Rakesh Kumar Naresh Kaushik


Twenty three CPTs (Candidate Plus Trees) of Pongamia pinnata were selected from different agro-climatic conditions of Haryana state of India and were assessed to identify the elite planting material for improvement of the species in terms of oil content. The differences among CPTs of P. pinnata were significant for seed oil content and all growth parameters of the progenies of these CPTs at the seedling stage. Oil content in P. pinnata varied from 27.07 (P12) to 38.17% (P2). The estimates of genotypic coefficients of variation for the characters studied were less as compared to the phenotypic coefficients of variation for all the characters examined. The highest phenotypic coefficient of variation (49.33) and genotypic coefficient of variation (28.56) was recorded for the germination percentage followed by height of the first branch. Number of leaves (0.5551**), inter-nodal length (0.5580**) and number of branches (0.6182**) showed high and positive correlation with the seed oil content. The progeny number 9, 21 and 2 were found to be the best on basis of oil content (36. 37, 36.83 and 38.17 %, respectively), and other characters examined. D2 analysis grouped the CPTs into 5 clusters. The highest numbers of progenies were included in the cluster I followed by cluster III and least number of progenies i.e., two were observed in cluster II. The intra cluster distances ranged from 4.12 (cluster V) to 5.96 (cluster II). The maximum inter-cluster distance was observed between cluster II and III (10.02) followed by I and III and minimum was between clusters I and cluster V. The crosses between clusters II and III may result sufficient segregation for further improvement of the species. Therefore, the progenies belonging to the clusters II and III could be taken as parents for a successful hybridization program.


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Heritability, Pongamia pinnta, progeny, seed oil content, variability

Ali, M.S., Choudhary, S.C., Alam, I., Kumar, D., Chakraborty, A.K. and Kumar R. (2009). Pattern of variation of seedling characters in Pongamia pinnata L. (Karanja). Ind. J. Agroforestry. 11: 101-102.
AOAC. (1984). Official methods of analysis. 14th ed. Washington, DC, USA: Association of Official Analytical Chemists.
Biswas, B., Kazakoff, S. H., Jiang, Q., Samuel, S., Gresshoff, P.M. and Scott, P. T.( 2013). Genetic and genomic analysis of tree legume Pongamia pinnata as a feedstock for biofuels. The Plant Genome.6(3):1-15.
Burton, G.W. (1952). Quantitative inheritance in grasses. Proc. 7th Intl. Grassland Cong1 pp. 277 - 283.
Divakara, B.N., Alur, A.S. and Tripathi S. (2010). Genetic variability and relationship of pod and seed traits in Pongamia pinnata (L.) Pierre a potential agroforestry tree. Int. J.Plant Production. 4: 129-141.
Divakara, B.N. and Das Rameshwar. (2011).Variability and divergence in Pongamia pinnata for further use in tree improvement. J. Forestry Res. 22: 193−200.
Dorman, K.W. (1976). The Genetics and Breeding of Southern Pines. Agriculture Handbook No. 471. USDA, Washington, DC: US Forest Service.
Gera, M.., Gera, N. and Aggarwal R. (1999). Path analysis in Dalbergia sissoo Roxb. Ind. For. 7: 660-664.
Johnson, H.W., Robinson, H.F. and Comstock, R.E. (1955). Estimates of genetic and environmental variability in soybean. Agronomy Journal, 47:314-318.
Kaushik, N., Kumar, S., Kumar, K., Beniwal, R.S., Kaushik, N. and Roy, S. (2007). Genetic variability and association studies in pod and seed traits of Pongamia pinnata (L.) Pierre in Haryana, India. Genetic Resou. and Crop Evol. 54: 1827-1832.
Kesari, V., Krishnamachari, A. and Rangan, L. (2008). Systematic characterization and seed oil analysis in candidate plus trees of biodiesel plant, Pongamia pinnata. J. Annals and Appl. Biol. 152: 397-404.
Lush, J.L. (1949). Heritability of quantitative characters in farm animals. Proc. 8th Intl. Genetic Cong. Hereditas (Supp.) pp356-357.
Mukta, N., Murthy, I.Y.L.N. and Sripal, P. (2009). Variability assessment in Pongamia pinnata (L.) Pierre germplasm for biodiesel traits. J. Ind. Crops and Products. 29: 536-540.
Panse, V.G.and Sukhatme, P.V. (1978). Statistical methods for agricultural workers, ICAR, New Delhi.
Punia, M.S. Kureel, R.S. and Pandey, A. (2006). Status and potential of tree borne oilseeds (TBOs) in biofuel production of India. Ind. J. Agrofor. 8: 80-86.
Rao, G. R., Shanker, Arun K., Srinivas, I., Korwar, G. R. and Venkateswarlu, B. (2011). Diversity and variability in seed characters and growth of Pongamia pinnata (L.) Pierre accessions. Trees. 25: 725-734.
Scott, P.T., Pregelj, L., Chen, N., Hadler, J.S., Djordjevic M.A. and Gresshoff, P.M. (2008). Pongamia pinnata: An untapped resource for the biofuels industry of the future. Bioenergy Res. 1: 2-11.
Spark, D.N. (1973). Euclidean cluster analysis Algorithm. Applied Statistics, 22: 126-130.
Sunil, N., Kumar, V., Sivaraj, N., Lavanya, C., Prasad, R.B.N., Rao B.V.S.K. and Varaprasad, K.S. (2010). Variability and divergence in Pongamia pinnata (L.) Pierre germplasm – a candidate tree for biodiesel. J. Bioenergy. 1: 382-391.
Vakshasya, R.K., Rajora, O.P. and Rawat, M.S. (1992). Seed and seedling traits of Dalbergia sissoo Roxb., Progeny variation studies among ten sources in India. For. Ecology and Mgt. 48: 265-275.
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Kumar, R., & Kaushik, N. (2015). Variability for seed oil content and seedling traits in Pongamia pinnata (L.) Pierre. Journal of Applied and Natural Science, 7(2), 1036-1041. https://doi.org/10.31018/jans.v7i2.727
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