Journal of Innovative Agriculture, Volume 9, Issue 4 : 44-56. Doi : 10.37446/jinagri/rsa/9.4.2022.44-56
Research Article

OPEN ACCESS | Published on : 31-Dec-2022

Genetic parameters estimation and evaluation of yield and yield attributing traits of rice genotypes under reproductive drought stress condition

  • Bigyan Khatri Chhetri
  • Department of Plant Breeding, PG Program, Institute of Agriculture and Animal Science (IAAS), Tribhuvan University, Kirtipur, Nepal.
  • Sagar Lamichhane
  • Institute of Agriculture and Animal Science (IAAS), Lamjung Campus,
  • Pratit Khanal
  • Institute of Agriculture and Animal Science (IAAS), Lamjung Campus, Nepal.
  • Subarna Sharma Acharya
  • Institute of Agriculture and Animal Science (IAAS), Lamjung Campus, Nepal.
  • Nav Raj Adhikari
  • Institute of Agriculture and Animal Science (IAAS), Lamjung Campus, Nepal.
  • Koshraj Upadhyay
  • Institute of Agriculture and Animal Science (IAAS), Gauradaha Campus, Nepal.

Abstract

In order to determine the degree of genetic divergence and to assess yield and yield components of rice under reproductive drought stress conditions, a field screening of eleven genotypes was carried out at a farmer's field in Sundarbazar, Lamjung. This was done using a randomized complete block design with three replications. Significant variations between all genotypes for all tested parameters were found by the analysis of variance, indicating the presence of genetic variability as well as the possibility of future improvement through selection. Phenotypic coefficient of variance was higher than genotypic coefficient of variance for all traits under study and difference between them was found low, meaning less influence of environment in the expression of these characters and selection could be effective on the basis of phenotype independent of genotype for the improvement of these traits. Moderate to high estimates of GCV, PCV, heritability and genetic advance as percent of mean was found for all traits studied. Chlorophyll content, leaf area and filled grains per panicle showed positive and significant association with grain yield. Three principal components were extracted based on eigen value accounting 84% of total variation. Eleven rice genotypes were clustered into three groups where cluster 3 was found to be superior for yield and yield attributing traits. Eight genotypes yielded more than that of check variety where highest yield was recorded by Sukhadhan-4. Rice genotypes under study showed enough genetic diversity hence, indirect selection of traits like flag leaf area, filled grains per panicle, harvest index, plant height, SPAD value and thousand grain weights will be effective for increasing yield.

Keywords

rice, reproductive, stress, drought, correlation, heritability, cluster

References

  • Abarshahr, M., Rabiei, B., & Lahigi, H. S. (2011). Genetic Variability, Correlation and Path Analysis in Rice under Optimum and Stress Irrigation Regimes. Notulae Scientia Biologicae, 3(4), 134–142. https://doi.org/10.15835/nsb346280

     Abebe, T., Alamerew, S., & Tulu, L. (2017). Genetic Variability, Heritability and Genetic Advance for Yield and its Related Traits in Rainfed Lowland Rice (Oryza sativa L.) Genotypes at Fogera and Pawe, Ethiopia. Advances in Crop Science and Technology, 05(02). https://doi.org/10.4172/2329-8863.1000272

    Adhikari, B. B., Mehera, B., & Haefele, S.M. (2015). Selection of drought tolerance rice varieties for the western mid hills of Nepal. Journal of the Institute of Agriculture and Animal Science, 33, 195-206.

    Basnet, B. M. S.(2012). Rice: Water, Food Security and Climate Change in Nepal. Hydro Nepal: Journal of Water, Energy and Environment, 11,78-80.

    Chahal, G. S., & Gosal, S. S. (2002). Principles and procedures of plant breeding: biotechnology and conventional approaches. Alpha Science International, Pangbourne.

    FAOSTAT. (2017). https://www.fao.org/faostat/en/

    Fukai, S., Pantuwan, G., Jongdee, B., & Cooper, M. (1999). Screening for drought resistance in rainfed lowland rice. Field Crops Research, 64(1–2), 61–74. https://doi.org/10.1016/s0378-4290(99)00051-9

    Rice Almanac. (2013). Global rice science partnership (4th ed.). International Rice Research Institute.

    Haide, Z., Khan, A. S.,& Zia, S. (2012).Correlation and Path Coefficient Analysis of Yield Components in Rice (Oryza sativa L.) Under Simulated Drought Stress Condition. American-Eurasian J. Agric. & Environ. Sci., 12 (1): 100-104.

    IRRI (2017). https://www.irri.org/

    Kumar, S., Dwivedi, S.K., Haris, A. A., Prakash, V., Mondal, S., & Singh, S.K. (2015). Screening and identification of rice genotypes for drought tolerance at reproductive stage under rainfed lowland condition. Journal of AgriSearch, 2(2), 105–111. https://jsure.org.in/journal/index.php/jas/article/download/133/99

    Maclean, J.L., Dawe, D.C., Hardy, B.,& Hettel, G.P. (2002). Rice almanac (3rd ed.). International Rice Research Institute.

    Mallick, R. N. (1981). Rice in Nepal. KalaPrakasan. Kathmandu, Nepal

    MoAD. (2013). Statistical Information on Nepalese Agriculture, 2012/13.Ministry of

    Agricultural Development, Singh Durbar, Kathmandu, Nepal.

    MoAD. (2015). Rice varietal mapping in Nepal: Implication for development and adoption. Ministry of Agriculture and Development, Singh Durbar, Kathmandu, Nepal.

