Molecular Variability of <i>Celosia Argentea</i> Using Amplified Fragment Length Polymorphism (AFLP) Marker
Bibliographic record
Abstract
The molecular variability of ten genotypes of Celosia argentea seeds collected from National Institute of Horticultural Research (NIHORT) and National Centre for Genetic Resources and Biotechnology (NACGRAB) germplasms were evaluated using the Amplified Fragment Length Polymorphism (AFLP) marker. The polymorphism of C. argentea was detected within the population using primer mix of AFLP EcoRI + MseI adaptors type in three primer combinations. Powermarker software V3.25 was statistically used to analyse the fragments from extracted DNA region. The highest concentrations of genomic DNA of 13.30 u/L and volume of 2217.59 u/L for total genomic DNA were recorded for NG/TO/MAY/09/015 and NG/MA/MAY/09/015 genotypes respectively. Variations were observed in the number of fragments amplified by each of the three AFLP primers combinations. The Polymorphic Information Content (PIC) of the amplified fragment of the genomic DNA was diverse at 89.1% for DNA size of 100 base pairs, while the percentage gene diversity was 90%. The primer sequence combination of AAC + CAG produced the highest number of bands, amplified fragments, and number of polymorphic bands of 400, 40, and 156.000 respectively. A dendrogram constructed revealed three cluster groups, in which clusters 1 and 3 were delineated into 4 genotypes each, while cluster 2 had the least with two genotypes. This study revealed variability among the genome of C. argentea using AFLP marker. This could promote improvement and conservation of C. argentea germplasm for broaden genetic basis of breeding program.
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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 | 0.001 |
| 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".