Trait analysis of short duration boro rice (Oryza sativa L.) varieties in northern region of Bangladesh: Insights from heatmap, correlation and PCA

Authors

  • Tapon Kumar ROY Bangladesh Rice Research Institute, Entomology Division, BRRI (BD) https://orcid.org/0000-0002-9815-319X
  • Anamika SANNAL Bangabandhu Sheikh Mujibur Rahman Agricultural University, Plant Pathology Division, BSMRAU (BD)
  • S.M.M. Shahriar TONMOY Bangladesh Rice Research Institute, Farm Management Division, BRRI (BD)
  • Sanjida AKTER Bangladesh Rice Research Institute, Entomology Division, BRRI (BD)
  • Bhagyobandhu ROY ICT Division, Bangladesh (BD)
  • Md. Masud RANA Bangladesh Rice Research Institute, Agronomy Division, BRRI (BD)
  • Zakaria ALAM Bangladesh Agriculture Research Institute, Tuber Crops Research Centre, BARI (BD)
  • Md. Rokebul HASAN Bangladesh Rice Research Institute, Plant Breeding Division, BRRI (BD)

DOI:

https://doi.org/10.55779/ng42175

Keywords:

biplot, cluster, grain yield, HYV, multi-location, scree plot, PCA

Abstract

The role of genetic variation is utmost importance in the selection of a desirable genotype for breeding programs. In the northern region of Bangladesh, the performance of five short duration boro rice varieties (BRRI dhan28, BRRI dhan74, BRRI dhan81, BRRI dhan88, and Bangabandhu dhan100) on yield and yield-contributing traits were evaluated in four locations. Yield attributes tiller hill-1 (TN), panicle hill-1 (PN), filled grain panicle-1 (FG), panicle length (PL), 1000-grain weight (TGW), and harvest index (HI), showed a positive correlation with grain yield (GY). Conversely, spikelet sterility (SSP) and unfilled grains panicle-1 (UFG) showed negative associations with grain yield. Principal component analysis (PCA) revealed that the first three components accounted for 89.60% of variability. The highest positive eigenvalue was observed in DF, DM, BY, HI, PN, SY, TN, PL and GY in PC1, indicating their significant influence on the overall genotype variations. PC2 was primarily driven by plant height (PH) and FG, while PC3 driven by TGW and UFG. The results suggest that grain yield is highly influenced by FG, PH, DM, DF, PN, TN, PL, TGW, SY, BY, and HI. These components highlighted the importance in distinguishing rice genotypes with higher grain yield potential. By considering these traits, BRRI dhan74 have outperformed other varieties, followed by BRRI dhan88 and Bangabandhu dhan100. BRRI dhan74 is most suitable for all four location followed by BRRI dhan88. The traits such as PN, PL, FG, TGW, PH, & HI significantly influence rice yield and should be prioritized in breeding programs aimed at developing high-yielding rice varieties.

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References

Augustina UA, Iwunor OP, Ijeoma OR (2013). Heritability and character correlation among some rice genotypes for yield and yield components. Journal of Plant Breeding and Genetics 1(2):73-84.

Badshah MA, Hasan MR, Roy TK, Rahman MA (2023). Effect of polythene covering on seedling quality and it’s carryover effect on field duration and grain yield of rice. Bangladesh Rice Journal 26(1):59-68. https://doi.org/10.3329/brj.v26i1.66595

Bandumula N (2018). Rice Production in Asia: Key to Global Food Security. Proceedings of the National Academy of Sciences, India Section B: Biological Sciences 88(4):1323-1328. https://doi.org/10.1007/s40011-017-0867-7

Chakravorty A (2013). Multivariate analysis of phenotypic diversity of landraces of rice of West Bengal. American Journal of Experimental Agriculture 3(1):110-123. https://doi.org/10.9734/AJEA/2013/2303

Clifford HT, Stephenson W (1975). An introduction to numerical classification. Academic Press, Landon, pp 229.

