TRAIT ASSOCIATION AND CONSTRUCTION OF SELECTION INDICES IN RICE (Oryza sativa L.) UNDER AEROBIC CONDITION

CHANDRASHEKHAR HARADARI¹*, SHAILAJA HITTALMANI^2
1Department of Genetics and Plant Breeding, University of Agricultural Sciences, Bangalore, 560 065, Karnataka, India
²Department of Genetics and Plant Breeding, University of Agricultural Sciences, Bangalore, 560 065, Karnataka, India
* Corresponding Author : chandugpb@gmail.com

Received : 30-05-2017     Accepted : 06-06-2017     Published : 30-06-2017
Volume : 9     Issue : 30       Pages : 4416 - 4421
Int J Agr Sci 9.30 (2017):4416-4421

Keywords : Selection index, Correlation, Relative efficiency, Grain yield, Aerobic rice
Academic Editor : Sood Salej, Ajay B. C.
Conflict of Interest : None declared
Acknowledgements/Funding : We would like to express our sincere thanks to MASLAB, Department of Genetics and Plant Breeding, University of Agricultural Sciences, Bangalore, 560 065, Karnataka, India for the facilities provided in conducting the research experiments and Kirkhouse Trust, United Kingdom for their financial support followed by scientific guidance
Author Contribution : All author equally contributed

Present investigation including 46 F3 families of rice were evaluated under aerobic condition during 2013, with an objective of tracing the relationship between yield component characters followed by construction of selection indices. Among yield component characters viz., productive tillers per plant (X1), single panicle weight (X2), spikelet fertility (X3), biomass (X4) and harvest index (X5) exhibited highly significant positive correlation coefficients with high direct effects on grain yield per plant (X6) indicating selection based on these characters could be very effective for yield and the same were considered to construct selection indices. Sixty three selection indices involving grain yield per plant and five yield component characters were constructed using discriminant function analysis and selection efficiency of the function was improved by increasing number of characters in the index. Among single character index, spikelet fertility exhibited higher genetic gain (49.41) and relative efficiency (1138.48%) over straight selection for grain yield. Whereas selection indices with six, five and four character combinations recorded highest genetic advance (79.56, 73.99 and 71.63 resp.) as well as relative efficiency (1833.09%, 1704.91% and 1650.65% resp.). F3 families viz., 23-5-108, 23-5-315 and 23-5-277 were found superior based on index score estimates. Practically, index with minimum characters could be advantageously exploited and advocated for selecting high yielders in rice.

1. Li J., Zhang H., Wang D., Tang B., Chen C., Zhang D., Zhang M., Duan J., Xiong H. and Li Z. (2011) POJ, 4(6), 302-317.
2. Bernier J., Atlin G. N., Serraj R., Kumar A. and Spaner D. (2008) J. Sci. Food. Agric., 88, 927-939.
3. UN Food and Agriculture Organization, Corporate Statistical Database (FAOSTAT). 2017.
4. Ministry of Agriculture & Farmers Welfare (2015) Agricultural statistics at a glance, GOI, New Delhi.
5. Girish T. N., Gireesha T. M., Vaishali M. G., Hanamareddy B. G. and Hittalamni S. (2006) Euphytica, 152, 149-161.
6. Kahani F. and Hittalmani S. (2016) SABRAO J. Breed. Gen., 48(2), 219-229.
7. Lerner M. (1958) The genetic basis of selection. John Willey and Sons Inc. New York.
8. Habib S. H., Iftekharuddaula K. M., Bashar M. K., Akter K. and Hossain M. K. (2007) Bangladesh J. Pl. Breed.Genet., 20(1), 25-32.
9. Kacchadia V. H., Baraskar V. V., Vacchani J. H., Barad H. R., Patel M. B. and Darwankar M. S. (2014) Electron. J. Plant Breed.,5(2), 268-271
10. Ahmad E. and Ansari A. M. (2016) Ann. Agric. Res. New Series, 37(1), 100-106.
11. IRRI (1996) Standard evaluation system for rice.4th edition, pp-17-18.
12. Webber C. R. and Moorthy B. R. (1952) Agron. J., 4, 202-209.
13. Snedecor G. W. (1961) Statistical methods. The Iowa State University Press, Acer, Iowa, USA.
14. Wright S. (1921) J. Agric. Res., 20, 557-585.
15. Dewey D. R. and Lu K. H. (1959) Agron, J., 51, 515-518.
16. Smith H. F. (1936) Ann. Eugen., 7, 240-250.
17. Fisher R. A. (1936) Ann. Eugen., 7, 87-104.
18. Robinson H. F., Comstock R. E. and Harvey V. H. (1951)Agron. J., 41, 353-359.
19. Brim C. A., Johnson H. W. and Cockerham C. C. (1959) Agron. J., 51, 42-46.
20. Gopalan M. and Ganesh S. K. (2013) Indian J. Sci. Tech., 6(9), 5223-5227.
21. Alam M. S., Islam M. M., Hassan L., Begum S. N. and Gupta R. (2014)Int. J. Inn. App. Stu., 8,1329-1338.
22. Kahani F. and Hittalmani S. (2015)J. Rice Res.,3, 152. doi:10.4172/2375-4338.1000152.
23. Boopathi N. M., Swapnashri G., Kavitha P., Sathish S., Nithya R., Ratnam W. and Kumar A. (2013) Rice sci., 20(1), 25-30.
24. Ramanjaneyulu A.V., Gourishankar V., Neelima T. L. and Shashibhushan D. (2014) SABRAO J. Breed. Gen., 46(1), 99-111.
25. Basavaraja T., Gangaprasad S., DhusyanthaKumar B. M. and Hittlamani S. (2011) Electron. J. Plant Breed., 2(4), 523-526.
26. Haider Z., Khan A. S. and Zia S. (2012) Amer-Eurasian J. Agric. & Environ. Sci., 12(1), 100-104.
27. Hazel L. N. and Lush J. L. (1943) J. Heredity, 33, 393-399.
28. Purohit S. and Majumder M. K. (2009) Middle East J. of Scientific res., 4(1), 28-31.
29. Akter S., Biswas B. K., Azad A. K., Hasanuzzaman M. and Arifuzzaman M. (2010) Int. J. Sustain. Crop Prod., 5(4), 30-35.