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

Research Articles

Vol. 11 No. 1 (2024)

Assessment of variability parameters and diversity of panicle architectural traits associated with yield in rice (Oryza sativa L.)

DOI
https://doi.org/10.14719/pst.2658
Submitted
10 May 2023
Published
14-10-2023 — Updated on 01-01-2024
Versions

Abstract

The rice panicle, a pivotal reproductive structure, signifies the transition from vegetative to reproductive growth in plants. Comprising components such as the rachis, primary and secondary branches, seed quantities and branch lengths, panicle architecture profoundly influences grain production. This study delves into the diversity of panicle architecture traits and scrutinizes variability parameters across 69 distinct rice genotypes. Our findings underscore substantial variations in panicle architecture traits among genotypes. Particularly noteworthy are traits with the highest coefficient of variation (CV%), encompassing the count of secondary branches, single plant yield, productive tillers per plant, seeds per secondary branch and panicle weight. Correlation analysis reveals robust positive connections between panicle weight, the number of filled grains per panicle, 1000-grain weight and single plant yield. The number of secondary branches exhibits the most substantial phenotypic coefficient of variation (PCV%) at 47.14%, accompanied by a genotypic coefficient of variation (GCV%) of 43.57%. Traits such as days to 50% flowering, plant height and number of filled grains per panicle manifest high heritability (97.04%, 91.24% and 76.22% respectively) and notable genetic advancement (23.11%, 39.62% and 47.49%). The principal component analysis identifies the primary component (PC1) as the principal contributor to variance. Biplot analysis accentuates positive correlations between attributes like the number of filled grains per panicle, panicle length, plant height, primary branch count, panicle weight, seeds per primary branch and the number of secondary branches with single plant yield. By employing Mahalanobis D2 statistics, the classification of genotypes into 6 distinct clusters reveals clusters III and IV as distinguished by their significant inter-cluster and intra-cluster distances. This comprehensive analysis unveils the potential for harnessing panicle architecture traits to enhance grain production and advances our comprehension of intricate relationships within diverse rice genotypes.

