Characterization of Brassica nigra collections using simple sequence repeat markers reveals distinct groups associated with geographical location, and frequent mislabelling of species identity
Bibliographic record
Abstract
Genetic diversity of 180 Brassica nigra (L.) Kochgenotypes from 60 different accessions was evaluated using 15 simple sequence repeat markers with known locations on the Brassica A, B, and C genomes. Two lines each from Brassica juncea (L.) Czern and Brassica carinata Braunwere also included as comparator species. A total of 218 high quality alleles were used to generate a genetic distance matrix, and clustering and multidimensional scaling analyses were used to investigate genetic relationships among the accessions. Accessions from the same country of origin tended to cluster together. Surprisingly, 13 accessions declared to be B. nigra had A- and B-genome alleles and morphology consistent with them being B. juncea, which was supported by their positioning near B. juncea in the cluster analysis. Two B. nigra accessions possessed alleles associated more closely with the A genome than the B genome, and these may be Brassica rapa L. accessions. One B. nigra accession had B- and C-genome alleles and morphology consistent with it being B. carinata. The remaining 44 accessions (73%) appeared to be truly B. nigra and formed morphologically and genetically distinct groups associated with country or region of origin, notably Ethiopia, Israel, India, and Europe. Most B. nigra accessions were highly heterozygous, consistent with their obligate outcrossing habit. This study demonstrated the value of using molecular markers with known genome locations (in this case, in the Brassica A, B, and C genomes) to confirm species identity in families such as Brassicaceae where species identification based solely on morphological characters is difficult.
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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".