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Genetic Diversity of Muskmelon Using Multivariate Technique

S. Rahman
Senior Scientific Officer
Plant Genetic Resources Centre (PGRC), Bangladesh Agricultural Research Institute (BARI), Gazipur.

M. A. K. Miah
Professor
Department of Genetics and plant breeding, Bangabandhu Sheikh Mujibur Rahman Agricultural University (BSMRAU), Gazipur.

H. Rahman
Assistant professor
Department of Entomology, BSMRAU, Gazipur, Bangladesh.

Abstract/ Executive Summary:

An experiment was conducted at the experimental farm of Plant Genetic Resources Centre (PGRC), Bangladesh Agricultural Research Institute (BARI), Gazipur in 2011 to estimate genetic diversity through multivariate technique. Based on multivariate analysis and application of covariance matrix for nonhierarchical clustering, 64 genotypes of muskmelon were grouped into six clusters to indicate the existence of considerable diversity among the genotypes. The cluster IV was consisted of single genotypes (BD2303). The highest number of genotypes possessed in Cluster I. The first principal axis largely accounted for the variation among the genotypes which alone contributed 25.65% of the variations. The highest inter genotypic distance (2.878) was observed between the genotypes BD2303 and BD2313 followed by the genotypes BD2303 and BD2314 (2.808).The highest intra cluster distance was computed for cluster III (0.839) followed by cluster I (0.751). Cluster VI showed the least intra cluster distance which indicated that the genotypes in this cluster were more or less homogeneous. The inter cluster distances were larger than the intra cluster distances suggesting wider genetic diversity among the genotypes of different clusters. Cluster mean pointed out the heavier fruit in cluster IV (2533.3g). The size of this cluster was also far different from all other clusters. Similarly, the highest total fruit weight per plant was found in cluster IV (13.5 kg) which was also far different from other clusters. So it revealed that genotypes of this cluster could be used for developing high yielding variety. Cluster VI showed the highest brix reading (5.6%). Therefore, the genotypes of this cluster could be used for the development of sweet muskmelon variety. Hybridization between the genotypes of cluster IV and those of cluster VI could develop high yielding sweet muskmelon variety(s).

Keywords: Genetic diversity; Cucumis melo; Cluster and Multivariate analysis

Location: Plant Genetic Resources Centre (PGRC), Bangladesh Agricultural Research Institute (BARI), Gazipur.

Start Date: 00-00-2011

End Date: 00-00-2011

Program Area: Postharvest and Agro-processing

Commodity: Muskmelon

Objectives:

To assess the genetic diversity among the collected germplasm and to identify the diverse parents for use in further genetic study.

Methodology:

The experiment was conducted at the experimental farm of Plant Genetic Resources Centre (PGRC), Bangladesh Agricultural Research Institute (BARI), Gazipur in 2011. The data on quantitative parameter of muskmelon was recorded and used to estimate genetic diversity through multivariate technique. The quantitative parameters were as follows : a. Fruit length (cm) b. Fruit width (cm) c. Fruit girth (cm) d. Flesh thickness(cm) e. Cavity diameter (cm) f. Fruit size (g) g. Number of fruits per plant h. Number of seeds per fruit i. 100 seed weight (g) j. Seed yield per plant (g) k. Total fruit weight (kg) l. Brix %. Mean data for each character was subjected to multivariate analysis techniques viz . Principal component analysis (PCA), Principal coordinate analysis (PCO), Canonical vector analysis (CVA) and Cluster analysis (CLSA) using GENSTAT 5.13 software.

Principal component analysis is one of the multivariate techniques to know the interrelationships among several characters and can be done from the sum of squares and product matrix for the characters. Principal components were computed from the correlation matrix and genotypic scores obtained for the first component and succeeding components with latent roots greater than unity. The latent roots are called "Eigen values". The first component has the property of accounting for maxi mum variance. The PCA displays most of the original variability in a smaller number of dimensions, since it finds linear combinations of a set of variate that maximize the variation contained within them. Contributions of the different characters towards divergence are discussed from the latent vectors of the two principal components. Principal coordinate analysis is equivalent to PCA but it is used to calculate inter - unit distances. Through the use of all dimensions of p it gives the minimum distances between each pair of the N points using similarity matrix. Inter - distances between genotypes were studied by PCO. CVA complementary to D² - statistic is a sort of multivariate analysis where canonical vectors and roots representing different axes of differentiation and the amount of variation accounted for by each of such axes, respectively are derived. Canonical variate analysis finds linear combination of original variability that maximize s the ratio of between groups to within groups variation, thereby giving functions of the original variables that can be used to discriminate between the groups. Thus in this analysis, a series of orthogonal transformations sequentially maximize the ratio of among groups to within group variations.

Genotypes were divided into groups on the basis of a data set into some number of mutually exclusive groups. The clustering was done using non hierarchical classification. In Genstat, the algorithm is used to search for optimal values of the chosen criterion. The optimal values of the criteria followed by some initial classification of the genotypes into required number of groups, the algorithm repeatedly transfers genotypes from one group to another so long as such transfer improved the value of the criterion. No further transfer can be found to improve the criterion. The algorithm switches to second stages that examine the effect swapping two genotypes of different classes, and so on. Computation of Average Intra - Cluster distance for each cluster was calculated by taking possible D² values within the members of a cluster obtained from the PCO after the clusters are formed. The formula utilized was ∑D² /n, where∑D² is the sum of distances between all possible combinations (n) of the genotypes included in a cluster. The square root of the average D² values represents the distance (D) within cluster. It was drawn using the values between and within cluster distances, which presents a momentary idea of the pattern of diversity among the genotypes included in a cluster. The procedure for calculating inter - cluster distance between cluster II and I, between cluster III and I, between cluster IV and I, between cluster V and I, between cluster VI and I and between cluster II and III and so on. The clusters were taken one by one and their distances from other clusters were calculated. Divergence analysis is usually performed to identify the diverse genotypes for hybridization programme. The genotypes grouped together are less divergent among themselves than different clusters. Clusters separated by the largest statistical distance (D² ), express the maximum divergence among the genotypes included into these different clusters.

Source of Information: Bangladesh J. Agril. Res. 41(2): 273-286, June 2016, ISSN 0258-7122

Article Link (Online Journal): DOI: http://dx.doi.org/10.3329/bjar.v41i2.28230

Funding Source:

1.	Budget:
2.	Budget:

Total Budget (Tk.) :

Achievement/Findings:

Genetic diversity of the muskmelon was assessed using multivariate technique. A considerable range of genetic diversity was found in the genotypes. The cluster analysis grouped the genotypes into six divergent clusters. The highest genotypes possessed in Cluster I. The Principal component analysis revealed that th e first principal axis largely accounted for the variation among the genotypes which alone contributed 25.65% of the variations. The maximum fruit weight per plant was found in cluster IV and the genotypes of this cluster could be used for developing high yielding variety. TSS indicates the sweetness of fruits. The genotype BD2312 (8 0 brix) was found as the sweetest muskmelon among the tested genotypes.

Knowledge Management: Journal, Booklet/Leaflet