References

  1. Panesar PS, Kaur S. Rice: types and composition. Encyclopedia of Food and Health, Academic Press. 2016;Oxford:646-52.
  2. https://doi.org/10.1016/B978-0-12-384947-2.00596-1
  3. Al-daej MI, Rezk AA, El-Malky MM, Shalaby TA, Ismail M. Comparative genetic diversity and marker-trait association using two DNA marker systems in rice (Oryza sativa L.). Agronomy. 2023;13(2):329.
  4. https://doi.org/10.3390/agronomy13020329
  5. Bai X, Huang Y, Mao D, Wen M, Zhang L, Xing Y. Regulatory role of FZP in the determination of panicle branching and spikelet formation in rice. Scientific Reports. 2016;6(1):1-11.
  6. https://doi.org/10.1038/srep19022
  7. Li G, Zhang H, Li J, Zhang Z, Li Z. Genetic control of panicle architecture in rice. The Crop Journal. 2021;9(3):590-97.
  8. https://doi.org/10.1016/j.cj.2021.02.004
  9. Agata A, Ando K, Ota S, Kojima M, Takebayashi Y, Takehara S et al. Diverse panicle architecture results from various combinations of Prl5/GA20ox4 and Pbl6/APO1 alleles. Communications Biology. 2020;3(1):302.
  10. https://doi.org/10.1038/s42003-020-1036-8
  11. Han X, Tang M, Deng Y. Preliminary study on pulping of rice straw in Tris-(2-hydroxyethyl) ammonium acetate ionic liquid under microwave irradiation. Bioresources. 2014;9(4).
  12. https://doi.org/10.15376/biores.9.4.6851-6860
  13. Singh RK, Kota S, Flowers TJ. Salt tolerance in rice: seedling and reproductive stage QTL mapping come of age. Theoretical and Applied Genetics. 2021;134:3495-533. https://doi.org/10.1007/s00122-021-03890-3
  14. Bai S, Hong J, Li L, Su S, Li Z, Wang W et al. Dissection of the genetic basis of rice panicle architecture using a genome-wide association study. Rice. 2021;14:1-12. https://doi.org/10.1186/s12284-021-00520-w
  15. Lu Y, Chuan M, Wang H, Chen R, Tao T, Zhou Y et al. Genetic and molecular factors in determining grain number per panicle of rice. Frontiers in Plant Science. 2022;13.
  16. https://doi.org/10.3389/fpls.2022.964246
  17. Imai K, Murai M, Hao Y, Chiba Y, Chiba A, Ishikawa R. Mapping of rice Ur1 (Undulated rachis?1) gene with effect on increasing spikelet number per panicle and sink size and development of selection markers for the breeding by the use of Ur1. Hereditas. 2009;146(6):260-68.
  18. https://doi.org/10.1111/j.1601-5223.2009.02108.x
  19. Zhai L, Wang F, Yan A, Liang C, Wang S, Wang Y et al. Pleiotropic effect of GNP1 underlying grain number per panicle on sink, source and flow in rice. Frontiers in Plant Science. 2020;11:933.
  20. https://doi.org/10.3389/fpls.2020.00933
  21. Jin J, Hua L, Zhu Z, Tan L, Zhao X, Zhang W et al. GAD1 encodes a secreted peptide that regulates grain number, grain length and awn development in rice domestication. Plant Cell. 2016;28(10):2453-63.
  22. https://doi.org/10.1105/tpc.16.00379
  23. Luo J, Liu H, Zhou T, Gu B, Huang X, Shangguan Y et al. An-1 encodes a basic helix-loop-helix protein that regulates awn development, grain size and grain number in rice. Plant Cell. 2013;25(9):3360-76.
  24. https://doi.org/10.1105/tpc.113.113589
  25. Wei X, Huang X. Origin, taxonomy and phylogenetics of rice. In: Rice. Elsevier. 2019; p. 1-29.
  26. https://doi.org/10.1016/B978-0-12-811508-4.00001-0
  27. Liu E, Liu Y, Wu G, Zeng S, Tran Thi TG, Liang L et al. Identification of a candidate gene for panicle length in rice (Oryza sativa L.) via association and linkage analysis. Frontiers in Plant Science. 2016;7:596.
  28. https://doi.org/10.3389/fpls.2016.00596
  29. Kong FN, Wang JY, Zou JC, Shi LX, De Jin M, Xu ZJ et al. Molecular tagging and mapping of the erect panicle gene in rice. Molecular Breeding. 2007;19:297-304.
  30. https://doi.org/10.1007/s11032-006-9062-x