Dhakal A, Pokhrel A, Sharma S, Poudel A (2020). Multivariate analysis of phenotypic diversity of rice (Oryza sativa L.) landraces from Lamjung and Tanahun Districts, Nepal. International Journal of Agronomy 8867961. https://doi.org/10.1155/2020/8867961

Guei RG, Abamu FJ, Karim T, Naman S (2004). Genetic variability in morphological and physiological traits within and among rice species and their interspecific progenies. Agronomie Africaine 16(1):15-32. https://doi.org/10.4314/aga.v16i1.1636

Hairmansis A, Supartopo, Yullianida, Nafisah, Hermanasari R, Puji Lestari A, Suwarno (2022). Genotype-environment interaction and yield stability of upland rice in intercropping cultivation. HAYATI Journal of Biosciences 30(2):292-301. https://doi.org/10.4308/hjb.30.2.292-301

Islam SS, Anothai J, Nualsri C, Soonsuwon W (2020). Analysis of genotype-environment interaction and yield stability of Thai upland rice (Oryza sativa L.) genotypes using AMMI model. Australian Journal of Crop Science 14(2):362-370. https://doi.org/10.21475/ajcs.20.14.02.p1847

Mahendran R, Veerabadhiran P, Robin S, Raveendran M (2015). Principal component analysis of rice germplasm accessions under high temperature stress. International Journal of Agricultural Science and Research 5(3):355-360.

Maji AT (2012). Application of principal component analysis for rice germplasm characterization and evaluation. Journal of Plant Breeding and Crop Science 4(6):87-93. https://doi.org/10.5897/JPBCS11.093

Mandal A, Lal GM, Lavanya GR (2023). Assessment of genetic variability, correlation and path analysis among rice (Oryza sativa L.) landraces genotypes for grain yield characters under irrigated. International Journal of Environment and Climate Change 13(10):55-65. https://doi.org/10.9734/ijecc/2023/v13i102616

McNeill K, Macdonald K, Singh A, Binns AD (2017). Food and water security: Analysis of integrated modeling platforms. Agricultural Water Management 194:100-112. https://doi.org/10.1016/j.agwat.2017.09.001

Messina C, Hammer G, Dong Z, Podlich D, Cooper M (2009). Modelling crop improvement in a G×E×m framework via gene–trait–phenotype relationships. Crop Physiology – Applications for Genetic Improvement and Agronomy. Elsevier, Netherlands 235-265. https://doi.org/10.1016/B978-0-12-374431-9.00010-4

Moosavi M, Ranjbar G, Zarrini HN, Gilani A (2015). Correlation between morphological and physiological traits and path analysis of grain yield in rice genotypes under Khuzestan conditions. Biological Forum 7(1):43-47.

Panigrahi A, kumar Bharathi M, Kumaravadivel N, Ashish Kumar Panigrahi C (2018). Genetic variability and character association studies in advanced backcross generation of rice (Oryza sativa L.). Journal of Pharmacognosy and Phytochemistry 7(1):2397-2400.

Pokhrel A, Dhakal A, Sharma S, Poudel A (2020). Evaluation of physicochemical and cooking characteristics of rice (Oryza sativa L.) landraces of Lamjung and Tanahun Districts, Nepal. International Journal of Food Science 1589150. https://doi.org/10.1155/2020/1589150

Rahman M, Islam M, Rahaman M, Sarkar M, Ahmed R, Kabir M (2021). Identifying the threshold level of flooding for rice production in Bangladesh: An empirical analysis. Journal of Bangladesh Agricultural University 19(2):30-37. https://doi.org/10.5455/JBAU.53297

Rahman MM, Syed MA, Adil M, Ahmad H, Rashid MM (2012). Genetic variability, correlation and path coefficient analysis of some physiological traits of transplanted aman rice (Oryza sativa L.). Middle-East Journal of Scientific Research 11(5):563-566.

