Genetic diversity, variability and characterization of the agro-morphological traits of Northern Ghana Roselle (Hibiscus sabdariffa var. altissima) accessions
Bibliographic record
Abstract
Roselle (Hibiscus sabdariffa var. altissima), a bast fibre crop adapted to the warm climate of Northern Ghana, offers a great economic potential not yet explored for lack of information on its distribution, collection, and genetic diversity. Little variability is reported in exotic genotypes to merit trait improvement. The objective of this study is to investigate distribution and diversity in roselle of Northern Ghana. Twenty-five accessions collected from seven districts were field evaluated in a 5×5 lattice square design in three replications at twelve qualitative and five quantitative morphological traits. Data were analysed for within- and between-population variability and multivariate analysis. Large within-population variability of SDI 0.72 to 0.87 was identified in accessions of Kassena-Nankana East district. The most variable traits, plant height and branch number, varied from 184 cm to 284 cm with six accessions HA-44, HA-47, HA-43, HA-38, HA-52, and HA-42 having the tallest plants and least basal branching of four. Mean flowering time was between 96 and 104 days. Mean Euclidean distance of 3.03 ± 0.90 ranged from 0.41 to 5.17. Based on means across pairwise distances of 2.22 and 3.94, three accessions were divergent, namely, HA-61 (3.94), HA-57 (3.66) and HA-59 (3.63). Clustering and principal components analyses delineated three distinct groups. The first three PCs explained 100% of the variance. The ample diversity in roselle awaits exploitation for genetic improvement, particularly for fibre yield. Key words: Bast fibre crop, cluster analysis, discriminant analysis, genetic diversity, morphology, PCA, roselle.
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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) | 0.001 | 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".