    Mukherjee, M., Padhy, B., Dondè, R., Mahadani, P., Baksh, S.K., Behera, L., & Kumar, S.(2018).Study of genetic diversity and effectiveness of traits for direct selection under drought as well as non-stress condition for Rainfed upland rice. Journal of Pharmacognosy and Phytochemistry, 7(3), 2060-2067.

    Staple food crops of the world. (2017). National Geographic Society. https://www.nationalgeographic.org/maps/wbt-staple-food-crops-world/

     Nikhil, B. S. K., Rangare, N. R., and Saidaiah, P. (2014). Correlation and path analysis in rice (Oryza sativa L.). National academy of agricultural science (NAAS), 32, 1-2.

    Guo Z, Zhao, Y., Röder, M.S., Reif, J.C., Ganal, M.W., and Chen, D. (2018). Manipulation and prediction of spike morphology traits for the improvement of grain yield in wheat. Sci Rep., 8,1–10.

    Liu, C., Khodaee, M., Lopes, M.S., Sansaloni, C., Dreisigacker, S., Sukumaran, S., and Reynolds, M. (2019). Multi-environment QTL analysis using an updated genetic map of a widely distributed Seri× Babax spring wheat population. Molecular Breeding, 39(9), 1-15.

    Mahpara, S., Ali, Z., Rehmani, M.I.A., Iqbal, J., and Shafiq, M.R.  (2017). Studies of genetic and combining ability analysis for some physio-morphological traits in spring wheat using 7× 7 diallel crosses. International Journal of Agricultural and Applied Sciences, 9(1), 33-40.

    Feng, T.,Xi,Y., Zhu, Y.H., Chai, N., Zhang, X.T., Jin, Y., Turner, N.C., and Li, F.M. (2021).Reduced Vegetative Growth Increases Grain Yield in Spring Wheat Genotypes in the Dryland Farming Region of North-West China. Agronomy, 11, 663.

    Luo, F., Deng, X., Liu, Y., and Yan, Y. (2018). Identification of phosphorylation proteins in response to water deficit during wheat flag leaf and grain development. Botanical studies, 59(1), 1-17.

    Ma, J., Tu, Y., Zhu, J., Luo, W., Liu, H., Li, C., and Lan, X. (2020). Flag leaf size and posture of bread wheat: genetic dissection, QTL validation and their relationships with yield-related traits. Theoretical and Applied Genetics, 133(1), 297-315.

    Bilgrami, S. S., Fakheri, B.A., Razavi, K., Mahdinezhad, N., Tavakol, E., Ramandi, H.D., and Shariati, J.V. (2018). Evaluation of agro-morphological traits related to grain yield of Iranian wheat genotypes in drought-stress and normal irrigation conditions. Australian Journal of Crop Science, 12(5), 738-748.

    Kamaran, S., Khan, T.M., Bakhsh, A., Hussain, N., Mahpara, S., Manan, A. ,and Iqbal, M. (2019). Assessment of morphological and molecular marker based genetic diversity among advanced upland cotton genotypes. Pakistan Journal of Agricultural Sciences, 56(3).

    Central Bureau of Statistics [CBS]. (2011). Nepal living standards survey 2010/2011. Kathmandu: Central Bureau of Statistics.

    Padmaja1, D., Radhika, K., Rao, L.V.S., & Padma, V. (2008). Studies on Variability, Heritability and Genetic Advance for Quantitative Characters in Rice (Oryza sativa L.). Indian Journal of Plant Genetic Resources, 21(3), 196–198.

    Saikumar, S., Saiharini, A., Ayyappa, D., Padmavathi, G., & Shenoy, V. (2014). Heritability, Correlation and Path Analysis among Yield and Yield Attributing Traits for Drought Tolerance in an Interspecific Cross  Derived from Oryza sativa x O. glaberrima Introgression Line under Contrasting Moisture Regimes. Not SciBiol, 6(3), 338-348

    Siddiq, E. A. (2000). Bridging rice yield gap in India. In: Proceedings of Expert Conference on bridging the rice yield gap in the Asia- Pacific region, RAP, FAO.

    Singh, A., Nandan, R., & Singh, P.K. (2014). Genetic variability and association analysis in rice germplasm under rainfed conditions. Crop Research, 47(1), 7–11.

    Longjam, S., & Singh, N.B. (2019).  Assessment of heritability and genetic advance for yield contributing characters in hill rice (Oryza sativa L.) genotypes of Manipur. The Pharma Innovation Journal8(4), 07–11.

    Tiwari, D. N., Tripathi, S. R., Tripathi, M. P., Khatri, N., & Bastola, B. R. (2019). Genetic Variability and Correlation Coefficients of Major Traits in Early Maturing Rice under Rainfed Lowland Environments of Nepal. Advances in Agriculture2019, 1–9.

    Tripathi, B. P., Bhandari, H. N., & Ladha, J.K. (2019). Rice Strategy for Nepal. Acta Scientific Agriculture,3(2), 171-180.

    E. B. Yambao, & Ingram, K. T. (1988). Drought stress index for rice. Philippine Journal of Crop Science13(2), 105–111.

    Hair, J. F., Anderson, R. E., Tatham, R. L., & Black, W.C. (1995). Multivariate data analysis (4th ed). Prentice-Hal, Englewood Cliffs, New Jersey, USA.

    Yousaf, A., Atta, B.M., Akhter, J., Monneveux, P., & Lateef, Z. (2008). Genetic variability, association and diversity studies in wheat (Triticum aestivum L.) germplasm. Pakistan Journal of Botany, 40(5), 87-97.

    Khodadadi, M., Fotokian, M.H.,  & Miransari, M. (2011). Genetic diversity of wheat (Triticum aestivum L.) genotypes based on cluster and principal component analyses for breeding strategies. Australian Journal of Crop Sciences, 5(1), 17-24.