Genetic Diversity and Population Structure in a World Collection of <i>Brassica napus</i> Accessions with Emphasis on South Korea, Japan, and Pakistan
Bibliographic record
Abstract
ABSTRACT Information on genetic diversity and population structure is needed for continued improvement in Brassica napus L. A total of 169 B. napus lines, collected between 1970 and 2000 in Australia, Canada, China, Europe, Japan, Pakistan, and South Korea, were genotyped with 84 simple sequence repeat markers. Nei's unbiased genetic diversity (H) and Shannon's information index (SI) showed that genetic diversity was highest among lines from Europe followed by South Korea, Japan, China, and Pakistan while lines from Australia and Canada had the lowest diversity. Pairwise comparison of the populations using Nei's genetic identity (I) and genetic distance (D) showed greater differentiation between Australia and Canada versus China and Pakistan. Accessions from South Korea and Japan were most similar, confirming an historical exchange of germplasm. The analysis of unique alleles and allele richness revealed that the Pakistani population was the richest followed by Europe and South Korea. Analysis of molecular variance revealed that 9% of the variation was accounted for by geographical region and 91% by lines. Both Structure and principal coordinate analyses indicated two subpopulations in the collection confirming separation of genotypes due to growth habit adaptation. Information on B. napus genotypes containing unique alleles is valuable for breeding programs in different parts of the world seeking to improve agronomic traits and adaptability.
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 | 0.001 | 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".