Genetic Diversity in Eggplant (Solanum melongena L.)  

S. Ramesh kumar1 , T. Arumugam2 , C.R. Anandakumar3
1. Assistant Professor, Department of Horticulture, Vanavarayar Institute of Agriculture, Manakkadavu, Pollachi, TNAU, Tamil Nadu, India;
2. Professor, Department of Horticulture, Agricultural College and Research Institute, TNAU, Madurai, Tamil Nadu, India;
3. Professor, Department of Plant Breeding and Genetics, Agricultural College and Research Institute, TNAU, Madurai, Tamil Nadu, India
Author    Correspondence author
Plant Gene and Trait, 2013, Vol. 4, No. 2   doi: 10.5376/pgt.2013.04.0002
Received: 26 Jan., 2013    Accepted: 05 Feb., 2013    Published: 20 Mar., 2013
© 2013 BioPublisher Publishing Platform
This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Preferred citation for this article:

 Kumar et al., 2013, Genetic Diversity in Eggplant (Solanum melongena L.), Plant Gene and Trait, Vol.4, No.2 4-8 (doi: 10.5376/pgt.2013.04.0002)

Abstract

Genetic divergence among 14 eggplant genotypes was estimated using Mahalanobis’s D2 statistic. Altogether six clusters were formed. The maximum number of genotypes (5) was found in cluster III with intra cluster distance of 2 597.79. The maximum inter cluster distance was observed between cluster â…¡ and cluster â…¤. Hence, genotypes belonging to these clusters may be utilized for involving in hybridization programme for crop improvement. The characters of yield per plant, fruit circumference, little leaf incidence and total phenols content contributed more for genetic divergence.

Keywords
Eggplant (Solanum melongena L.); Genetic diversity; Cluster analysis

1 Introduction
Eggplant or brinjal was first cultivated in India which is regarded as the primary centre of origin/diversity. India is the major producer of brinjal in the world and it is grown in an a area of 0.61 million ha with an estimated annual production of 13.37 million tonnes with a productivity of 17.3 tonnes per ha. In Tamil Nadu the production was 8.5 lakh tonnes from 0.75 lakh ha of area (Anonymous, 2010). Information on genetic divergence among the available germplasm is vital to a plant breeder for an efficient choice of parents for hybridization. It is an established fact that genetically diverse parents are likely to contribute desirable segregants. It was also observed that the more diverse the parents, greater are the chances of obtaining high heterotic F1s and broad spectrum of variability in the segregating generation (Arunachalam, 1981). Improvement in yield and quality is normally achieved by selecting genotypes with desirable character combin- ations existing in the nature or by hybridization. Selection of parents identified on the basis of divergence analysis would be more promising for a hybridization programme. Some related results have been reported in eggplant by Kumar et al. (2000), Singh and Gopalakrishnan (1999), Chaudhary and Pathania (1998) and Tambe et al. (1993). These studies did not cover any local cultivars/genotypes. Therefore, the present inve- stigation was undertaken to estimate the nature and magnitude of genetic diversity in some eggplant genotypes. This type of study would be useful for breeding eggplant varieties in the country.

2 Results and Discussion
The use of Mahalanobis D2 statistics for estimating genetic divergence have been emphasized by many workers Patil et al. (1994) and Mishra et al. (1998) because it permits precise comparison among all possible pairs of population in any given group effecting actual crosses.

2.1 Clustering Pattern 
In the present study, fourteen genotypes were evaluated for fifteen characters and the analysis revealed the presence of wide genetic diversity as they formed six gene constellations. Among the six clusters, cluster III had constituted maximum of five genotypes out of fourteen assembled from different geographical location (Table 1). The clustering pattern revealed that the genotype did not resolve according to their geographical origin. Geographic diversity, though appear as an important factors it seems that it is not the only factor determining the genetic divergence. It also indicates that the factors other than geographical diversity may also be responsible for such grouping types. Singh and Prasad (1991) opined that the geographical distribution need not directly be related to genetic diversity as estimated by D2 statistics. A similar finding was reported by Parmanick et al. (1992), Tambe et al. (1992) and Yadav et al. (1996). In contrast, the other clusters â… , â…¡, â…£ and â…¤ had two genotypes each coming from different geographical origin. Whereas, Cluster â…¢ had five genotypes and among five genotypes, two which was from same geographical location.
 

 

 
Table 1 Clustering pattern of 14 genotypes of brinjal


2.2 Intra and Inter cluster distances 
Average intra and inter cluster D2 values of fourteen genotypes have been studied (Table 2; Table 3). Among the six clusters, the clusters â…¡, â…¢, â…£ and â…¤ were found to be highly divergent from the others, as it had constituted two genotypes. The values show that the cluster â…¤ had the maximum intra D2 value, followed by cluster III. This is indicative of the fact that the genotypes included in these clusters are very diverse. The inter cluster D2 value was found to be maximum between cluster â…¡ and â…¤ followed by â…£ and â…¤. The genotypes belonging to clusters â…¡, â…¢, â…£and â…¤ could have greater genetic divergence and hence intermating between the genotypes belonging to them would give more transgressive segregates in advanced generations. Selection of genotypes belonging to clusters with maximum inter cluster distance had also been proposed by Mehta et al. (2004), Patel et al. (2004) and Prabakaran (2010) in brinjal. 
 

