Morphological Assessment of the Genetic Variability among 53 Accessions of West African okra [&lt;i&gt;Abelmoschus caillei&lt;/i&gt; (A. Chev.) Stevels] from South Western Nigeria

Osawaru, Moses Edwin; Ogwu, Matthew Chidozie; Dania-Ogbe, F.M

doi:10.4314/njbas.v21i3.8

Cited by 29 publications

(14 citation statements)

References 20 publications

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“…This suggests that genotypes of the same origin that are included in different clusters is an indication of the broad genetic base of the genotypes belonging to the origin. Prasad et al (2001) reported similar results when they studied 60 inbred lines of cucumber and Osawaru et al (2013) in their genetic variability study among 53 accessions of West African okra (Abelmoschus caillei [A.…”

Section: Cluster Analysissupporting

confidence: 52%

Studies of phenotypic and genotypic variation in sixteen cucumber genotypes

Ene

Ogbonna

Agbo

et al. 2016

Chilean J. Agric. Res.

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Genetic variability in a crop population is important for successful plant breeding. Sixteen cucumber (Cucumis sativus L.) genotypes were evaluated in the early and late planting seasons to estimate the magnitude of their genetic variability and heritability. Genotypes were also classified into groups based on the performance and determination of the highest discriminating trait that accounted for greater variability using cluster analysis and principal component analysis (PCA), respectively. The measured agronomic traits were vine length, number of branches, number of leaves, and leaf area 8 wk after planting, days to flower initiation, days to 50% flowering, number of staminate flowers per plant, number of pistillate flowers per plant, fruit length, fruit girth, fruit weight per plant, number of fruits per plant, mean fruit weight, and total fruit yield ha -1 . A high coefficient of variation was recorded for most traits in both seasons and high variability was found among genotypes. High broad-sense heritability was associated with all the traits in both seasons, except for mean fruit weight in the early planting season and fruit girth, mean fruit weight, and total fruit yield in late planting season. Cluster analysis and its comparison of means showed that 'Beit Alpha', 'Ashely', 'Straight 8', and 'Sumter' from cluster F in the early planting season and 'Beit Alpha' and 'Ashely' from cluster E in the late planting season expressed the best agronomic traits and yield potentials. Hence, selection for any trait would favor genotypes in these clusters. Principal component analysis involved vine length as the most discriminating trait that accounted for greater variability in cucumber in both the early and late planting seasons, and it should be considered in cucumber improvement programs.

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Section: Cluster Analysissupporting

confidence: 52%

Studies of phenotypic and genotypic variation in sixteen cucumber genotypes

Ene

Ogbonna

Agbo

et al. 2016

Chilean J. Agric. Res.

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“…It has been stated that genetic affinity between accessions from different regions could be attributed to selection and exchange of germplasm between farmers and ethnic groups [15]. Variability recorded in this study also agrees with the findings of [16], who reported high variability among fifty three okra accessions studied in Nigeria which might be due to genetic drift and selection in different environment.…”

Section: Discussionsupporting

confidence: 89%

Variability studies among some okra (Abelmoschus esculentus LMoench.) accessions from Niger State, Nigeria

K.¹,

J.A.²,

A.S.³

et al. 2020

IJFSA

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Field experiment was carried out at National Cereals Research Institute (NCRI), Badeggi research field, Niger State, to reveal the variability among some okra accessions. Thirty one accessions of okra were collected from farmers field and two (LD-88 and Nhae-47) collected from the department of crop production, Federal University of Technology Minna. The accessions were planted in Randomized Complete Block Design (RCBD) with three replications in a plot size of 2m x 1.5m. The experiment was carried out during dry and raining (2014/2015) season. Data were collected on twenty agro-morpholocal traits. Results of the principal component analysis (table 1 and table 2) of the combined seasons for the traits studied showed that the first five principal components accounts for 77.2 % and 89.0 % of the total variations in the population. Single Linkage Cluster Analysis (SLCA) display the accessions in accordance to their similarities level through the aid of dendrogram. SLCA of the combined season showed two major cluster groups that were linked at 65.7% level of similarity. Accessions that showed variability and clustered in different group may be useful for improvement of okra.

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“…Several studies used principal coordinates to demonstrate the divergence between genotypes using molecular data (Aitken et al, 2018;El-Esawi et al, 2018;Guzmán, Segura, Aradhya, & Potter, 2018;Taglioti et al, 2018;Wu et al, 2018;Ferreira et al, 2016;Zaher et al, 2011;Van Inghelandt, Melchinger, Lebreton, & Stich, 2010). Other studies were based on principal component analyses (Muller et al, 2018;Valcárcel, Peiró, Pérez-de-Castro, & Díez, 2018;Osawaru, Ogwu, & Dania-Ogbe, 2013;Santi et al, 2012;Jombart, Devillard, & Balloux, 2010). Additionally, studies have been conducted that used the projection of distance technique in a two or three-dimensional plane (Nicky, Carvalho, Assis, & Carvalho, 2008;Sant'Anna & Cruz, 2015).…”

Section: Introductionmentioning

confidence: 99%

Comparison of projection of distance techniques for genetic diversity studies

et al. 2019

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The objective of this study was to compare different graphical dispersion analysis techniques in two- or three-dimensional planes. In this study, the data from different published works were used in order to determine the best methodology for analyzing the genetic diversity of different species. In this study, efficiency is measured by the amount of original distance absorbed by the projection of distances technique, which in the case of major components is equal to the amount of total variation originally available and retained by the principal components used for dispersion purposes. The projection of dissimilarity measurement technique, principal component analysis (PCA), and principal coordinate analysis (PCoA) were used. Considering the analysis by means of three orthogonal axes, the graphical dispersion efficiency was 82.22 for PCA, 87.22 for PCoA, and 85.25 for the projection of distances technique. For the 2D analysis, considering the two main axes, the mean dispersion efficiency was 69.90 for the PCA, 75.06 for the projection technique, and 78.16 for PCoA. Considering the studies carried out with experimental data of six different species, it is concluded that the principal coordinate analysis is superior.

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Morphological Assessment of the Genetic Variability among 53 Accessions of West African okra [<i>Abelmoschus caillei</i> (A. Chev.) Stevels] from South Western Nigeria

Cited by 29 publications

References 20 publications

Studies of phenotypic and genotypic variation in sixteen cucumber genotypes

Studies of phenotypic and genotypic variation in sixteen cucumber genotypes

Variability studies among some okra (Abelmoschus esculentus LMoench.) accessions from Niger State, Nigeria

Comparison of projection of distance techniques for genetic diversity studies

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