, Volume 22, Issue 5, pp 697–709 | Cite as

Genetic associations, variability and diversity in seed characters, growth, reproductive phenology and yield in Jatropha curcas (L.) accessions

  • G. R. Rao
  • G. R. Korwar
  • Arun K. Shanker
  • Y. S. Ramakrishna
Original Paper


A thorough and extensive wild germplasm exploration survey was undertaken and 32 high yielding candidate plus trees (CPTs) of Jatropha curcas from different locations from a latitudinal and longitudinal spread between 12°41′ and 22°′E longitude and 77° and 84°40′N latitude covering 11 locations in an area spread of 150,000 km2 was collected for evaluating genetic association, and variability in seed and growth characters. Significant trait differences were observed in all the seed characters viz., seed morphology and oil content as were observed in growth characters viz., plant height, and female to male flower ratio and seed yield in the progeny trial. Broad sense heritability was high in general and exceeded 80% for all the seed traits studied. Female to male flower ratio showed near to 100% heritability followed by yield (83.61) and plant height (87.73). The path analysis revealed that female to male flower ratio had highest positive direct relationship with seed yield (0.789), followed by number of branches (0.612) and number of days from fruiting to maturity (0.431). Negative indirect effects were seen in number of days from flowering to fruiting which indirectly and negatively influenced yield through plant height and number of branches. Hierarchical clustering by Ward’s minimum variance cluster analysis showed phylogeographic patterns of genetic diversity. K-means clustering revealed that trees from different geographic regions were grouped together in a cluster and as were trees from the same geographical area placed in different clusters suggesting that geographical diversity did not go hand in hand with genetic diversity. In addition clustering identified promising accession with favourable traits for future establishment of elite seedling seed orchard and clonal seed orchard for varietal and hybridization programmes.


Biodiesel Diversity Germplasm Phylogeography 



Acknowledgements are due to Indian Council of Agricultural Research for financial support for the project through Agricultural Products Cess Fund Ad Hoc Scheme Grant No F·No. 5-28/2003-SW and DF dated: 9th February 2004, Code No. 0871005