Rana MM, Hossain MB, Roy TK, Shultana R, Hasan MR, Naher UA, Biswas JC, Maniruzzaman M (2023). Response of yield and agronomic output of Bangabandhu dhan100 under varying sowing window in cold prone Rangpur region. Indian Journal of Agricultural Research 58(2):259-265. https://doi.org/10.18805/IJARe.AF-796

Ranjkesh N, Talubaghi MJ (2022). Study of genotype × environment interaction on agronomic characteristics and grain yield of 30 rice genotypes. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4223694

Roy SK, Ali MY, Jahan MS, Saha UK, Ahmad-Hamdani MS, Hasan MMAN (2014). Evaluation of growth and yield attributing characteristics of indigenous Boro rice varieties. Life Science Journal 11(4):122-126.

Roy TK, Hasan MA, Pramanik SK, Sikder S (2021). Yield performance of rice varieties under NaCl induced salinity stress in boro season. Journal of Science and Technology 19:40-51.

Roy TK, Tonmoy SM, Sannal A, Akter S, Tarek KH, Rana MM, Hasan MR (2022). Yield performance of some short duration high yielding rice varieties during boro season in northern region of Bangladesh. International Journal of Natural and Social Sciences 9(4):15-21. https://doi.org/10.5281/zenodo.7877953

Sanni KA, Fawole I, Ogunbayo SA, Tia DD, Somado EA, Futakuchi K, Sié M, Nwilene FE, Guei RG (2012). Multivariate analysis of diversity of landrace rice germplasm. Crop Science 52(2):494-504. https://doi.org/10.2135/cropsci2010.12.0739

Shoba D, Vijayan R, Robin S, Manivannan N, Iyanar K, Arunachalam P, Nadarajan N, Pillai MA, Geetha S (2019). Assessment of genetic diversity in aromatic rice (Oryza sativa L.) germplasm using PCA and cluster analysis. Electronic Journal of Plant Breeding 10(3):1095-1104. https://doi.org/10.5958/0975-928X.2019.00140.6

Shrestha J, Singh Kushwaha UK, Maharjan B, Subedi SR, Kandel M, Poudel AP, Yadav RP (2020). Genotype × environment interaction and grain yield stability in Chinese hybrid rice. Ruhuna Journal of Science 11(1):47-58. https://doi.org/10.4038/rjs.v11i1.86

Statista (2021). Global rice production in 2020 and 2021, by country (in million metric tons). Retrieved 2024 March 10 from https://www.statista.com/statistics/271969/world-rice-acreage-since-2008/

Umadevi M, Shanthi P, Saraswathi R (2019). Characterization of rice landraces of Tamil Nadu by multivariate analysis. Electronic Journal of Plant Breeding 10(3):1185-1193. https://doi.org/10.5958/0975-928X.2019.00150.9

USDA (2020). Rice sector at a glance. United States Department of Agriculture. Retrieved 2024 March 10 from https://www.ers.usda.gov/topics/crops/rice/rice-sector-at-a-glance/

Yesmin MA, Salim M, Monshi FI, Hasan AK, Hannan A, Islam SS, Tabassum R (2022). Morpho-physiological and genetic characterization of transplanted aman rice varieties under old Brahmaputra flood plain (Aez-9) in Bangladesh. Tropical Agricultural Research and Extension 25(1):71-84. https://doi.org/10.4038/tare.v25i1.5573

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Published

2024-06-05

How to Cite

ROY, T. K., SANNAL, A., TONMOY, S. S., AKTER, S., ROY, B., RANA, M. M., ALAM, Z., & HASAN, M. R. (2024). Trait analysis of short duration boro rice (Oryza sativa L.) varieties in northern region of Bangladesh: Insights from heatmap, correlation and PCA. Nova Geodesia, 4(2), 175. https://doi.org/10.55779/ng42175

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