  31. Luo J, Liu H, Zhou T, Gu B, Huang X, Shangguan Y et al. An-1 encodes a basic helix-loop-helix protein that regulates awn development, grain size and grain number in rice. Plant Cell. 2013;25(9):3360-76.
  32. https://doi.org/10.1105/tpc.113.113589
  33. Tsukahara K, Sawada H, Kohno Y, Matsuura T, Mori IC, Terao T et al. Ozone-induced rice grain yield loss is triggered via a change in panicle morphology that is controlled by aberrant panicle organization 1 gene. PLoS One. 2015;10(4):e0123308. https://doi.org/10.1371/journal.pone.0123308
  34. Luan X, Liu S, Ke S, Dai H, Xie XM, Hsieh TF et al. Epigenetic modification of ESP, encoding a putative long noncoding RNA, affects panicle architecture in rice. Rice. 2019;12(1):1-8.
  35. https://doi.org/10.1186/s12284-019-0282-1
  36. Chun SW, Lee JW, Ahn JY. Development and characterization of novel microsatellite markers in Tilia amurensis Rup using next-generation sequencing. Molecular Biology Reports. 2022;1-5. doi: 10.1007/s11033-021-07035-z.
  37. Jiao Y, Wang Y, Xue D, Wang J, Yan M, Liu G et al. Regulation of OsSPL14 by OsmiR156 defines ideal plant architecture in rice. Nature Genetics. 2010;42(6):541-44.
  38. https://doi.org/10.1038/ng.591
  39. Li M, Tang D, Wang K, Wu X, Lu L, Yu H et al. Mutations in the F?box gene larger panicle improve the panicle architecture and enhance the grain yield in rice. Plant Biotechnology Journal. 2011;9(9):1002-13.
  40. https://doi.org/10.1111/j.1467-7652.2011.00610.x
  41. Chen X, Chen M, Lin G, Yang Y, Yu X, Wu Y et al. Structural development and physicochemical properties of starch in caryopsis of super rice with different types of panicle. BMC Plant Biology. 2019;19(1):1-15.
  42. https://doi.org/10.1186/s12870-019-2101-7
  43. Yoon J, Jeong HJ, Baek G, Yang J, Peng X, Tun W et al. A VIN3-like protein OsVIL1 is involved in grain yield and biomass in rice. Plants. 2021;11(1):83. https://doi.org/10.3390/plants11010083
  44. Deveshwar P, Prusty A, Sharma S, Tyagi AK. Phytohormone-mediated molecular mechanisms involving multiple genes and QTL govern grain number in rice. Frontiers in Genetics. 2020;11:586462.
  45. https://doi.org/10.3389/fgene.2020.586462
  46. Zhou J, Li Z, Xiao G, Zhai M, Pan X, Huang R et al. CYP71D8L is a key regulator involved in growth and stress responses by mediating gibberellin homeostasis in rice. Journal of Experimental Botany. 2020;71(3):1160-70.
  47. https://doi.org/10.1093/jxb/erz491
  48. Rathna Priya TS, Eliazer Nelson ARL, Ravichandran K, Antony U. Nutritional and functional properties of coloured rice varieties of South India: A review. Journal of Ethnic Foods. 2019;6(1):1-11.
  49. https://doi.org/10.1186/s42779-019-0017-3
  50. Karthikeyan P, Anbuselvam Y, Elangaimannan R, Venkatesan M. Variability and heritability studies in rice (Oryza sativa L.) under coastal salinity. Electronic Journal of Plant Breeding. 2010;1(2):196-98.
  51. https://www.ejplantbreeding.org/index.php/EJPB/article/view/1904/967
  52. Panda D, Sahu N, Behera PK, Lenka K. Genetic variability of panicle architecture in indigenous rice landraces of Koraput region of Eastern Ghats of India for crop improvement. Physiology and Molecular Biology of Plants. 2020;26(10):1961-71.
  53. https://doi.org/10.1007/s12298-020-00871-6
  54. Gautam A, Shrestha A. Evaluation of panicle architecture traits in rice genotypes using PTRAP. Nepal Agriculture Research Journal. 2023;15(1):115-24. https://doi.org/10.3126/narj.v15i1.51533
  55. Shrestha J, Subedi S, Kushwaha UKS, Maharjan B. Evaluation of growth and yield traits in rice genotypes using multivariate analysis. Heliyon. 2021;7(9):e07940.
  56. https://doi.org/10.1016/j.heliyon.2021.e07940
