Genetic structure and diversity of natural and domesticated populations of <i>Citrus medica</i> L. in the Eastern Himalayan region of Northeast India
Bibliographic record
Abstract
Citron (Citrus medica L.) is a medicinally important species of citrus native to India and occurs in natural forests and home gardens in the foothills of the eastern Himalayan region of northeast India. The wild populations of citron in the region have undergone rapid decline due to natural and anthropogenic disturbances and most of the remaining individuals of citron are found in fragmented natural forests and home gardens in the region. In order to assess the genetic structure and diversity of citron in wild and domesticated populations, we analyzed 219 individuals of C. medica collected from four wild and eight domesticated populations using microsatellite markers. The genetic analysis based on five polymorphic microsatellite loci revealed an average of 13.40 allele per locus. The mean observed and expected heterozygosity values ranged between 0.220-0.540 and 0.438-0.733 respectively among the wild and domesticated populations. Domesticated populations showed close genetic relationships as compared to wild populations and pairwise Nei's genetic distance ranged from 0.062 to 2.091 among wild and domesticated populations. Analysis of molecular variance (AMOVA) showed higher genetic diversity among- than within populations. The analysis of population structure revealed five groups. Mixed ancestry of few individuals of different populations revealed exchange of genetic materials among farmers in the region. Citron populations in the region show high genetic variation. The knowledge gained through this study is invaluable for devising genetically sound strategies for conservation of citron genetic resources in the region.
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".