Genetic Polymorphism between Tobacco Cultivar-groups Revealed by Amplified Fragment Length Polymorphism Analysis
Bibliographic record
Abstract
Tobacco (Nicotina tabacum) has been introduced to Thailand for hundreds of years. All tobaccos cultivated inthe country are legally separated to local (or early-imported) and imported cultivar groups. However, no methodcould precisely differentiate the two groups, especially from cured leaf samples. Amplified fragment lengthpolymorphism (AFLP) analysis was introduced to estimate genetic polymorphism of 19 tobacco cultivars grownin Thailand. Thirty-two selective primer-combinations were screened on the genomic DNA extracted from curedleaves. Three primer pairs were selected and resulted in 139 scorable AFLP fragments, of which 103 (74.1%)were polymorphic. Genetic relationship analysis revealed clustering patterns of tobacco samples generallyfollowing the cultivar groups. Almost all local cultivars were found closely related to Burley and Turkish typesof the imported group, but significantly separated from Virginia type. Our finding therefore should be animportant knowledge for further research on cultivar identification and genetic improvement of tobaccos.
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 | 0.000 |
| 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".