2019•International Journal of Chemical StudiesOpen access

Character association studies of yield and its related traits in Okra

Sunil Gatade, Usha Tn, D. Lakshmana, L. Hanumantharaya, Devaraju, Chandana Bc

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Abstract

The experiment was laid out in a randomized completely block design with three replications including thirty five okra genotypes. Analysis of variance revealed that highly significant differences were observed among the genotypes for yield and seed quality traits indicating existence of genetic variability in the genotypes. Correlation studies revealed that highly significant and positive association of fruit yield per plant with plant height, number of branches, fruit length, fruit weight and number of fruits per plant at both phenotypic and genotypic level, indicating the possibility of simultaneous selection for these traits. The path coefficient analysis for fruit yield per plant was carried out considering 10 dependent component characters at both phenotypic and genotypic level. Path and genotypic coefficient revealed that fruit weight, number of fruits per plant and fruit length were the most influencing factors. Thus, these characters deserve greater weightage during selection for yield. Characters having high positive direct effects along with positive significant correlation with yield per plant can be directly selected, and simultaneously the characters which show high positive indirect effects can also be selected for the improvement of yield.

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What this paper is about

The experiment was laid out in a randomized completely block design with three replications including thirty five okra genotypes. Analysis of variance revealed that highly significant differences were observed among the genotypes for yield and seed quality traits indicating existence of genetic variability in the genotypes. Correlation studies revealed that highly significant and positive association of fruit yield per plant with plant height, number of branches, fruit length, fruit weight and number of fruits per plant at both phenotypic and genotypic level, indicating the possibility of simultaneous selection for these traits. The path coefficient analysis for fruit yield per plant was carried out considering 10 dependent component characters at both phenotypic and genotypic level. Path and genotypic coefficient revealed that fruit weight, number of fruits per plant and fruit length were the most influencing factors. Thus, these characters deserve greater weightage during selection for yield. Characters having high positive direct effects along with positive significant correlation with yield per plant can be directly selected, and simultaneously the characters which show high positive indirect effects can also be selected for the improvement of yield.

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Available abstract

The experiment was laid out in a randomized completely block design with three replications including thirty five okra genotypes. Analysis of variance revealed that highly significant differences were observed among the genotypes for yield and seed quality traits indicating existence of genetic variability in the genotypes. Correlation studies revealed that highly significant and positive association of fruit yield per plant with plant height, number of branches, fruit length, fruit weight and number of fruits per plant at both phenotypic and genotypic level, indicating the possibility of simultaneous selection for these traits. The path coefficient analysis for fruit yield per plant was carried out considering 10 dependent component characters at both phenotypic and genotypic level. Path and genotypic coefficient revealed that fruit weight, number of fruits per plant and fruit length were the most influencing factors. Thus, these characters deserve greater weightage during selection for yield. Characters having high positive direct effects along with positive significant correlation with yield per plant can be directly selected, and simultaneously the characters which show high positive indirect effects can also be selected for the improvement of yield.

Key concepts: Path coefficient, Randomized block design, Path analysis (statistics), Biology, Yield (engineering), Horticulture, Genotype, Selection (genetic algorithm)

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