Genetic diversity in bambara groundnut (<i>Vigna subterranea</i> (L.) Verdc) landraces revealed by AFLP markers
Why this work is in the frame
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Bibliographic record
Abstract
Bambara groundnut (Vigna subterranea (L.) Verdc), an African indigenous legume, is popular in most parts of Africa. The present study was undertaken to establish genetic relationships among 16 cultivated bambara groundnut landraces using fluorescence-based amplified fragment length polymorphism (AFLP) markers. Seven selective primer combinations generated 504 amplification products, ranging from 50 to 400 bp. Several landrace-specific products were identified that could be effectively used to produce landrace-specific markers for identification purposes. On average, each primer combination generated 72 amplified products that were detectable by an ABI Prism 310 DNA sequencer. The polymorphisms obtained ranged from 68.0 to 98.0%, with an average of 84.0%. The primer pairs M-ACA + P-GCC and M-ACA + P-GGA produced more polymorphic fragments than any other primer pairs and were better at differentiating landraces. The dendrogram generated by the UPGMA (unweighted pair-group method with arithmetic averaging) grouped 16 landraces into 3 clusters, mainly according to their place of collection or geographic origin. DipC1995 and Malawi5 were the most genetically related landraces. AFLP analysis provided sufficient polymorphism to determine the amount of genetic diversity and to establish genetic relationships in bambara groundnut landraces. The results will help in the formulation of marker-assisted breeding in bambara groundnut.
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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) | 0.001 | 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 it