##plugins.themes.bootstrap3.article.main##

Priyanka Verma S. K. Maurya Hridesh Yadav Ankit Panchbhaiya

Abstract

The present investigation was carried out at Vegetable Research Centre, Pantnagar to estimate the ge-netic divergence using Mahalanobis D2 statistics for twelve characters on 35 genotypes of pointed gourd. Cluster analysis and principal component analysis (PCA) were used to identify the most discerning trait responsible for greater variability in the lines and on the basis of mean performance, genotypes were classified into different groups. Five principal components (PC) have been extracted using the mean performance of the genotypes and 83.23 per cent variation is yielded by the first five principal components, among them high mean positive value or higher weight age was obtained was obtained for days to first female flower anthesis and days to first fruit harvest among all the vectors, indicates that these traits are important component of genetic divergence in pointed gourd. Non- hierarchical Euclidean cluster analysis grouped the genotypes into seven clusters and the highest number of genotypes were found in cluster number IV i.e. eleven whereas maximum inter-cluster distance was found between the cluster III and VI i.e. 74.250, it indicates that a wide range of genetic divergence is present between the genotypes present among these two clusters. And as per contribution toward total divergence, traits like fruit yield per hectare and number of fruit per plant contributed 92.64% toward total divergence. The high diversity found in the genotypes showed its great potential for improving qualitative as well as quantitative traits in pointed gourd.

Downloads

Download data is not yet available.

Metrics

Metrics Loading ...

##plugins.themes.bootstrap3.article.details##

##plugins.themes.bootstrap3.article.details##

Keywords

Divergence, Non-hierarchical cluster, PCA, Principal component analysis, Pointed gourd

