Factor, Principal component and canonical analyses were used to study the extent of genetic diversity among 30 accessions of West African okra . Genetic variability among the accessions proved to be large . Pigmentation of various parts of the accessions and fruit characteristics contributed significantly to the total variation observed . Factor analysis and principal component analysis produced similar results which were substantially different from those produced by canonical analysis . The first three canonical variables accounted for 100% of the total variance while the number of pods per plant, and pod weight primarily accounted for the first canonical variable . Whereas the second canonical variable was primarily loaded by number of seeds per pod and fruit colour, the third canonical variable was comprised of a weight of 100 seeds and number of epicalyx segments .The level of variability observed supports the opinion (Stevels, 1988(Stevels, , 1990) that this okra type constitutes a separate species .

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Thirty-one accessions of cowpea of diverse eco-geographic origins were evaluated for genetic diversity using principal component analysis (PCA), single linkage cluster analysis (SLCA) and canonical techniques. The accessions were classified into six groups by PCA and SLCA while canonical technique identified five vector groups. There was no relationship between the clustering pattern and eco-geographic distribution. PCA and canonical techniques can be jointly used in multivariate analysis as both techniques performed complimentary role in identifying characters responsible for variation in cowpea. SLCA alone provided a clearer and more informative display of the group of accessions based on character performance. The three techniques revealed most distant accessions as having widest variation and possible choice of parent stocks in hybridization.

Thirty okra genotypes of diverse eco-geographical origin were grown in single-row plots in a randomised complete block design. The data collected on 14 characters were subjected to analysis of variance. By multivariate analysis (Mahalanobis D(2) technique), the genetic divergence among the genotypes were quantitatively measured. The genotypes were grouped into five clusters by this technique. There was no relationship between clustering pattern and eco-geographic distribution. The effects of genetic divergence on the choice of parental stock in hybridization was discussed.

Okra, character correlations, path coefficient analysis. SUMMARY Genotypic, phenotypic and environmental correlation coefficients were calculated for fifteen characters during two growing seasons. Correlation coefficients varie between seasons. Edible pod weight, edible pod length, edible pod width, number of seeds per plant, weight of 100 seeds, length of mature pods and number of branches per plant showed significant genotypic correlation with pod yield per plant; only number of branches per plant, edible pod length and weight of 100 seeds were phenotypically correlated with pod yield. Environmental correlation coefftcients were generally low but edible pod length, final plant height and edible pod weight showed significant environmental correlation with pod yield during the two seasons.The genotypic correlation coefficients of selected eight characters with pod yield were partitioned into direct and indirect causes. In the early seasons, edible pod weight had the largest positive direct effect on pod yield with its largest indirect effect through reduction in edible pod width. Edible pod width which was highly correlated with pod yield had a negative direct effect on pod yield. In the late season, edible pod weight had the largest direct effect on pod yield, with large indirect effects through reduction in number of days to flowering and number of pods per plant. Number of days to flowering had a large direct effect on pod yield with its largest indirect effect through reduction in edible pod weight. The residual factors during the two seasons were negative. The study indicated that only number of branches per plant, edible pod length and weight of 100 seeds would be useful for indirect selection for pod yield. The path analysis indicated that edible pod weight was the most reliable and effective character to select for when high yield is the objective.

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West African okra occurs in wild and unselected variants in Nigeria but farmers desire stable and high-yielding cultivars. Twenty-five West African okra genotypes from diverse geographical backgrounds were evaluated in five different environments for stability of performance. Performance was measured by number of days to 50% flowering, number of pods per plants, number of seeds per pod, plant height at maturity and seed yield per plant. A regression method, Additive main effects and Multiplicative Interaction (AMMI) and Genotype main effect and genotype x environment Interaction (GGE) were employed in the evaluation. Joint regression and AMMI analyses showed significant (P< 0.01) G x E interaction with respect to seed yield, and both identified NGAE-96-0060 and NGAE-96-0063 as stable genotypes. The AMMI and GGE biplot analyses are more efficient than the Eberhart and Russell analysis. The GGE biplot explains higher proportions of the sum of squares of the GxE interaction and is more informative with regards to environments and cultivar performance than the AMMI analysis. GGE-biplot models showed that the five environments used for the study belonged to three mega-environments with environment 2 (Upland, 2007) being the most representative and most desirable of all. The GGE results also confirmed NGAE-96-0063 as being stable with NGAE-96-04 as the most stable. NGAE-96-04 was identified as most superior genotype in terms of yield and stability of performance and could be recommended for cultivation.