SINGLE MARKER ANALYSIS FOR MORPHO-PHYSIOLOGICAL PARAMETERS IN PIGEONPEA

R.M. BASAVARAJESHWARI¹, K.N. GEETHA², A.G. SHANKAR³*
¹Department of Crop Physiology, University of Agricultural Sciences, GKVK, Bengaluru, 560065, India
²Department of Agronomy, University of Agricultural Sciences, GKVK, Bengaluru, 560065, India
³Department of Crop Physiology, University of Agricultural Sciences, GKVK, Bengaluru, 560065, India
* Corresponding Author : ambara8@hotmail.com

Received : 16-07-2019     Accepted : 26-07-2019     Published : 30-07-2019
Volume : 11     Issue : 14       Pages : 8785 - 8787
Int J Agr Sci 11.14 (2019):8785-8787

Keywords : Morpho-physiological traits, Pigeonpea, Single marker analysis, Marker assisted selection breeding
Academic Editor : Vinod S Kukanur
Conflict of Interest : None declared
Acknowledgements/Funding : Authors are thankful to Department of Biotechnology, Govt of India for funding this research. Authors are also thankful to University of Agricultural Sciences, GKVK, Bengaluru, 560065, India
Author Contribution : All authors equally contributed

Morpho-physiological parameters play an important role in determining the yield in pigeonpea under normal as well as stress conditions. The objective of the study was to identify the SSR markers linked with the morpho-physiologycal traits in F3 generation of pigeonpea. Plant height, Stalk weight, number of branches, pod length, pod width, SCMR, stem girth and seed yield were the morpho-physiological traits measured under this study. Around 100 SSR markers were employed to screen 188 F3 lines. Seven markers were found to be linked to various traits measured in the mapping population of pigeonpea. Hence these markers may be useful in marker assisted selection breeding programme.

1. Gowda C. L. L., Upadhyaya H. D., Sharma S., Varshney R. K. and Dwivedi S. L. (2013) The Plant Genome, 6, 1-11.
2. Aruna Talari and Devindra Shakappa (2018) Asian J. Dairy & Food Res, 37(3), 212-220
3. Saxena K.B. (2008) Tropical Plant Biology, 1,159-178
4. Ender M., Terpstra K., Kelly J.D. (2008) Mol. Breed., 21, 149-157.
5. Hospital F. (2009) Genetica, 136, 303-310.
6. Srivastava P.P., Kar P.K., Awasthi A.K., Urs S.R. (2007) Rus. J. Genet., 43, 858-864.
7. Maureira-Butler I.J., Udall J.A., Osborn T.C. (2007) Theor. Appl. Genet., 115, 859-867
8. Dutta S., Kumawat G., Singh B. P., Gupta D. K., Singh S., Dogra V., Gaikwad K., Sharma T. R., Raje R. S., Bandhopadhya T. K., Datta S., Singh M. N., Bashasab F., Kulwal P., Wanjari K. B., Varshney R. V., Cook D. R. and Singh N. K. (2011) BMC Plant Biology, 2011, 11,17.
9. Dutta S., Ajay K., Mahato, Sharma P., Raje R. S., Sharma T. R. AND SINGH N. K. (2013) Plant Breeding, 132, 191–196.
10. Tanksley S. D., Medina-Filho H. and Rick C. M. (1982) Heredity, 48,11-25.
11. Suresh K., Bhadauria H.S., Satish K. and Neetu S. (2016) International Journal of Agriculture Sciences, 8(60), 3367-3370
12. Saumya Ranjan Barik, Elssa Pandit, Shakti Prakash Mohanty, Sharat Kumar Pradhan and Trilochan Mohapatra (2019) bioRxiv 590075 preprint.
13. Liu B. H. (2017) Statistical Genomics, Linkage, mapping and QTL Analysis. CRC Press, Clevel and Boca Raton, FL, eBook ISBN 9780203738658
14. Coffman C. J., Doerge R. W., Wayne M. L. and Mcintyre A. (2003) BMC Genet., 4, 10-29.
15. Anandhan T., Manivannan N., Vindhiyavarman P. and Jeyakumar P. (2010) Electronic Journal of Plant Breeding, 1(4), 1227-1234.