<abstract xmlns="http://www.w3.org/1999/xhtml">

Okra yields are low in West and Central Africa and factors including narrow genetic base of available germplasm have been implicated. An assessment of genetic variability among germplasm from various sources and knowledge of trait contributions to these variations is crucial to the success of okra breeding program. Eighteen okra accessions were evaluated during the 2020 cropping season in Nigeria to assess the genotypes for genetic diversity, group the accessions into clusters and identify traits that chiefly accounted for the variations among the genotypes. Data obtained were subjected to analysis of variance (ANOVA), metroglyph and principal component analyses (PCA). ANOVA revealed significant accession mean squares for majority of the measured traits. Metroglyph analysis grouped the accessions into four clusters with members of Cluster IV generally high-yielding, early-maturing and short genotypes. NGB00353 and NGB00356 that were among genotypes with high total index scores were members of Cluster IV. The first four principal components (PCs) accounted for 80% of the total observed variation. PC1 with the highest discriminatory power was loaded with days to budding, internode length, pod yield.plot−1 and the number of pods.plant−1. The variation within and between clusters could be explored in okra breeding program.
</abstract>

Okra yields are low in West and Central Africa and factors including narrow genetic base of available germplasm have been implicated. An assessment of genetic variability among germplasm from various sources and knowledge of trait contributions to these variations is crucial to the success of okra breeding program. Eighteen okra accessions were evaluated during the 2020 cropping season in Nigeria to assess the genotypes for genetic diversity, group the accessions into clusters and identify traits that chiefly accounted for the variations among the genotypes. Data obtained were subjected to analysis of variance (ANOVA), metroglyph and principal component analyses (PCA). ANOVA revealed significant accession mean squares for majority of the measured traits. Metroglyph analysis grouped the accessions into four clusters with members of Cluster IV generally high-yielding, early-maturing and short genotypes. NGB00353 and NGB00356 that were among genotypes with high total index scores were members of Cluster IV. The first four principal components (PCs) accounted for 80% of the total observed variation. PC1 with the highest discriminatory power was loaded with days to budding, internode length, pod yield.plot−1 and the number of pods.plant−1. The variation within and between clusters could be explored in okra breeding program.

Assessment of genetic variability among accessions of okra (<italic>Abelmoschus esculentus</italic> L. Moench)

Acta Horticulturae et Regiotecturae

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Assessment of genetic variability among accessions of okra ( L. Moench)

Okra yields are low in West and Central Africa and factors including narrow genetic base of available germplasm have been implicated. An assessment of genetic...

Assessment of genetic variability among accessions of okra (Abelmoschus esculentus L. Moench)

Published Online: Dec 02, 2021

Page range: 141 - 147

Received: Apr 18, 2021

Accepted: Jun 15, 2021

DOI: https://doi.org/10.2478/ahr-2021-0036

Keywords
clusters, early-maturing, high yield, okra germplasm, variations

© 2021 Richard Olayiwola et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Assessment of genetic variability among accessions of okra (Abelmoschus esculentus L. Moench)

Published Online: Dec 02, 2021

Page range: 141 - 147

Received: Apr 18, 2021

Accepted: Jun 15, 2021

DOI: https://doi.org/10.2478/ahr-2021-0036

Keywordsclusters, early-maturing, high yield, okra germplasm, variations

© 2021 Richard Olayiwola et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Keywords
clusters, early-maturing, high yield, okra germplasm, variations