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D2 Statistic Techniques used for Analysis of Genetic DivergenceBY: Shaukeen Khan | Category: Agriculture | Submitted: 2017-04-19 00:31:12
Article Summary: "D2 Statistic is potential tool for identification of parents which are genetically diversified and used in hybridization programme.."
D2Statistic Techniques used for Analysis of Genetic Divergence
Author: Shaukeen Khan
D2 statistics analysis is used for selection of genetically divergent parents in hybridization programme. The concept of D2 statistics was originally developed by P.C. Mahalanobis in 1928. Rao used this technique for assessment of genetic diversity in plant breeding. It is used to measure the degree of diversification and determines relative portion of each component trait to total divergence. A large number of germplasm lines can be evaluated at a time for genetic diversity by it. It provides reliable estimates of genetic divergence. In plant breeding, genetic diversity plays a key role because hybrids between lines of diverse origin display a greater heterosis than closely related parents. This technique has been observed in fescue, maize, alfalfa, cotton and several other crops. Genetic diversity arises due to geographical separation. It is based on second order statistics, so analysis is more difficult than metroglyph analysis. Here, Analysis is possible from replicated data and genetic diversity is depicted by cluster diagram. The estimation of D2 values is very complicated specially when number of trait being studied becomes large because it needs inversion of matrix of higher order. The computation is very much simplified when traits under study are indepdent. There are three methods of grouping the genotypes into distinct clusters like Tenative grouping, Tocher method and Canonical root methods. It consists three major steps : Selection of genotypes, Eualuation of material, Biometricl analysis. According to this technique, if distance between cluster or groups of genotypes is more , three will be more genetically divergent parents of these groups. So , these cluster will be used in hybridization programme because of high genetic diversity leads to higher heterosis.
MAIN FEATURES OF D2 STATISTICS ANALYSIS
1.It is numerical approach which is used for measuring genetic divergence in germplasm collections.
2.It is based on second order statistics.
3.Analysis is more difficult than metroglyph analysis.
4.Analysis is possible from replicated data.
5.Genetic diversity is depicted by cluster diagram
MERIT OF D2 STATISTIC ANALYSIS
1.It helps in selection of genetically divergent parents for their exploitation in hybridization programme.
2.It measure the degree of diversification and determines relative portion of each component trait to total divergence.
3.It provides reliable estimates of genetic divergence
4.A large number of germplasm lines can be evaluated at a time for genetic diversity by it.
DEMERIT OF D2 STATISTIC ANALYSIS
1.Analysis is difficult.
2.The estimates are not satisfactory.
3.The analysis is not possible from unreplicated data.
1. Daniel, R.R. 2000. Future challenges in food production in India. Curr. Sci., 79(8): 1051-1053.
2. Mahalanobis, P.C. 1936. On the generalized distance in statistic. Proc. Nat. Inst. Soc., India. 2: 49-55.
About Author / Additional Info:
P.hd. student in Plant Breeding and Genetics, Rajasthan College of Agriculture, MPUAT, Udaipur, Rajasthan, India
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