Morpho–Molecular Characterization of Brazilian Common Bean Landraces Varieties and Commercial Cultivars
Bibliographic record
Abstract
This study aimed to characterize forty genotypes (31 landrace varieties and nine commercial cultivars) of common bean (Phaseolus vulgaris L.) morphologically and molecularly. Morphological descriptors were evaluated during seedling, flowering, physiological maturation and post-harvest stages. Ten microsatellite markers were used for molecular screening. The markers were analyzed according to the number of alleles per locus, the allele frequency per locus and the polymorphism in content (PIC). Genetic distances and cluster analysis were performed using Bayesian inference and the UPGMA method. All black beans evaluated have anthocyanin in the cotyledons, hypocotyls and stems, and their flowers are purple. For the growth habit, 50% of the evaluated genotypes belong to type III, and at the physiological maturation stage, yellow color is predominant in the pods (85%). Through the genetic dissimilarity, three groups were observed for the likelihood reason, and five groups were observed through the UPGMA method, a strong indication of the wide genetic diversity among the evaluated genotypes. All genotypes from the Andean center of origin were grouped into the same cluster.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".