  1. Agarwal AK (2007) Biofuels (alcohols and biodiesel) applications as fuels for internal combustion engines. Prog Eng Combust Sci 33:233–271CrossRefGoogle Scholar
  2. Baenziger SP, Gregory S, McMaster R, Wilhelm WW, Weiss A, Hays CJ (2004) Putting genes into genetic coefficients. Field Crops Res 90:133–143CrossRefGoogle Scholar
  3. Bhargava A, Shukla S, Ohri D (2007) Genetic variability and interrelationship among various morphological and quality traits in quinoa (Chenopodium quinoa Wild.). Field Crops Res 101:104–116CrossRefGoogle Scholar
  4. Carlowitz Von PGL (1986) Defining ideotypes of multipurpose trees for their phenotypic selection and subsequent breeding. In: Proceedings of the international workshop on biological diversity and genetic resources of underexploited plants. Kew, 14.Google Scholar
  5. Cornelius J (1994) The effectiveness of plus-tree selection for yield. For Ecol Manage 67:23–34CrossRefGoogle Scholar
  6. Costa RB, Rego D, Contini FLH, Moreno AZ, Rondelli KG, Kumimoto H (2005) Genetic variability and heritability estimates for the germination trait in Albizia lebbeck parent trees. Ciênc Rural 35:1209–1212Google Scholar
  7. De Rodrguez DJ, Angulo-Sanchez JL, Rodrguez-Garca R (2001) Correlation and path coefficient analyses of the agronomic trait of a native population of guayule plants. Ind Crops Prod 14:93–103CrossRefGoogle Scholar
  8. Dierig DA, Rayb DT, Coffelta TA, Nakayamaa FS, Leakea GS, Lorenzc G (2001) Heritability of height, width, resin, rubber, and latex in guayule (Parthenium argentatum). Ind Crops Prod 13:229–238CrossRefGoogle Scholar
  9. El Amin YR, Luukkanen O (2006) Adaptive genetic variation in water-use efficiency and gum yield in Acacia senegal provenances grown on clay soil in the Blue Nile region. Sudan For Ecol Manage 226:219–229CrossRefGoogle Scholar
  10. Eriksson O (1999) Seed size variation and its effect on germination and seedling performance in the clonal herb Canvallaria majalis. Acta Oecol 20:61–66CrossRefGoogle Scholar
  11. Falconer DS, MacKay TFC (1996) Introduction to Quantitative Genetics. Chapman & Hall, LondonGoogle Scholar
  12. Ginwal HS, Phartyal SS, Rawat PS, Srivastava RL (2005) Seed source variation in morphology, germination and seedling growth of Jatropha curcas Linn., in Central India. Silvae Genet 54:76–80Google Scholar
  13. Goel VL, Behl HM (2001) Genetic selection and improvement of hard wood tree species for fuelwood production on sodic soil with particular reference to Prosopis juliflora. Biomass Bioenerg 20:9–15CrossRefGoogle Scholar
  14. Johansson AK, Kuusisto PH, Laakso PH, Derome KK, Sepponen PJ, Katajisto JK, Kallio HP (1997) Geographical variations in seed oils from Rubus chamaemorus and Empetrum nigrum. Phytochemistry 44:1421–1427CrossRefGoogle Scholar
  15. Karon′ ski M, Calin′ ski T (1973) Grouping in multivariate populations on the basis of Euclidean distances. Algor Biometr Stat 17:117–129Google Scholar
  16. Kaura SK, Gupta SK, Chowdhury JB (1998) Morphological and oil content variation in seeds of Azadirachta indica A. Juss. (Neem) from northern and western provenances of India. J Plant Foods Hum Nutr (Formerly Qualitas Plantarum) 52:132–136Google Scholar
  17. Kaushik N, Kumar K, Kumar S, Roy S (2007) Genetic variability and divergence studies in seed traits and oil content of Jatropha (Jatropha curcas L.) accessions. Biomass Bioenerg 31:497–502CrossRefGoogle Scholar
  18. O’Neill CM, Gill S, Hobbs D, Morgan C, Bancroft I (2003) Natural variation for seed oil composition in Arabidopsis thaliana. Phytochemistry 64:1077–1090PubMedCrossRefGoogle Scholar
  19. Openshaw K (2000) A review of Jatropha curcas: an oil plant of unfulfilled promise. Biomass Bioenerg 19:1–15CrossRefGoogle Scholar
  20. Pliura A, Zhang SY, MacKay J, Bousquet J (2007) Genotypic variation in wood density and growth traits of poplar hybrids at four clonal trials. For Ecol Manage 238:92–106CrossRefGoogle Scholar
  21. Sachan JN, Parshuram S, Singh B, Pattnaik RK (2004) Analysis of genetic divergence for quality improvement in toria (Brassica rapa L. spp.toria). Environ Ecol 22:283–286Google Scholar
  22. Sokal RR, Rohlf TJ (2003) Biometry: the principles and practice of statistics in biological research. 8th Printing. W·H Freeman, San FranciscoGoogle Scholar
  23. Tams SH, Bauer E, Oettler G, Melchinger AE, Schön C (2006) Prospects for hybrid breeding in winter triticale: II. Relationship between parental genetic distance and specific combining ability. Plant Breed 125:331–336CrossRefGoogle Scholar
  24. Tefera H, Assefa K, Hundera F, Kefyalew T, Teferra T (2003) Heritability and genetic advance in recombinant inbred lines of tef (Eragrostis tef). Euphytica 131:91–96CrossRefGoogle Scholar
  25. van Osteroma EJ, Weltzienb E, Yadav OP, Bidingerb FR (2006) Grain yield components of pearl millet under optimum conditions can be used to identify germplasm with adaptation to arid zones. Field Crops Res 96:407–421CrossRefGoogle Scholar
  26. Vollmann J, Moritz T, Kargl C, Baumgartner S, Wagentrist H (2007) Agronomic evaluation of camelina genotypes selected for seed quality characteristics. Ind Crops Prod (in Press, corrected proof, available online)Google Scholar
  27. Wanyancha M, Mills WR, Gwaze DP (1994) Genetic variation in Acacia albida (Faidherbia albida) and its agroforestry potential in Zimbabwe. Forest Ecol Manage 64:127–134CrossRefGoogle Scholar
  28. Ward JH (1963) Hierarchical grouping to optimize an objective function. J Am Stat Assoc 58:236–244CrossRefGoogle Scholar
  29. Wilkinson L, Hill M, Welna JP, Birkenbevel BK (1996) Systat for windows, 6th edn. SPSS, EvanstonGoogle Scholar
  30. Yoshida H, Takeshi H, Katsura K, Tatsuhiko S (2007) A model explaining genotypic and environmental variation in leaf area development of rice based on biomass growth and leaf N accumulation. Field Crops Res 102:228–238CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2008

Authors and Affiliations

  • G. R. Rao
    • 1
  • G. R. Korwar
    • 1
  • Arun K. Shanker
    • 2
  • Y. S. Ramakrishna
    • 1
  1. 1.Natural Resource ManagementCentral Research Institute for Dryland Agriculture (CRIDA)HyderabadIndia
  2. 2.Crop SciencesCentral Research Institute for Dryland Agriculture (CRIDA)HyderabadIndia

Personalised recommendations