 

 
Table 2 Mean inter and intra cluster D2 values

 

 

 
Table 3 Mean inter and intra cluster distances


2.3 Cluster mean for different characters 
The cluster mean values serve for selection of parents for recombination breeding. The cluster V, which had constituted only two genotype (Nilakottai Local and Annamalai), was found to exhibit minimum values for plant height, fruit circumference, calyx length and fruit borer infestation and maximum in number of branches per plant, fruit length, fruit pedicel length, number of fruits per plant and ascorbic acid content. The clusters differed with respect to their per se performance. A close look at Table 4 reveals that the clusters excelled in respect of different characters. Cluster â…¡ and â…¤ were more diverse with very high fruit yield per plant and solitary in nature. Cluster â…£and â…¥ were also solitary in nature comprising early genotypes with respect to days to flowering. Cluster â…¡was good for fruit yield and related characters. Cluster â…£ was also good having high phenol content and lower incidence of liitle leaf incidence. 
 

 

 
Table 4 Cluster means for fifteen characters in brinjal


The cluster mean for fruit yield per plant was highest in cluster â…¡ (Alavayal Local and Palamedu Local) followed by cluster â…¤ (Nilakottai Local and Annamalai) and â…¢ (Sedapatty Local (Green), Melur local, Keerikai Local, Sedapatty Local (Blue) and KKM 1). High cluster mean for most of the yield contributing traits coupled with inter cluster distance was found in cluster V and cluster â…¡ which indicate the possibility of obtaining high heterotic vigour and selection of superior segre- gants by inter crossing genotypes from these clusters as reported by Mehta et al .(2004).

2.4 Contribution of characters to genetic divergence 
In addition to the knowledge on the degree of divergence, the study also revealed the contribution of different characters studied towards total genetic divergence (Table 5). The character that appears the maximum number of times ranks first and greater is its contribution to genetic divergence. In the present investigation, an assessment of the contribution of different characters indicated that, the character fruit yield per plant was the maximum contributor for genetic divergence, followed by little leaf incidence, fruit circumference, total phenol content, shoot borer infestation and fruit borer infestation. The importance of fruit circumference in genetic divergence of brinjal had been observed by Dhankar et al. (1978), Babu and Patil (2004) and Prabakaran (2010). The relative contribution of plant height, days to first flowering, number of branches per plant, fruit pedicel length, clayx length, number of fruits per plant and ascorbic acid content for divergence among the genotypes was found nil. While the contribution of fruit length and average fruit weight was minimal. The study also indicated that the characters such as fruit yield per plant, fruit circumference, little leaf incidence and total phenol content, should also be considered while selecting parents for hybridization as they are important contributors of genetic divergence.
 

 

 
Table 5 Relative contribution of different characters to genetic diversity in brinjal


3 Materials and Methods
The experiment was conducted at the College Orchard, Agricultural College and Research Institute, Madurai during 2009~2010 which is situated at 9°5 latitude and 78°5 longitude and at an elevation of 147 m above MSL with 14 genotypes (10 local types and four released varieties) of eggplant representing samples from different locations. The seeds of these germplasm were sown on the seedbed and thirty-five days old seedlings were transplanted in the main field with a plant spacing of 60 cm maintaining a row distance of 60cm. The experiment was laid out in a Randomized Block Complete Design with three replications. Cultural practices were followed as per the package of practices of TNAU Crop Production Guide (2005). Thirty plants were accommodated in a plot with a data were recorded from five randomly selected plants from each plot for plant height, days to first flowering, number of branches per plant, fruit length, fruit pedicel length, fruit circumference, calyx length, number of fruits per plant, average fruit weight, shoot borer infestation, fruit borer infestation, little leaf incidence, ascorbic acid content, total phenol content and fruit yield per plant in 14 parents. Plot means over the replications were used for the statistical analysis. Genetic diversity was studied following Mahalanobis’s (1936) generalized distance (D2) extended by Rao (1952). Based on the D2 values, the genotypes were grouped into clusters following the method suggested by Tocher (Rao, 1952). Intra and inter cluster distances were calculated by the methods of Singh and Chaudhury (1985). Statistical analyses were carried out using GENRES software.

Authors' Contributions
Dr. S. Ramesh Kumar conceived the overall study, performed the experiment designs and drafted the manuscript. Dr. T. Arumugam and Dr. C.R. Anandakumar took part in the experiment as chairman and member of the advisory. The above scientists read the manuscript and revised it. All authors had read and consent the final text.

Acknowledgements
The authors are thankful to various research institutes Viz., Vegetable Research Station Palur, Agricultural College and Research Institute, Killikulam, Madurai and TNAU, Coimbatore for providing the germplasms to carry out the present investigation. Dr. V. Premalakshmi, Assistant Professor (Horticulture), Agricultural College and Research Institute, Madurai is duly acknowledged for giving valuable suggestions during my research period.


References 
Anonymous, 2010, Area, production and productivity of brinjal in India during 2009-2010, www.indiastat.com 

Arunachalam V., 1981, Genetic distances in plant breeding, Indian J. Genet., 41: 226-236 

Babu R.B., and Patil R.V., 2004, Genetic divergence in brinjal, Veg. Sci., 31(2): 125-128

Chaudhary D.R., and N.K. Pathania, 1998. Variation studies in some genetic stocks of eggplant, Himachal Journal of Agricultural Research, 24(1-2): 67-73 

Dhankar B.S., Mehrotra N., and Chaudhary B.D., 1978, Divergence in brinjal (Solanum melongena L.), Genetic Agr., 32: 299-304 

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