Using DNA Markers to Evaluate Genetic Diversity Among Native Pawpaw Patches in Iowa\nand Kentucky
Bibliographic record
Abstract
The pawpaw [Asimina triloba (L.) Dunal] is in the early stages of domestication and wild collected plant material is still important in the commercial production of pawpaw. Native pawpaw patches can be found in hardwood forests growing in large patches as understory trees and can be found in 26 states in the eastern United States, ranging from northern Florida to southern Ontario (Canada) and as far west as eastern Nebraska. Kentucky State University serves as the USDA-National Clonal Germplasm Repository for pawpaw, therefore assessing genetic diversity across the pawpaw’s native range is a high priority. The objective of this study was to determine whether pawpaw trees from native patches in Iowa and Kentucky display genetic differences using the simple sequence repeat (SSR) marker system. DNA was extracted using the DNAMITE Plant Kit from leaf samples collected from 20 individual trees per patch from two native patches near Lake Cumberland in Kentucky, and in two native patches eastern Iowa. Primers B3, B103, B129, C104, and G119 were labeled with FAM and used to amplify SSR products. These products were then separated using a 3130 Applied Biosystems capillary electrophoresis system. The SSR primers yielded markers in the pawpaw selections examined that were useful in separating the pawpaw genotypes. The Iowa and Kentucky patches had at least two pawpaw genotypes in each patch but were mainly clonal in structure. The Iowa and Kentucky patches were separated easily based on high genetic variation in the marker alleles.
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How this classification was reachedexpand
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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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 teacher head, 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".