Skip to main navigation menu Skip to main content Skip to site footer

Research Articles

Vol. 11 No. sp4 (2024): Recent Advances in Agriculture by Young Minds - I

Allelic divergence and heritable interrelationship studies for yield and submergence tolerance in rice (Oryza sativa L.)

DOI
https://doi.org/10.14719/pst.5600
Submitted
7 October 2024
Published
25-12-2024

Abstract

Global low-lying rice cultivation faces a serious threat of flash floods, exacerbated by climate change. Significant progress has been made by plant breeders to introgress Sub1 locus into elite rice background through marker-assisted breeding approaches. The F2 population derived from the ADT 36 × #91-27 (NIL of CO 43 Sub1) was used to identify high-yielding lines that are homozygous for the Sub1 locus and Pi54 gene. INDEL markers, ART 5 and Pi 54, were used for genotyping the Sub1 locus and Pi54 gene, respectively. Out of 83 F2 plants, 21 plants are homozygotes and 45 plants are heterozygotes for the Sub1 locus. Whereas 21 plants are homozygotes and 46 are heterozygotes for the Pi54 gene. Four plants were identified to be homozygotes for the Sub1 locus and Pi54 gene. Genetic analysis of the F2 plants identified that productive tillers (number/plant) and the filled grains (number/panicle) exerted the highest positive effect on the single plant yield and also had the highest heritability. Also, these traits have a significant positive correlation per se. These traits, particularly productive tillers (number/plant), can potentially be used in subsequent generations to select high-yielding submergence tolerance and blast resistant lines of ADT 36 × #91-27 (NIL of CO 43 Sub1).