  57. Parimala K, Raju CHS, Prasad ASH, Kumar SS, Reddy SN. Studies on genetic parameters, correlation and path analysis in rice (Oryza sativa L.). Journal of Pharmacognosy and Phytochemistry. 2020;9(1):414-17.
  58. http://www.phytojournal.com/
  59. Bai L, Huan S, Gu J, McClements DJ. Fabrication of oil-in-water nano emulsions by dual-channel microfluidization using natural emulsifiers: Saponins, phospholipids, proteins and polysaccharides. Food Hydrocolloids. 2016;61:703-11.
  60. https://doi.org/10.1016/j.foodhyd.2016.06.035
  61. Xu Z, Chen W, Zhang L, Yang S. Design principles and parameters of rice ideal panicle type. Chinese Science Bulletin. 2005;50:2253-56.
  62. https://doi.org/10.1007/BF03182678
  63. Mei HW, Xu JL, Li ZK, Yu XQ, Guo LB, Wang YP et al. QTLs influencing panicle size detected in two reciprocal introgressive line (IL) populations in rice (Oryza sativa L.). Theoretical and Applied Genetics. 2006;112:648-56.
  64. https://doi.org/10.1007/s00122-005-0167-0
  65. Mazid MS, Rafii MY, Hanafi MM, Rahim HA, Latif MA. Genetic variation, heritability, divergence and biomass accumulation of rice genotypes resistant to bacterial blight revealed by quantitative traits and ISSR markers. Physiologia Plantarum. 2013;149(3):432-47.
  66. https://doi.org/10.1111/ppl.12054
  67. Ndjiondjop MN, Semagn K, Sow M, Manneh B, Gouda AC, Kpeki SB et al. Assessment of genetic variation and population structure of diverse rice genotypes adapted to lowland and upland ecologies in Africa using SNPs. Frontiers in Plant Science. 2018;9:446.
  68. https://doi.org/10.3389/fpls.2018.00446
  69. Herawati R. Genetic analysis of grain yield of f 4 populations for developing new type of upland rice. SABRAO Journal of Breeding and Genetics. 2019;51(1). https://sabraojournal.org/genetic-analysis-of-grain-yield-of-f4-populations-for-developing-new-type-of-upland-rice/
  70. Mishra SS, Behera PK, Panda D. Genotypic variability for drought tolerance-related morpho-physiological traits among indigenous rice landraces of Jeypore tract of Odisha, India. Journal of Crop Improvement. 2019;33(2):254-78.
  71. https://doi.org/10.1080/15427528.2019.1579138
  72. Akinwale MG, Gregorio G, Nwilene F, Akinyele BO, Ogunbayo SA, Odiyi AC. Heritability and correlation coefficient analysis for yield and its components in rice (Oryza sativa L.). African Journal of Plant Science. 2011;5(3):207-12.
  73. https://doi.org/10.3923/ijpbg.2011.224.234
  74. Gunasekaran A, Seshadri G, Ramasamy S, Muthurajan R, Karuppasamy KS. Identification of newer stable genetic sources for high grain number per panicle and understanding the gene action for important panicle traits in rice. Plants. 2023;12(2):250.
  75. https://doi.org/10.3390/plants12020250
  76. Das S, Das SS, Chakraborty I, Roy N, Nath MK, Sarma D. Principal component analysis in plant breeding. Biomolecule Reports. 2017;3:1-3.
  77. https://www.mdpi.com/journal/biomolecules
  78. Al-daej MI, Rezk AA, El-Malky MM, Shalaby TA, Ismail M. Comparative genetic diversity assessment and marker-trait association using two DNA marker systems in rice (Oryza sativa L.). Agronomy. 2023;13(2):329.
  79. https://doi.org/10.3390/agronomy13020329
  80. Saito H, Orn C, Thun V, Ouk M, Tomita A, Sasaki K et al. Diversity of traits related to panicle architecture and grain size in Cambodian rice germplasm and newly developed mini-core collection. Japan Agricultural Research Quarterly: JARQ. 2023;57(1):21-35.
  81. https://doi.org/10.6090/jarq.57.21
  82. Chakma SP, Huq H, Mahmud F, Husna A. Genetic diversity analysis in rice (Oryza sativa L.). Bangladesh Journal of Plant Breeding and Genetics. 2012;25(1):31-39.
  83. https://doi.org/10.3329/bjpbg.v25i1.17010

Downloads

Download data is not yet available.