Evaluation of maize microsatellite markers for genetic diversity analysis and fingerprinting in sugarcane
Bibliographic record
Abstract
The use of maize microsatellite markers as a potential cost-effective method for molecular analysis of sugarcane was evaluated. Of the 34 primer pairs obtained from maize genomic libraries, 14 showed repeatable amplifications in Saccharum species clones, commercial hybrids, and the related genera Erianthus, accounting for 41.17% cross transferability. Complex banding patterns were encountered in sugarcane with the number of amplified fragments ranging from 7 to 14 with an average of 10 per primer, indicating the high polyploidy and heterozygosity existing in sugarcane. Phenetic analysis of the SSR polymorphisms produced by nine primers could clearly differentiate the different species of Saccharum and Erianthus and revealed the relationships that existed between them. Genetic similarity co-efficient indicated low diversity existing among the S. officinarum clones (82%) and a relatively higher level of diversity in the S. spontaneum clones (69.7%). Higher level of divergence of Erianthus from Saccharum was also clearly estabilished. Five primers produced genus- and species-specific fragments for Erianthus, S. spontaneum, S. officinarum, and S. barberi. The polymorphic primers, when tested on a panel of 30 commercial sugarcane cultivars, revealed a broad range (32.4-83.3%) of pair-wise similarity values, indicating their ability to detect high levels of polymorphism. A combination of two primers could differentiate all the varieties, further emphasizing their potential in fingerprinting and varietal identification.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 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 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".