Genetic Assessment of Combining Ability for Seed-Yield and Its Related Traits in Soybean [Glycine max (L.) Merrill]

DOI: 10.18805/LR-542    | Article Id: LR-542 | Page : 21-25
Citation :- Genetic Assessment of Combining Ability for Seed-Yield and Its Related Traits in Soybean [Glycine max (L.) Merrill].Legume Research.2021.(44):21-25
Gbemisola Oluwayemisi Ige, Godfree Chigeza, Subhash Chander, Abebe Tesfaye Abush, David Kolawole Ojo, Malachy Akoroda igegbemi@gmail.com
Address : International Institute of Tropical Agriculture, SARAH Campus, Lusaka, Zambia. Subhash Chander, Department of Genetics and Plant Breeding, CCS Haryana Agricultural University, Hisar 125004, Haryana, India.
Submitted Date : 12-12-2019
Accepted Date : 18-03-2020


Crosses were made in line × tester mating design between a set of five IITA soybean released varieties and three plant introduced (PI) accessions obtained from World Vegetable Center, Taiwan. In order to produce sufficient seeds, F1 crosses were selfed, subsequently F2 populations along with their parents were planted in a randomized complete block design at two locations in Nigeria with three replications. Agronomic traits viz. days to flowering, days to poding, plant height, number of pods/plant and seed yield/plant were measured. Testers and lines showed significant differences for all the measured traits except days to flowering for testers. Considering the significance and magnitude of general combining ability (GCA) effect, line TGx 1988-5F was observed desirable for earliness, while line TGx 1989-19F was the best combiner for number of pods/plant and seed yield/plant. On the other hand, best tester for seed yield was PI 230970. Crosses TGx 1835-10E × PI 459025B and TGx 1987-62F × PI 459025B had significant and highest SCA effect for seed yield/plant. These two crosses appeared to be most promising for soybean yield improvement programme.


General combining ability Line × Tester Soybean Specific combining ability


  1. Agrawal, A.P., Salimath, P.M., Patil, S.A. (2005). Gene action and combining ability analysis in soybean [Glycine max (L.) Merrill]. Legume Research. 28(1): 7-11.
  2. Balasubramaniyan, P. and Palaniappan, S.P. (2003). Principles and practices of agronomy India: Agrbios pp 45-46.
  3. Bastawisy, M.B., Eissa, M.S., Ali, K.A., Mansour, S.H., Ali, M.S. (1997). Gene effect and heritability in soybean [Glycine max (L.) Merrill]. Annals of Agricultural Science. 35(1): 15-24
  4. Chander, S., Ortega-Beltran, A., Bandyopadhyay, R., Sheoran, P., Ige, G.O., Vasconcelos, M.W., Garcia-Olivera, A.L. (2019). Prospects for durable resistance against an old soybean enemy: A four-decade journey from Rpp1 (Resistance to Phakopsora pachyrhizi) to Rpp7. Agronomy. 9(7): 348-361.
  5. Dar, S.H., Rather, A.G., Ahanger, M.A., Talib, S. (2014). Gene action and combining ability studies for yield and component traits in rice (Oryza sativa L.): A Review. Journal of Plant and Pest Science. 1(3): 110-127.
  6. De Almeida Lopes, A.C., Vello, N.A., Pandini, F. (2001). Seed yield combining ability among soybean genotypes in two locations. Crop Breeding and Applied Biotechnology. 1(3): 221-228.
  7. Durai, A.A. and Subbalakshmi, B. (2009). Diallel analysis in vegetable soybean. Indian Journal of Horticulture. 66(2): 274-276.
  8. FAO. (2017). Regional Overview of Food Security and Nutrition in Africa 2017. The food security and nutrition–conflict nexus: building resilience for food security, nutrition and peace. Accra. Accessed at http://www.fao.org/3/a-i7967e.pdf. 
  9. FAOSTAT. (2017). Retrieved from http://www.fao.org/faostat/en/#data/QC. Accessed on July 1st 2019.
  10. Felahi, Z.E., Hannachi, A., Bouzerzour, H., Boutekrabt, A. (2013). Line × Tester mating design analysis for grain yield and yield related traits in bread wheat (Triticum aestivum L.). International Journal of Agronomy. 2013: 1-9.
  11. Gadag, R.N., Upadhyaya, H.D., Gaud, G.V. (1999). Genetic analysis of yield, protein, oil and other related traits in soybean. Indian Journal of Genetics and Plant Breeding. 59(4): 487-492.
  12. Kempthorne, O. (1957). An Introduction to genetic statistics. John Wiley and Sons, Inc. New York, USA pp 468-473.
  13. Mebrahtu, T. and Devine, T.E. (2008). Combining ability analysis for selected green pod yield components of vegetable soybean genotypes (Glycine max). New Zealand Journal of Crop and Horticultural Science. 36(2): 97-105.
  14. Nath, A., Maloo, S.R., Nath, S., Chakma, A., Verma, R., Yadav, G.S. (2018). Genetical studies on assessment of combining ability for grain yield and yield attributing traits in green gram [Vigna radiata (L.) Wilczek]. Journal of Pharmacognosy and Phytochemistry. 7(2): 2562-2566.
  15. Pandini, F., Vello, N.A., Lopes, A.C.D.A. (2002). Heterosis in soybeans for seed yield components and associated traits. Brazilian Archives of Biology and Technology. 45 (4): 401-412.
  16. Popoola, T.O.S. and Akueshi, C.O. (1986). Nutritional evaluation of daddawa, a local spice made from soybean (Glycine max). MIRCEN Journal of Applied Microbiology and Biotechnology. 2(3): 405-409.
  17. Raut, V.M., Taware, S.P., Halvankar, G.B. (2000). Gene effects for some quantitative characters in soybean crosses. Indian Journal of Agricultural Sciences. 70(5): 334-335.
  18. SAS, Statistical Analysis System Institute, Inc. (2000). SAS Proprietary Software 9.4 SAS Institute Inc., Cary, North Carolina.
  19. Schonfeldt, H.C. and Hall, N.G. (2012). Dietary protein quality and malnutrition in Africa. British Journal of Nutrition. 108(S2): S69-S76.
  20. Sharma, S.R. and Phul, P.S. (1994). Combining ability analysis in soybean. Indian Journal of Genetics and Plant Breeding. 54(3): 281-286.
  21. Sood, V.K., Rana, N.D., Gupta, V.P. (2000). Combining ability and gene action for seed yield and its components in soybean [Glycine max (L.) Merrill]. Indian Journal of Genetics and Plant Breeding. 60(2): 247-250.
  22. Tadesse, G., Sentayehu, A., Asnake F. (2016). Combining ability studies for yield and yield components in selected soybean lines. International Journal of Current Agricultural Sciences. 6(7): 71-73.

Global Footprints