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Genetic Diversity Analysis in Bitter Gourd (momordica Charantia L.)

S Ghosh
Plant Breeding, Bangladesh Agricultural Research Institute (BARI) Gazipur

MH Khan
Agronomy, Bangladesh Agricultural Research Institute (BARI) Gazipur

SR Bhuiyan
Dept. of Genetics & Plant Breeding Sher-e- Bangla Agricultural University, Dhaka

R Akter
Agronomy, Bangladesh Agricultural Research Institute (BARI) Gazipur

Md Samsuzzaman
BARI, Gazipur

Abstract/ Executive Summary:

Seventeen genotypes of bitter gourd (Momordica charantia L.) were studied in a field experiment conducted at the experimental field of Sher-e-Bangla Agricultural University, Dhaka, during April 2010 to September 2010. The objectives of the study were to estimate the genetic variation among the genotypes for different characters including fruit yield. There was a great deal of significant variation among the genotypes for all the characters. The inter cluster distance between II and III (12.97) was the highest and distance between other clusters were more or less intermediate. Intermediate diverse parents have more chance to contribute heterosis in the subsequent generations. Cluster II had the highest cluster mean for vine length, number of nodes per vine, branches per vine, days to first male & female flowering, weight per fruit and yield per plant, but the characters days to first male and female flowering were the most important yield contributing character. Hybridization between the genotypes of cluster II and cluster VI manifests the maximum heterosis and creates wide genetic variability. Genetically distant parents are usually able to produce higher heterosis. Considering magnitude of genetic distance, magnitude of cluster means for different characters and field performance the genotypes G2, G5, G14 G15 from cluster II, genotypes G1 and G3 from cluster I, genotypes G8 and G9 from cluster III and genotypes G10, G11, G13 from cluster IV suitable for future hybridization programme.

Keywords: Biter gourd, Genetic variation, Ffruit yield and other characteristics

Location: Sher-e-Bangla Agricultural University, Dhaka

Start Date: 00-04-2010

End Date: 00-09-2010

Program Area: Variety and Species

Commodity: Bitter gourd

Objectives:

Considering the scope of study and available genetic resources of bitter gourd the present investigation was under taken with a view to estimate genetic diversity using multivariate techniques.

Methodology:

Seventeen genotypes of bitter gourd were used for the present research work. The genetically pure and physically healthy seeds of these genotypes were collected from different location. The experiment was laid out in a Randomized Complete Block Design (RCBD) with three replications. The individual plot was 3 m × 1 m in size. The distance maintained for spacing was row to row 50 cm, plant to plant 2m and between two blocks 1 m. Seeds of different accessions were sown in the pit on 5th May, 2010.Germination of seeds were completed within twelve days and in each pit four seeds were sown and the soil around the plant was firmly pressed by hand. After final land preparation, pits of 50 cm × 50 cm × 45 cm were prepared in each plot with a spacing of 3 m × 1.25 m. The dose of manure and fertilizers used in the study are Cow dung 10 ton/ha, Urea 150 kg/ha, TSP 100 kg/ha, MOP 150 kg/ha, Gypsum 80 kg/ha, Zinc Oxide 8 kg/ha. The intercultural operations were done from time to time throughout the cropping season for proper growth and development of the plants. Only one healthy seedling was kept per pit for the proper development. Fruits were picked on the basis of horticultural maturity, size, color and age. Frequent picking was done throughout the harvesting period. The following data such as, Days to first male flowering, Days to first female flowering, Vine length (m), Number of nodes per vine, Branches per vine, Fruit length (cm), Fruit diameter (cm), Number of fruit per plant, Weight per fruit (g), Yield per plant (kg), were recorded on parameters from the studied plants during the experiment. Mean data of the characters were subjected to univariate analysis using MSTAT-C computer program me. Multivariate analysis was done by computer using GENSTAT 5.13 and Microsoft Excel 2000 software through four techniques viz., Principal Component Analysis (PCA), Principal Coordinate Analysis (PCO), Cluster Analysis (CA) and Canonical Vector Analysis (CVA). The genetic diversity among the genotypes was assessed as general distance (D²) statistic and its auxiliary analyses. Principal Coordinate analysis is equivalent to PCA and used to calculate inter unit distances. Through the use of all dimension of p it gives the minimum distance between each pair of the n points using similarity matrix. The Mahalanobis’s distance (D²) values were calculated from transformed uncorrelated means of characters. The D² values were estimated for all possible combinations between genotypes. Average intra-cluster distances were calculated. Using the values of intra and inter-cluster distances (D), a cluster diagram was drawn. It gives a brief idea of the pattern of diversity among the genotypes included in a cluster.

Source of Information: Eco-friendly Agril. J. 8(11): 110-115, 2015 (November); ISSN 1999-7957

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Funding Source:

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Total Budget (Tk.) :

Achievement/Findings:

Among the inter cluster distance, distance between II and III (12.97) were the highest and other clusters were bearing more or less intermediate distance. Intermediate diverse parents have the more chance to contribute heterosis in the subsequent generations. Cluster II had the highest cluster mean for vine length, no. of nodes per vine, branches per vine, first male & female flowering, weight per fruit and yield per plant, but average to below average for days to first male and female flowering were not direct yield contributing characters. Hybridization between the Genotype of cluster II and cluster VI will manifest the maximum heterosis and create wide genetic variability. Considering magnitude of genetic distance, magnitude of cluster means for different characters and field performance of the genotypes G₂, G₅, G₁₄ G₁₅ from cluster II, genotypes G₁ and G₃ from cluster I, genotypes G₈and G₉ from cluster III and genotypes G₁₀, G₁₁, G₁₃ from cluster IV would be suitable for highest yield per plant in future hybridization programme.

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