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Studies on Character Association and Genetic Divergence in White Jute (Corchorus capsularis L.)

DOI: 10.18805/IJARe.A-5437    | Article Id: A-5437 | Page : 187-191
Citation :- Studies on Character Association and Genetic Divergence in White Jute (Corchorus capsularis L.).Indian Journal of Agricultural Research.2021.(55):187-191
Sayan Jana, Nitesh Kumar, Subhra Mukherjee, Prabir Kumar Bhattacharyya, Gouranga Sundar Mandal, Sitangshu Ghoshal niteshkumar310@gmail.com
Address : Department of Genetics and Plant Breeding, Bidhan Chandra Krishi Viswavidyalaya, Mohanpur-741 252, West Bengal, India.
Submitted Date : 25-10-2019
Accepted Date : 1-09-2020

Abstract

Background: In white jute, very limited success has been reported by researchers to break yield plateau due to the narrow genetic base of the genetic material available with the breeders. Evaluation of agronomic traits and information about genetic variance in the breeding population is essential for selection and in planning crosses to enhance the productivity and diversity in cultivars. Yield character components are inherited and each one accounts for variations in yield, hence interrelated with each other. The current investigation was done to measure the genetic variability and genetic diversity of white jute genotypes for characters and interrelationship that contribute to yield and fibre quality.
Methods: In the present study, fifty-two white jute (C. capsularis L.) genotypes were assessed during the Pre-Kharif season of 2017 at the Teaching Farm of Bidhan Chandra Krishi Viswavidyalaya, Mandouri, Nadia, West Bengal. Plants were raised in randomized block design with three replications. Statistical analysis was done for the estimation of ANOVA variability, correlation and path analysis and genetic divergence.
Result: Plant height and bark thickness with high heritability and high genetic advance were identified as important selection parameters. Plant height, bark thickness and green weight per plant had a significantly high positive correlation with dry fibre weight per plant both at genotypic and phenotypic levels. Plant height had the highest contribution toward the dry fibre weight followed by bark thickness. Genotypes were grouped into 13 clusters and cluster I had the highest number of 23 genotypes. The inter-cluster distance was found maximum between cluster I and cluster VI. Cluster XI recorded the highest mean for the plant height. Ten genotypes identified from different clusters in this study can be incorporated as donors in hybridization to combine both yield and improved fibre quality.

Keywords

Correlation analysis Genetic diversity Genetic variability Heritability Path coefficient analysis White jute

References

  1. Das A. and Kumar D. (2016). Genetic divergence and character association for yield and quality attributing characters in tossa jute (Corchorus olitorius L.). Electronic Journal of Plant Breeding. 7(3): 529-537.
  2. Dewey, D.R. and Lu, K.H. (1959). A correlation and path coefficient analysis of components of crested wheat grass seed production. Agronomy Journal. 51: 515-518.
  3. Islam, M.R., Islam, M.M., Akter, N. and Ghosh, R.K. (2002). Genetic variability and performance of tossa jute. Pakistan Journal of Biological Science. 5(7): 744-745.
  4. Islam, M.S., Uddin, M.N., Haque, M.M. and Islam, M.N. (2001). Path coefficient analysis for some fibre yield related traits in white jute (Corchorus capsularis L.). Pakistan Journal of Biological Science. 4(1): 47-49.
  5. Kar, C.S., Kundu, A., Sarkar, D., Sinha, M.K. and Mahapatra, B.S. (2009). Genetic diversity in jute (Corchorus spp.) and its utilization: A review. Indian Journal of Agricultural Sciences. 79(8): 578-586.
  6. Panse, V.G. and Sukhatme, P.V. (1989). Statistical Methods for Agricultural Workers. Indian Council of Agricultural Research, New Delhi, India.
  7. Pervin, N. and Haque, G.K.M.N. (2012). Path coefficient analysis for fibre yield related traits in deshi jute (Corchorus capsularis L.). International Research Journal of Applied Life Sciences. 1(3): 72-77.
  8. Rao, C.R. (1952). Advanced statistical methods in biometrical research, John Wiley & Sons, Inc, New York, pp. 357-363.
  9. Senapati S., Ali M.N and Sasmal, B.G. (2006). Genetic Variability. Heritability and Genetic advance in Corchorus Sp. Environment and Ecology. 24S(1):1-3.
  10. Singh, R.K. and Chaudhury, B.D. (1985). Biometrical methods of quantitative genetic analysis. Kalyani Publishers, New Delhi, India.

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