Morphological and Molecular Diversity in Turkish Sesame Germplasm and Core Set Selection
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
ABSTRACT The conservation of plant germplasm is essential to ensure future breeding gains and crop bio‐diversity. To be truly useful, such germplasm must be characterized for morphological traits and genetic diversity. In this work, agro‐morphological diversity was assessed in 137 Turkish sesame ( Sesamum indicum L.) genotypes (129 accessions and eight cultivars) by examination of eight qualitative and nine quantitative traits. As expected, morphological variability in the cultivars was low with broader diversity present in sesame accessions. However, some accessions were identified with interesting features, such as increased number of capsules and seed yield, which could be employed in future cultivar development. The sesame genotypes were analyzed for molecular genetic diversity with 140 amplified fragment length polymorphism (AFLP) loci. The results indicated a relatively low level of variability with an average dissimilarity value of 0.33 for all genotypes. Population structure was also examined and indicated that the material fell into two subpopulations. As most of the accessions (82%) were obtained from the U.S. Department of Agriculture (USDA) and are not yet housed in the Turkish national sesame germplasm collection, the data were used to identify a core set of 22 accessions that should be preserved in Turkey. The importance of using both molecular and morphological data for core selection is highlighted with a focus on germplasm preservation and breeding.
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.
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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 it