References

  1. FAO. FAOSTAT Database. https://wwwfaoorg/faostat/en/#data/QCL/visualize2021 [cited 16 October 2024].
  2. Qian Q, Guo L, Smith SM, Li J. Breeding high-yield superior quality hybrid super rice by rational design. National Science Review. 2016;3(3):283-94. https://doi.org/ 10.1093/nsr/nww006
  3. Krishnan R, Sanjay J, Gnanaseelan C, Mujumdar M, Kulkarni A, Chakraborty S. Assessment of climate change over the Indian region: a report of the ministry of earth sciences (MOES). Government of India: Springer Nature; 2020. https://doi.org/ 10.1007/978-981-15-4327-2_1
  4. Oladosu Y, Rafii MY, Arolu F, Chukwu SC, Muhammad I, Kareem I, et al. Submergence tolerance in rice: Review of mechanism, breeding and future prospects. Sustainability. 2020;12(4):1632. https://doi.org/10.3390/su12041632
  5. Setter T, Ramakrishanayya G, Ram P, Singh B, Mallik S, Roy J, et al., editors. Physiology of rice: prospects for increasing tolerance to submergence. Proceedings of the International Symposium on Rainfed Rice for Sustainable Food Security Central Rice Research Institute, Cuttack, India; 1998.
  6. Sarkar R, Das K, Panda D, Reddy J, Patnaik S, Patra B, et al. Submergence tolerance in rice: biophysical constraints, physiological basis and identification of donors. Central Rice Research Institute, Cuttack, India. 2014;36.
  7. Peramaiyan P, Singh K, Borgohain R, Khandai S, Varkey LM, Kumar V, et al. Submergence-tolerant rice varieties and mechanical transplanting for intensification of rice-rice cropping systems in Assam. Farming System. 2024;2(1):100068. https://doi.org/ 10.1016/j.farsys.2023.100068
  8. Ismail AM, Singh US, Singh S, Dar MH, Mackill DJ. The contribution of submergence-tolerant (Sub1) rice varieties to food security in flood-prone rainfed lowland areas in Asia. Field Crops Research. 2013;152:83-93. https://doi.org/10.1016/j.fcr.2013.01.007
  9. Phukon M, Das J, Sruthi R, Verma RK, Modi MK, Bhattacharyya A, et al. Study on submergence tolerance of rice (Oryza sativa L.) in a core panel of North-East India using GWAS. Indian Journal of Genetics and Plant Breeding. 2024;84(02):193-201. https://doi.org/10.31742/ISGPB.84.2.6
  10. Cairns JE, Sonder K, Zaidi P, Verhulst N, Mahuku G, Babu R, et al. Maize production in a changing climate: impacts, adaptation and mitigation strategies. Advances in Agronomy. 2012;114:1-58. https://doi.org/10.1016/b978-0-12-394275-3.00006-7
  11. Johnson HW, Robinson H, Comstock R. Estimates of genetic and environmental variability in soybeans. 1955. https://doi.org/10.2134/agronj1955.00021962004700070009x
  12. Saha SR, Hassan L, Haque MA, Islam MM, Rasel M. Genetic variability, heritability, correlation and path analyses of yield components in traditional rice (Oryza sativa L.) landraces: Variability and traits association in rice. Journal of the Bangladesh Agricultural University. 2019;17(1):26-32. https://doi.org/10.3329/jbau.v17i1.40659
  13. Ashfaq M, Rasheed A, Zhu R, Ali M, Javed MA, Anwar A, et al. Genome-wide association mapping for yield and yield-related traits in rice (Oryza sativa L.) using SNPs markers. Genes. 2023;14(5):1089. https://doi.org/10.3390/genes14051089
  14. Viswabharathy S, Kalaimagal T, Manonmani S, Jeyakumar P, Raveendran M. Estimation of narrow sense heritability in early segregating generations of rice introgressed with Sub1 QTL. Electronic Journal of Plant Breeding. 2023;14(3):912-22. https://doi.org/10.37992/2023.1403.103
  15. Reshma O, Shivaprasad K, Surendra P, Reddy B. Path and correlation analysis of elite rice (Oryza sativa L.) genotypes under diverse situations. Biological Forum - An International Journal. 2023;15(5):1443-48.
  16. TNAU. TNAU Crop Production Guide Agriculture 2020 [Available from: https://tnau.ac.in/site/research/wp-content/uploads/sites/60/2020/02/Agriculture-CPG-2020. pdf].
  17. Mirza MY, Khan MA, Akmal M, Mohmand AS, Nawaz MS, Nawaz N, et al. Estimation of genetic parameters to formulate selection strategy for increased yield in linseed. Pakistan Journal of Agricultural Research. 2011;24(1-4):19-24.
  18. Sivasubramaniam S, Madhava Menon P. Genotypic and phenotypic variability in rice. 1973.
  19. Snedecor G, Cochran W. Statistical methods. 6th Ed, Iowa State Univ Press. Ame Iowa USA. 1967;2:304-08.
  20. Olivoto T, Lúcio ADC. metan: An R package for multi?environment trial analysis. Methods in Ecology and Evolution. 2020;11(6):783-89. https://doi.org/10.1111/2041-210X.13384
  21. Manivannan N. TNAUSTAT-Statistical package. 2014.
  22. Allard R. Principles of plant breeding. John Wiley and Sons; 1999.
  23. Bitew JM. Estimation of genetic parameters, heritability and genetic advance for yield related traits in upland rice (Oryza sativa L. and Oryza glaberrima Steud) genotypes in northwestern Ethiopia. World Scientific News. 2016;2(47):340-50.
  24. Visscher PM, Hill WG, Wray NR. Heritability in the genomics era - concepts and misconceptions. Nature Reviews Genetics. 2008;9(4):255-66. https://doi.org/ 10.1038/nrg2322
  25. Burton GW. Quantitative inheritance in grasses. 1952.
  26. Ogunniyan D, Olakojo S. Genetic variation, heritability, genetic advance and agronomic character association of yellow elite inbred lines of maize (Zea mays L.). Nigerian Journal of Genetics. 2014;28(2):24-28. https://doi.org/10.1016/j.nigjg.2015.06.005
  27. Babu VR, Shreya K, Dangi KS, Usharani G, Nagesh P. Genetic variability studies for qualitative and quantitative traits in popular rice (Oryza sativa L.) hybrids of India. International Journal of Scientific and Research Publications. 2012;2(6):1-5.
  28. Patel R, Rukhsar AP, Patel D, Parmar DJ. Genetic analysis and trait association in F2 interspecific population in tomato (Solanum lycopersicum L.) using third and fourth degree statistics. Int J Curr Microbiol App Sci. 2018;7(12):2933-37. https://doi.org/ 10.20546/ijcmas.2018.712.334
  29. Choo T, Reinbergs E. Analyses of skewness and kurtosis for detecting gene interaction in a doubled haploid population. Crop Science. 1982;22(2):231-35. https://doi.org/ 10.2135/cropsci1982.0011183X002200020008x
  30. Khandappagol M, Rajanna M, Savita S. Variability and frequency distribution studies in F2 population of two crosses involving traditional varieties of rice (Oryza sativa L.). Journal of Pharmacognosy and Phytochemistry. 2019;8(1):1630-34.
  31. Patel M, Patel V, Patel S, Patel R. Assessment of genetic variability for yield and yield attributing traits in F2 population of intervarietal cross in rice (Oryza sativa L.). Int J Curr Microbiol Appl Sci. 2020;9:1550-55. https://doi.org/10.20546/ijcmas.2020.903.181
  32. Ardiarini N-R, Adiredjo A-L. Genetic variability and gene action for several traits in F4 and F5 population of rice. Plant Breeding and Biotechnology. 2022;10(1):31-36. https://doi.org/10.9787/PBB.2022.10.1.31
  33. Pavithra S, Senthil A, Djanaguiraman M, Raveendran M, Pushpam R, ManikandaBoopathi N. Analysis of genetic variability for leaf and yield traits in diverse rice germplasm. J of Curr Crop Sci Technol. 2022;109(4-6):29-34. https://doi.org/10.29321/MAJ.10.000603
  34. Falconer DS. Introduction to quantitative genetics: Pearson Education India; 1996.
  35. Reetisana N SE, Renuka T, Julia T, Pyngrope AH. Correlation and path coefficient analysis in screening of submergence tolerance in rice (Oryza sativa L.) genotypes of Manipur. Biological Forum - An International Journal. 2022;14(2):1130-35.
  36. Khan MMH, Rafii MY, Ramlee SI, Jusoh M, Al Mamun M. Path-coefficient and correlation analysis in Bambara groundnut (Vigna subterranea [L.] Verdc.) accessions over environments. Scientific Reports. 2022;12(1):245. https://doi.org/10.1038/s41598-021-03692-z
  37. Saleh MM, Salem KF, Elabd AB. Definition of selection criterion using correlation and path coefficient analysis in rice (Oryza sativa L.) genotypes. Bulletin of the National Research Centre. 2020;44:1-6. https://doi.org/10.1186/s42269-020-00403-y
  38. Thuy NP, Trai NN, Khoa BD, Thao NHX, Phong VT, Thi QVC. Correlation and path analysis of association among yield, micronutrients and protein content in rice accessions grown under aerobic condition from Karnataka, India. Plant Breeding and Biotechnology. 2023;11(2):117-29. https://doi.org/10.9787/PBB.2023.11.2.117
  39. Singh AK, Dwivedi D, Kumar D, Singh A, Dixit S, Khan N, et al. Genetic variability, character association and path coefficient analysis in rice (Oryza sativa) genotypes of semi-arid region of India. The Indian Journal of Agricultural Sciences. 2023;93(8):844-49. https://doi.org/10.56093/ijas.v93i8.137199

Downloads

Download data is not yet available.