7741 genomewide distributed markers. Our analysis on genetic diversity and population structure revealed that the Central European lines are most closely related to Swiss and Canadian lines and somewhat more distant from the investigated Chinese and US lines. In addition, we analysed patterns of allelic diversity and the extent of linkage disequilibrium. Collectively, our results can assist breeding of Central European soybean and suggest that further progress can be made by crosses among adapted material but a long‐term success also requires introgression of alleles from non‐European germplasm to further broaden the genetic diversity and incorporate novel traits.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| 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) | 0.001 | 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".