Changes in Genetic Diversity of U.S. Flue‐Cured Tobacco Germplasm over Seven Decades of Cultivar Development
Why this work is in the frame
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Bibliographic record
Abstract
Plant breeding methodologies have been applied to flue‐cured tobacco ( Nicotiana tabacum L.) for approximately seven decades. As has been observed in several other crops, stringent quality requirements have resulted in use of conservative breeding strategies in the development of new cultivars. The impact of breeding practices on genetic diversity within U.S. flue‐cured tobacco germplasm has not been investigated. In this study, we genotyped 117 tobacco cultivars from eight sequential time periods with 71 microsatellite primer pairs. A total of 294 alleles were scored. Only a fraction (48%) of alleles present in the initial germplasm pool was represented in cultivars released during the 1990s and 2000s. Only 13 and 18 alleles were detected in the 1990s and 2000s, respectively, which were undetected in the initial gene pool. The overall trend was one of gradual reduction in allelic counts at microsatellite loci, indicating a reduction in diversity over time at the gene level. Average genetic similarity was highest among cultivars of the 1990s and 2000s, reflecting a reduction in genetic diversity at the population level. This observed narrowing of the U.S. flue‐cured tobacco germplasm base in combination with low rates of genetic gain for yield in the last 20 years may point to a need for diversification of parental materials used in future breeding crosses. Reported genetic relationships among the group of genotyped cultivars may be valuable for future strategic germplasm choices.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it