Identification of RAPD markers linked to A and B genome sequences in <i>Musa</i> L.
Bibliographic record
Abstract
Plantains and bananas (Musa spp. sect. eumusa) originated from intra- and interspecific hybridization between two wild diploid species, M. acuminata Colla. and M. balbisiana Colla., which contributed the A and B genomes, respectively. Polyploidy and hybridization have given rise to a number of diploid, triploid, and tetraploid clones with different permutations of the A and B genomes. Thus, dessert and highland bananas are classified mainly as AAA, plantains are AAB, and cooking bananas are ABB. Classification of Musa into genomic groups has been based on morphological characteristics. This study aimed to identify RAPD (random amplified polymorphic DNA) markers for the A and B genomes. Eighty 10-mer Operon primers were used to amplify DNA from M. acuminata subsp. burmannicoides clone 'Calcutta 4' (AA genomes) and M. balbisiana clone 'Honduras' (BB genomes). Three primers (A17, A18, and D10) that produced unique genome-specific fragments in the two species were identified. These primers were tested in a sample of 40 genotypes representing various genome combinations. The RAPD markers were able to elucidate the genome composition of all the genotypes. The results showed that RAPD analysis can provide a quick and reliable system for genome identification in Musa that could facilitate genome characterization and manipulations in breeding lines.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 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".