Cultivar identification and diversity analysis based on morphological descriptors and image analysis in chickpea (Cicer arietinum L.)
 

DOI: 10.18805/lr.v0i0.7839    | Article Id: LR-3780 | Page : 647-655
Citation :- Cultivar identification and diversity analysis based on morphological descriptors and image analysis in chickpea (Cicer arietinum L.) .Legume Research-An International Journal.2018.(41):647-655

Monika A. Joshi, Divya Aggarwal and Archana Sanyal

monikakshat622@yahoo.com
Address :

Division of Seed Science and Technology, ICAR – Indian Agricultural Research Institute, New Delhi 110 012, India

Submitted Date : 16-09-2016
Accepted Date : 1-12-2016

Abstract

Thirty three genotypes of chickpea including 9 kabuli and 24 desi types were evaluated for distinctiveness based on 13 qualitative and 7 quantitative morphological DUS descriptors. In desi type, only 4 traits were polymorphic whereas, in kabuli type, only 3 were polymorphic. Identification profiles were generated on the basis of grouping and essential characters prescribed by DUS Guidelines of PPV & FR Authority. However, out of twenty four desi genotypes, distinct profiles could be created only for sixteen varieties and in kabuli type, only three out of nine genotypes could be singled out individually.  Image analysis using scanned images of flowers of desi types successfully complemented the morphological descriptors to establish genotypic identity based on differences in the petal colour intensity and venation pattern. Genetic parameters for all the quantitative traits revealed less environmental influence on the characters expression thus, signifying their utility in the varietal characterization. Seven agro-morphological traits were used to assess the variability using Ward’s Minimum Variance Cluster Analysis.  Thirty three cultivars from both types were grouped into four cluster each, however, none of the clusters contained genotypes with all the desirable traits, which could be directly selected and utilized.

Keywords

Chickpea Distinctiveness Essential characters Grouping characters Image analysis Morphological descriptors

References

  1. Ahmad, Z., Mumtaz, S.A., Nisar, M. and Khan, N. (2012) Diversity analysis of chickpea germplasm and its implications for conservation and crop breeding. Agricultural Sciences, 3 (5): 723-31.
  2. Anonymous. (2001). Protection of Plant Varieties and Farmers’ Rights Act, 2001. Act No. 53 of 2001. Enacted by Parliament of India. 
  3. Anonymous. (2007). PPV and FR Authority Specific DUS Test Guidelines for twelve notified crops-chickpea (Cicer arietinum) Plant Variety Journal of India 1: 211-216.
  4. Bicer, B.T. and Sakar, D. (2007). Comparison of exotic lines to native cultivars for agronomic and morphologic traits. Journal of Agriculture Sciences 13(3): 279-284.
  5. Birla, R. and Chauhan, A. P. S. (2015). An Efficient Method for Quality Analysis of Rice Using Machine Vision System. Journal of Advances in Information Technology 6(3): pp 140-145.
  6. Duan, L., Yang, W., Huang, C. and Liu, Q. (2011). A novel machine-vision-based facility for the automatic evaluation of yield-related traits in rice. Plant Methods 7(44): pp 1-13
  7. Falconer, D. S. (1989). Introduction to Quantitative Genetics (3rd ed.). Logman Scientific and Technical, Logman House, Burnt Mill, Harlow, Essex, England.
  8. Farshadfar, E., Mahtabi, E., Safavi, S.M. and Shabani, A. (2013). Estimation of variability and genetic parameters in chickpea (Cicer arietinum L.) genotypes International Journal of Agronomy and Plant Production 4 (10): 2612-2616.
  9. Joshi, Monika A., Aggarwal, D., Pandey, A., Bind, D. and Alam, M. W. (2015). Generation of distinct profiles of rice varieties based on agro-morphological characters and assessment of genetic divergence. Research on Crops 16(2): 311-319.
  10. Kwon, S. H. and Torrie, J. H. (1964). Heritability and interrelationship of two soybean (Glycine max L.) populations. Crop Science 4: 196-198. 
  11. Lootens, P., Waes van, J. and Carlier, L. (2007). Evaluation of the tepal colour of Begonia x tuberhybrida for DUS testing using image analysis. Euphytica 155: 135-142.
  12. Maheshwari, C. V. (2013). Machine vision technology for Oryza sativa L. International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering 2: 2893-2900.
  13. Maiti, P. and Wesche-Ebeling. (2001). Advances in Chickpea Science, Science Publishers Inc. 
  14. Makanur, B., Deshpande, V. K. and Vyakaranahal, B. S. (2013). Characterization of cowpea genotypes based on Quantitative descriptors.    The Bioscan 8: 1183-1188.
  15. Malik S.R., Shabbir,G., Zubir, M., Iqbal, S.M. and Ali, A. (2014). Genetic diversity analysis of morpho-genetic traits in desi chickpea (Cicer arietinum L.). International Journal of Agricultural Biology 16: 956 960.
  16. Mushtaq, M.A., Bajwa, M.M. and Saleem, M. (2013). Estimation of genetic variability and path analysis of grain yield and its components in chickpea (Cicer arietinum L.) International Journal of Scientific and Engineering Research. 4 (1): 1- 4.
  17. Noor, F., Ashaf, M. and Ghafoor, A. (2003). Path analysis and relationship among the quantitative traits in chickpea (Cicer arietinum L.). Pakistan Journal of Biological Sciences 6: 551-555.
  18. Patil, V.N. and Phandis, B.A. (1997). Genotypic variability and its implication in selection of gram. Journal of Maharashtra Agricultural Universities 2: 121- 123. 
  19. Sanyal, A., Joshi, M. A., Tomar, B.S. and Aggarwal, D. (2016). Phenotypic divergence for agro-morphological traits among the extant rice (Oryza sativa L.) varieties. Indian Journal of Agricultural Sciences 86 (5): 673-678. 
  20. Sarao, N.K., Joshi, M.A., Sharma, R.C., Sandhu, J.S. and Kumar, J. (2009) Characterization of chickpea based on morphological markers. Journal of Food Legumes 22(4): 251-253.
  21. Steel, R. G. D., Torrie, J. H. and Dicky, D. A. (1997). Principles and procedures of Statistics. A Biometrical Approach. 3rd edition. McGraw Hill Book Co. Inc, New York. pp: 428. 

Global Footprints