Estimation of Genetic Variability, Correlations and Path Coefficients for Seed Yield Contributors in Castor (Ricinus communis L.)

Document Type : Short Communication

Authors

1 Research Operation Department, National Cereals Research Institute (NCRI), Badeggi, PMB 8, Bida, Nigeria.

2 National Centre for Genetic Resources and Biotechnology, North Central Outstation, PMB 8, Bida, Nigeria.

Abstract

Castor is one of neglected African oil crops with little research attention in Nigeria. In the present research, eighty-six castor genotypes were evaluated at three locations in Niger State, Nigeria. The aim was to estimate the extent of genetic variability and also to examine the associations among the seed yield and its components. The treatments were laid out in an Alpha Lattice Design with three replications. The results revealed significant effects of genotypes on most of the studied traits. Days to 50% flowering ranged between 34 days and 125 days, and had a mean of 69.21 days. The minimum of 7.33 g and maximum of 64.12 were recorded for 100 seed weight. Seed yield ranged from 144.45 Kgha-1 to 1 349.92 Kgha-1 with the average yield of 646.04 Kgha-1. Spike length and 100 seeds weight showed a high Genotypic Coefficient of Variation (GCV) and also high Phenotypic Coefficient of Variation (PCV). Significant positive correlations were observed between the seed yield and plant height at flowering, branches per plant, length of spike, spike per plant, days to maturity and 100 seeds weight. The path coefficient analysis revealed positive direct effects of seedling establishment, spike length, spikes per plant, plant height at first raceme maturity, days to first raceme maturity and 100 seeds weight on the seed yield. Highest positive direct effect on seed yield was recorded in spike length, followed by spikes per plant and seed weight, respectively. Significant positive correlations and high positive direct effect were observed between spike length, spikes per plant and seed weight. The findings revealed the importance of spike characters for the selection of desirable castor genotypes for increased seed yield.

Keywords

References

Allan G., Williams A., Rabinowicz P. D., Chan A. P., Ravel J., and Keim, P. (2008). Worldwide genotyping of castor bean germplasm (Ricinus communis L.) using AFLPs and SSRs. Genetic Resources and Crop Evolution, 55 (3):365-378. Doi: 10.1007/s10722-007-9244-3.
Akintunde A. N. (2012). Path analysis step by step using excel. Journal of Technical Science and Technologies, 1(1): 9-15.
Ani, A. O., and Okorie, A. U. (2009). Response of broiler finishers to diets containing graded levels of processed castor oil bean (Ricinus communis L.) meal. Journal of Animal Physiology and Animal Nutrition, 93(1): 157–164.
Aswani K., Sangwan R. S., and Jatasra D. S. (2003). Correlations and path analysis in castor (Ricinus communis L) under dry land conditions. Indian Journal of Dry Land Agricultural Research and Development, 18: 89–91.
Deepika B., and Tummala, P. R. (1981). Correlations and path coefficient analysis in castor (Ricinus communis L). Canadian Journal of Genetics and Cytology, 23(3): 525–531.
Gana A. K. (2015). Agronomy of castor. Bida, Khalifa Press, Nigeria, 10–34.
Gana A. K., Yusuf A. F. and Apuyor B. (2013). Castor oil plant and its potential intransformation and industrialization of under developing nations in the world. Advanced Journal of Agricultural Research, 1(5): 072–079.
Golakia P. R., Poshiya1 V. K., and Monpara B. A. (2015). Identification of superior donor parents for earliness through combining ability in castor. International Journal of Research in Plant Science, 5(3): 26-31.
Golakia P. R., Kavani R. H., and Monpara B. A. (2007). Genetic variation and trait relationship in castor. National Journal of Plant Improvement, 9: 60-62.
Gomez K. A., and Gomez A. A. (1984). Statistical procedures for agricultural research. A Wiley-interscalene Publication John Wiley & Sons, New York, 19-87.
Ibeagha O. A., and Onwualu A. P. (2015). Strategies for improving the value chain of castor as an industrial raw material in Nigeria. Agric Engineering International CIGR Journal, 17(3): 217 – 230.
India (2004). National Guidelines for the Conduct of Tests for Distinctness, Uniformity and Stability of Castor (Ricinus communis L.). Retrieved from Indian Plant Authority 
Gautam P. L. (2010-2011). Protection of plant varieties & farmers’ rights authority-Annual Report. Department of Agriculture & Cooperation, Ministry of Agriculture, Government of India NASC Complex, DPS Marg, New Delhi, pp. 100. http://www.plantauthority.gov.in/pdf/annualreport_10-11esum.pdf.
Laureti D. (1988). Genotype-environment interaction and stability of castor (Ricinus communis L.) cultivars. Agricoltura Ricerca, 10(89): 39-42.
Lima R. I. S., Severino L. S., Sampaio I.R., Sofiatti V., Gomes J. A., and Beltrao N. E. M. (2011). Blends of castor meal and husks for optimized use as organic fertilizer. Indian Journal of Crops Production, 33(1): 364 – 368.
Mutlu H., and Meier M. A. R. (2010). Castor oil as a renewable resource for the chemical industry. European Journal of Lipid Science Technology, 112(1): 10 - 30.
Ogunniyi D. S. (2006). Castor Oil: A vital industrial raw material. Bioresource Technology, 97(9): 1086–1091.
Patel P. S., and Jaimini S. N. (1988). Variability in castor. Indian Journal of Agricultural Science, 58: 394-396.
PBTools, version 1.4. (2014). Biometrics and Breeding Informatics, PBGB Division, International Rice Research Institute, Los Baños, Laguna.
Ramesh T., and Venkate S. (2001). Path coefficient analysis in castor. Agricultural Science Digest, 21: 59-60.
Rao P. V. R.., Giri V. G., and Pachauri D. K. (2006). Evaluation of castor (Ricinus communis L.). Research on Crops, 10: 696 – 698.
Robert E. K., and Raftery A. E. (1995). Bayes Factors. Journal of the American Statistical Association, 90(430): 773-795.
Shivanna S. (2008). Genetic diversity, combining ability and stability analysis of selected castor lines. PhD thesis submitted to the University of Agricultural Sciences, Bangalore, 28-45
Torres F. E., Teodoro P. E., Ribeiro L. P., Correa C. C. G., Hernandes F. B., Fernandes R. L., Gomes A. C., and Lopes K. V. (2015). Correlations and path analysis on oil content of castor genotypes. Bioscience Journal, 31(5): 1363 – 1369.
Zheng L., Qi J. M., Fang P. P., Su J. G., Xu J. T., and Tao, A. F. (2010). Genetic diversity and phylogenetic relationship of castor as revealed by SRAP analysis. Wuban Zhiwuxue, 28: 1-6. (In Chinese with English abstract).

Files

History

  • Receive Date: 12 February 2019
  • Revise Date: 13 May 2019
  • Accept Date: 13 July 2019

Share

How to cite

Statistics