Grouping of rice (Oryza sativa L.) lines based on multivariate analysis under drought stress condition

Document Type : Research Paper


guilan university


For evaluation and grouping of 150 inbred lines of rice based on some morphological and physiological traits, an experiment was conducted using Augment design based on randomized complete block design (RCBD) with four replications in Agricultural College of Guilan University, in 2013. Correlation coefficients between traits showed a significant correlation between grain yield with almost all of traits. Factor analysis showed that four independent and main factors explained 94.23 percent of total variance in all lines. The first factor with 51.99 percent of variance was named as the yield components and fertility rate. The second factor with 25.41 percent of variance was nominated as fertility rate, the yield and the yield components. The third factor with 11.50 percent of variance was nominated as physiologic traits. The fourth factor with 5.33 percent of variance was nominated as plant morphologic. Cluster analysis by ward method with a 92.7 percent of original grouped cases correctly classified four distinct groups for studied lines. Finally, to select high-yielding lines and tolerate to drought stress in rice simultaneously selection can be carried out for traits such as number of total spikelet per panicle, number of filled grain per panicle; spikelet fertility, proline content, chlorophyll a, chlorophyll b, total chlorophyll and relative water content.


Main Subjects

  1. Abarshahr, M., Rabiei, B. & Samizadeh-Lahigi, H. (2011). Assessing genetic diversity of rice varieties under drought stress conditions. Notulae Scientia Biologicae, 3: 114-123.
  2. Bagheri, N., Babaeian-Jelodar, N. & Pasha, A. (2011). Path coefficient analysis for yield and yield components in diverse rice (Oryza sativa L.) genotypes. Biharean Biologist, 5 (1): 32-35.
  3. Bates, I. S., Waldern R. P. & Teare, I. D. (1973). Rapid determination of free proline water stress studies. Plant and Soil, 39: 205-207.
  4. Bonnet, M., Camares, O. & Veisseire, P. (2000). Effects of zinc and influence of Acremonium lolii on growth parameters, chlorophyll a fluorescence and antioxidant enzyme activities of ryegrass (Lolium perenne L. cv Apollo). Journal of Experimental Botany, 51: 945–953.
  5. Bouman, B. A. M., Peng, S., Castaňeda, A. R. & Visperas, R. M. (2005). Yield and water use of irrigated tropical aerobic rice systems. Agricalture Water Management, 74: 87–105.
  6. Chakravorty, A., Ghosh P. D. & Sahu, P. K. (2013). Multivariate analysis of phenotypic diversity of landraces of rice of west bengal. American Journal of Experimental Agriculture, 3(1): 110-123.
  7. Cha-Um, S., Yooyongwech, S. & Supaibulwatana, K. (2010). Water deficit stress in the reproductive stage of four indica rice (Oryza sativa L.) genotypes. Pakistan Journal of Botany, 42(5): 3387-3398.
  8. Fentie, D., Alemayehu, G., Siddalingaiah, M. & Tadesse, M. (2014). Genetic Variability, Heritability and Correlation Coefficient Analysis for Yield and Yield Component Traits in Upland Rice (Oryza sativa L.). East African Journal of Sciences, 8 (2): 147-154.
  9. GenStat. (2009). GenStat for Windows 12th Edition. VSN International, Hemel Hempstead, UK.
  10. Ghiasy, M., Farahbakhsh, H., Sabouri, H. & Mohamadi nejad, GH. (2013). Evaluation of rice cultivars in drought and normal conditions based on sensitive and tolerance indices. Electronic Journal of Crop Production, 6 (4): 55-75. (In Farsi)
