Genetic diversity among Japanese indigenous common buckwheat (<i>Fagopyrum esculentum</i>) cultivars as determined from amplified fragment length polymorphism and simple sequence repeat markers and quantitative agronomic traits
Bibliographic record
Abstract
We assessed the genetic diversity in Japanese indigenous common buckwheat (Fagopyrum esculentum) cultivars using amplified fragment length polymorphism (AFLP) and simple sequence repeat (SSR) markers and investigated the relationships between the genetic diversity and agronomic traits. The average expected intracultivar hetero zygosity was 0.303 for AFLP and 0.819 for SSR. The differentiations among agroecotypes, among cultivars within an agroecotype, and among cultivars were small (0.002, 0.024, and 0.026 for SSR and 0.013, 0.013, and 0.026 for AFLP, respectively) but statistically significant from zero except for the SSR differentiation among agroecotypes. In principal coordinates analysis, cultivars within the same agroecotype tended to cluster, indicating that agroecotypes well reflected the genetic relationships among cultivars. In AFLP, the differentiation among the agroecotypes was more distinct than in SSR, and genetic distance showed a moderate correlation with the difference in quantitative traits, indicating that AFLP can resolve the relationships among cultivars with better resolution than SSR. By contrast, SSR may be more sensitive to demographic changes. Four of the five SSR markers showed a significant positive correlation (Kendall's tau = 0.382-0.607) between allelic richness and variation in flowering timing, indicating that cumulative bottleneck events have occurred during the population history, with a decline in the variation of photosensitivity of flowering.
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 | 0.001 |
| 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) | 0.000 | 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".