Morpho-agronomic Characters Under Drought Stress and Genetic Diversity on the Local Landraces of Cowpea [Vigna unguiculata (L.) Walp] From East Nusa Tenggara Province, Indonesia
Bibliographic record
Abstract
This study was performed to reveal the morpho-agronomic characters under drought and genetic diversity using SRAP (Sequence-related amplified polymorphism) marker on local landraces of cowpea (Vigna unguiculata (L). Walp) collected from East Nusa Tenggara Province, Indonesia. Data on drought response indexes according to the dry matter production of cowpea plants classified Carolina and Pinu Pahar as drought-sensitive and drought-tolerant cowpea genotypes, respectively. The assessment of the genetic diversity of cowpea genotypes was performed by using 25 SRAP combination primers. A total of 250 bands were produced by which 245 bands (98%) were polymorphic. The value of PIC (Polymorphic Information Content) of SRAP primers in this study varied from the highest value (0.97) to the lowest value (0.71) generated by primer pairs Me4-Em1 and Me3-Em4, respectively, with an average of PIC 0.87. An unweighted pair group method based on arithmetic averages (UPGMA) in this study was performed according to Nei and Li’s similarity index. The analysis of UPGMA and PCoA successfully separated Carolina and Pinu Pahar genotypes into different clusters. The result of the Mantel test showed that there was no significant correlation between the independent morpho-agronomic analysis and SRAP molecular matrix data.
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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 | 0.000 | 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".