  11. Ghorbani, H., Samizadeh Lahiji, H. A., Rabiei, B. & Allahgholipour, M. (2011). Grouping different rice genotypes using factor and cluster analyses. Journal of Sustainable Agriculture and Production Science, 21(3): 89-104. (In Farsi)
  12. Lanceras, J. C., Griengrai, P., Boonrat, J. & Theerayut, T. (2004). Quantitative trait loci associated with drought tolerance at reproductive stage in rice. Plant Physiology, 1: 384-399.
  13. Lichtenthaler, H. K. & Wellburn, A. R. (1983). Determinations of total carotenoids and chlorophylls a and b of leaf extracts in different solvents. Biochemical Society Transactions, 11: 591 - 592.
  14. Majidimehr, A., Amiri-Fahliani, R. & Masoumiasl, A. (2014). Study of biochemical and chemical traits of different rice genotypes under salinity stress. Cereal Research, 4 (1): 45-58. (In Farsi)
  15. Nam, N. H., Chauhan, Y. S. & Johansen, C. (2001). Effect of timing of drought stress on growth and grain yield of extra-short-duration pigeonpea lines. Journal of Agricultural Science, 136: 179–189.
  16. Nandan, R., Sweta, D. & Singh, S. K. (2010). Character association and path analysis in rice (Oryza sativa L.) genotypes.World Journal of Agricultural Sciences, 6 (2): 201 - 206.
  17. Rahimi, M., Rabiei, B. Ramezani, M. & Movafegh, S. (2010). Evaluation of agronomic traits and determine the variables to improve rice yield. Iranian Journal of Field Crops Research, 8(1): 111-119. (In Farsi)
  18. Raychaudhuri, S., Stuart, J. M. & Altman, R. B. (2000). Principal components analysis to summarize microarray experiments: Application to sporulation time series. Pacific Symposium on Biocomputing, 455-466.
  19. Safaei Chaeikar, S., Samizadeh, H., Rabiei, B. & Esfahani, M. (2009). Correlation of agronomic traits under optimum irrigation and water stress in rice (Oryza sativa L.). Journal of Sciences and Technology of Agriculture and Natural Resources, 13(48): 91-105. (In Farsi)
  20. Sanni, K. A., Fawole, I., Ogunbayo, A., Tia, D., Somado, E. A., Futakuchi, K., Sié, M., Nwilene, F. E. & Guei, R. G. (2010). Multivariate analysis of diversity of landrace rice germplasm. In: Innovation and Partnerships to Realize Africa’s Rice Potential. Proceedings of the Second Africa Rice Congress, Bamako, Mali, 22–26 March 2010. Africa Rice Center (AfricaRice), Cotonou, Benin. pp. 1.1.1-1.1.8.
  21. SES. (2002). Standard evaluation system for rice. International Rice Research Institute Manila, Philippines.
  22. SPSS-Inc. (2010). IBM SPSS statistics 19 core system user’s guide. USA: SPSS Inc., an IBM Company Headquarters.
  23. Tao, H., Brueck, H., Dittert, K., Kreye, C., Lin, S. & Sattelmacher, B. (2006). Growth and yield formation for rice (Oryza sativa L.) in the water-saving ground cover rice production system (GCRPS). Field Crops Research, 95: 1–12.
  24. Venkata Lakshmi, M., Suneetha, Y., Yugandhar, G. & Venkata Lakshmi, N. (2014). Correlation studies in rice (Oryza sativa L.). International Journal of Genetic Engineering and Biotechnology, 5(2): 121-126.
  25. Worede, F., Sreewongchai, T., Phumichai, Ch. & Sripichitt, P. (2014). Multivariate analysis of genetic diversity among some rice genotypes using morpho-agronomic traits. Journal of Plant Science, 9(1):14-24.
  26. Yan, W. & Rajcan, I. (2002). Biplot analysis of test sites and trait relations of soybean in Ontario. Crop Science, 42: 11-20.
  27. Yazdani, M., Kochak, M. & Bagheri, H. (2014). Segregating rice genotypes by cluster analysis procedure at different salt stress condition. Advances in Environmental Biology, 8(10): 383-387.
Volume 48, Issue 4 - Serial Number 4
March 2018
Pages 1027-1039
  • Receive Date: 14 November 2016
  • Revise Date: 12 March 2017
  • Accept Date: 03 April 2017
  • Publish Date: 20 February 2018