References
Afroze, F., M. G. Rasul, Islam, A.K.M.A., Mian, M.A.K. and Hossain, T. (2007).Genetic divergence in ash gourd (BenincasahispidaThunb.).Bangladesh J. Pl. Breed. Genet., 20(1): 19-24.
Beale, E.M.L. (1969).Euclidean cluster analysis.37th session of Int Stat Inst, UK.
Cruz, C. D. and Carneiro, P.C. (2003). Modelosbiométricosaplicadosaomelhoramento genetic diversity.Viçosa (MG): UFV, Imprensa University. 2(1).
Devi, N.D. and Mariappan, S. (2014). Studies on genetic diversity in snake gourd (TrichosanthesanguinaL.). Universal Journal of Agricultural research.(1): 1-5.
Iqbal, Q., Saleem, M.Y., Hameed, A. and Asghar, M. (2014). Assessment of genetic divergence in tomato through agglomerative hierarchical clustering and principal component analysis. Pak. J. Bot., 46(5): 1865-1870Z
Gaffar, A. (2008). Characterization and genetic diversity of sponge gourd (Luffa cylindrica L.).M.Sci. Thesis submitted to Sher-e- Bangla Agricultural University, Dhaka. India. pp. 88-90.
Ghaderi, A., Adams, M.W. andNassib, A.M. (1984).Relationship between genetic distance and heterosis for yield and morphological traits in dry edible bean and faba bean.Crop Sci. 24:37-42.
Hair, J.R., R.E. Anderson, R.L. Tatham, and W.C. Black. (1995). Multivariate data analysis with readings. 4th edition, Prentice-Hall, Englewood Cliffs, NJ.
Hotelling, H. (1933). Analysis of complex of statistical variables into principal components. Journal of Educational pshycology, 24: 417-441.
Huque, A.K.M.H., Hossain, M.K., Alam, N., Hasanuzzaman, M. and Biswas, B.K.(2012). Genetic divergence in yardlong bean (Vignaunguiculata (L.) walp. Ssp. Sesquipedalisverdc). Bangladesh J. Bot.,
41(1):61-69.
Janaki, M., Naram Naidu, L., VenkataRamana, C. &Paratpara Rao, M. (2016).Genetic divergence among chilli (Capsicum annuum l.) Genotypes based on quantitative and qualitative traits. I.J.S.N.7.(1): 181-189.
Kendall, M. (1980).Multivariate Analysis (Second Edition).Charles Griffin and Co London.
Khan, A.S.M.R., Rabbani, M.G., Siddique, M.A.and Hossain, M.I. (2008). Study on genetic diversity of pointed gourd using morphological characters. Bangladesh J. Agril. Res. 33(3): 607-616.
Khodadabi, M., Fotokian, M.H. and Miransari, M. (2011). Genetic diversity of wheat genotypes based on cluster and principal component analysis for breeding strategies. Australian J. Crop Sci. 5.(1): 17-24.
Kovacic, Z. (1994). Multivariate analysis.Faculty of Economics.University of Belgrade.(In Serbian).P. 293.
Kumar, S.,Marappa, N. And Govindaraj.M.(2010). Classification of new germplasm and advanced breeding lines of groundnut (Arachishypogaea L.) through principal component analysis. Leg. Res. 33: 242-248.
Mahalanobis, P.C. (1936). On the Generalized Distance in Statistics.Proc. Natl. Scence. India B. (2): 49- 55.
Nwangburuka, C. C. (2010). Morphological characterization and genetic studies in okra Abelmoschusesculentus (L.)Moench. Ph.D. Thesis submitted to Federal University of Agriculture, Abeokuta, Nigeria.
Nwofia, J. E., Amajuoyi, A.N. andMbah, E.U. (2015). Response of three cucumber varieties (CucumussativusL.) to planting season and NPK fertilizer rates in lowland humid tropics, sex expressions, yield and inter-relationship between yield and associated traits. International Journal of Agriculture and Forestry.5(1): 30-37.
Pan, R.S., Singh, A.K., Kumar, S., and Rai, M. (2009) Studies on genetic divergence in lablab bean through principal analysis. Ind J Hort. 66: 483-487.
Pandit, M.K. and Hazra, P. (2008).Pointed gourd. In: Rana, M.K. ed. Scientific cultivation of vegetables. New Delhi, Kalyani Publication. pp. 218-228.
Pearson, K. (1901). On lines and planes of closest fit to systems of point in space. Philosophical Magazine, (2): 559-572.
Ramanujam, S., Tiwary, A.S. and Mehra, R.B. (1974).Genetic divergence and hybrid performance in mungbean.Theor. Appl. Genet. 44.(5): 211-214.
SAS Institute (2011). SAS enterprise guide, Version 9.2. SAS Inst., Cary, NC, USA.
Sharma, J.R. (1998). Statistical and biometrical techniques in plant breeding. New Age International, New Delhi.
Sharifi, P. and Aminpana, H. (2014).A study on the genetic variation in some of faba bean genotypes using multivariate statistical techniques. Trop. Agric. 91(2):87-97.
Singh, S. R., Ahmed, N., Lal, S., Ganie, S. A., Amin, M., Jan, N. and Amin, A. (2013).Determination of genetic diversity in onion (Allium cepaL.) by multivariate analysis under long day conditions.African Journal of Agricultural Research.8.(45): 5599-5606.
Srinivas, J., Kale, V. S., Nagre, P.K. and Meshram, M. (2016). Genetic divergence studies in cowpea. International Journal of Agricultural Science and Research. 6. (3): 97-104.
Sultana, S., Kawochar, M.A., Naznin, S., Raihan, H. and Mahmud, F.(2015). Genetic Divergence in Pumpkin (Cucurbita moschata L.)Genotypes.Bangladesh J. Agril.Res.40.(4): 683-692.
Syed, M.A., Islam, M.R., Alam, M.M. and Amin, M.N. (2012). Genetic divergence in chickpea (Cicer arietinum L.). Bangladesh journal of agricultural research, 37: 129-136.
Yadav, H., Maurya, S. K., and Bhatt, L. (2016).Genetic Divergence in Ridge Gourd through Principal Component and Non-Hierarchical Cluster Analysis.Environment & Ecology. 34(1A): 334-340.
Citation Format
How to Cite
Verma, P., Maurya, S. K., Yadav, H., & Panchbhaiya, A. (2017). Determination of genetic divergence in pointed gourd by principal component and non-hierarchical euclidean cluster analysis. Journal of Applied and Natural Science, 9(4), 2421–2426. https://doi.org/10.31018/jans.v9i4.1548
More Citation Formats:
Section
Research Articles