DArT-based evaluation of soybean germplasm from Polish Gene Bank
Bibliographic record
Abstract
OBJECTIVE: Soybean is an important plant used for food, feed and many industrial purposes. Interest in soybean breeding is growing in Central Europe, including Poland. A very large number of soybean accessions are stored in gene banks, but less than 1% of them have been used for breeding. Here, we present genotypic data as well as phenotypic data on plant and seed performance, including seed chlorophyll fluorescence traits, and on yield components within a collection of soybean accessions that are conserved in the Polish Gene Bank at the Plant Breeding and Acclimatization Institute-National Research Institute. RESULTS: The materials used consisted of sub-collections: 79 Polish genotypes, including old traditional cultivars, 24 Canadian, 21 American, 21 Swedish and 31 from Central and Eastern European Countries, 9 from France and 6 from Japan. In total, 9602 high quality SNPs were derived from DArTseq, a method utilising GBS technology. GWAS, performed with the BLINK model, revealed that a total of 41 significant SNPs were mapped for days to flowering, flower colour, plant height, days to pod formation, 100 seed weight, pod colour, seeds and hilum colour and steady-state chlorophyll fluorescence under light (Ft_Lss). This is the first report about the diversity of traditional old Polish soybean cultivars.
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 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 | 0.001 | 0.002 |
| 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) | 0.001 | 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 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".