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Plant Science Today (PST)

Research Articles

Early Access

Multivariate analysis for improving selection of yield and related traits in rice (Oryza sativa L.)

DOI
https://doi.org/10.14719/pst.8994
Submitted
21 April 2025
Published
17-10-2025
Versions

Abstract

Rice (Oryza sativa L.) serves as a staple food for nearly half of the world population, with yield being critical traits for both consumers and food security. In this study, 45 diverse rice genotypes, including standard checks, were evaluated for yield and related agronomic traits over the 2023 and 2024 growing seasons. The experiment was carried out at lovely professional university, Jalandhar, Punjab, using a randomized complete block design (RCBD) with three replications. Rice genotypes such as Goyadi (G35), Kalamati (G39), AAU DR-1 (G16), IR 167 1662 (G40) and Mala Gauri (G26) showed the maximum potential for achieving superior seed yield per plant (SYP). These genotypes consistently exhibited robust average results in various traits related to yield. In terms of specific traits, IR 82635-B-B-75-2 (G41), G39, CO-51 (G42) and Kanchan (G14) were identified for earliest Days to 50 % flowering (DFF), while IR 167 1662 (G40), Khajur (G25), Asamiya Dhan (G15), CO-51 (G42) and IR 82635-B-B-75-2 (G41) were the earliest to reach maturity. For reduced Plant height (PH), genotypes Fara Dhan (G37), Kani Dhan (G36), Tama Koni (G34), Khajur (G25) and Bhushu (G11) stood out. The promising performance of these genotypes across multiple yield-contributing traits suggests they can serve as valuable male parents in hybridization programs. High estimates of phenotypic coefficient of variation (PCV) and Genotypic coefficient of variation (GCV) coefficients of variation remained observed for both Harvest index (HI) and Seed yield per plant (SYP), indicating significant genetic variability with minimal environmental influence. Cluster analysis revealed that Cluster II had the minimum intra-cluster distance (ICD), suggesting greater homogeneity among its genotypes, whereas Cluster IV ICD. The maximum genetic divergence was found among Clusters IV and VII, while the least was between Clusters IV and VI. Traits such as PH and grains/panicle (GPP) contributed most to the total genetic divergence. Principal Component Analysis showed that PC1 was largely influenced by traits like 1000 seeds weight (TSW), SYP and DFF, while PC2, PC3 and PC4 contributed significantly to yield enhancement, supporting their use in selection for yield improvement.

References

  1. 1. Madishetty AR, Lal GM, Adarsh K. Genetic variability and correlation studies for yield and yield related traits in rice (Oryza sativa L.). Int J Plant Soil Sci. 2023;35(20):1165-76. https://doi.org/10.9734/ijpss/2023/v35i203914
  2. 2. Sai BH, Reddy BRK, Priya MS, Vemireddy LR. Genetic diversity analysis for yield and yield attributing characters in rice (Oryza sativa L.). Electron J Plant Breed. 2022;13(4):1282-7. https://doi.org/10.37992/2022.1304.161
  3. 3. Chauhan S, Mandliya T, Jain D, Joshi A, Khatik CL, Singh A, et al. Early selective strategies for higher yielding bio-economic Indian ginseng based on genotypic study through metabolic and molecular markers. Saudi J Biol Sci. 2022;29(4):3051-61.
  4. https://doi.org/10.1016/j.sjbs.2022.01.030
  5. 4. Garbanzo G, Cameira MDR, Paredes P. The mangrove swamp rice production system of Guinea Bissau: Identification of the main constraints associated with soil salinity and rainfall variability. Agronomy. 2024;14(3):468.https://doi.org/10.3390/agronomy14030468
  6. 5. Agalya JS, Hari PP, Ramchander S, Kumar P, Devesena N, Naveenkumar R, et al. Assessment of variability parameters and diversity of panicle architectural traits associated with yield in rice (Oryza sativa L.). Plant Sci Today. 2024;11(1):109-18. https://doi.org/10.14719/pst.2658
  7. 6. Sabar M, Mustafa SE, Ijaz M, Khan RAR, Shahzadi F, Saher H, et al. Rice breeding for yield improvement through traditional and modern genetic tools. Eur J Ecol Biol Agric. 2024;1(1):14-9.
  8. https://doi.org/10.59324/ejeba.2024.1(1).02
  9. 7. Faysal ASM, Ali L, Azam MG, Sarker U, Ercisli S, Golokhvast KS, et al. Genetic variability, character association and path coefficient analysis in transplant Aman rice genotypes. Plants. 2022;11(21):2952. https://doi.org/10.3390/plants11212952
  10. 8. Fentie DB, Abera BB, Ali HM. Association of agronomic traits with grain yield of lowland rice (Oryza sativa L.) genotypes. Int J Agric Sci. 2021;8(3):2348-97.
  11. 9. IRRI. Standard evaluation system (SES) for rice. 5th ed. Philippines: IRRI; 2013.
  12. 10. Prakash S, Reddy SS, Chaudhary S, Vimal S, Kumar A. Multivariate analysis in rice (Oryza sativa L.) germplasms for yield attributing traits. Plant Sci Today. 2024;11(1):64-75. https://doi.org/10.14719/pst.2231
  13. 11. Johnson HW, Robinson HF, Comstock RE. Estimation of genetic and environmental variability in soybeans. Agron J. 1955;47:314-8. https://doi.org/10.2134/agronj1955.00021962004700070009x
  14. 12. Rahangdale S, Singh Y, Upadhyay PK, Koutu GK. Principal component analysis of JNPT lines of rice for the important traits responsible for yield and quality. Indian J Genet Plant Breed. 2021;81(1):127-31. https://doi.org/10.31742/IJGPB.81.1.14
  15. 13. Behera PP, Singh SK, Sivasankarreddy K, Majhi PK, Reddy BJ, Singh DK. Yield attributing traits of high zinc rice (Oryza sativa L.) genotypes with special reference to principal component analysis. Environ Conserv J. 2022;23(3):458-70. https://doi.org/10.36953/ECJ.10302233
  16. 14. Islam SS, Nualsri C, Hasan AK. Character association and path analysis studies in upland rice (Oryza sativa) genotypes. Res Crops. 2021;22(2):239-45. https://doi.org/10.31830/2348-7542.2021.063
  17. 15. Singh S, Singh AK, Singh SP, Singh AK, Yadav RK. Correlation and path coefficient analysis of some rice genotypes (Oryza sativa L.). Int J Environ Clim Change. 2022;12:1100-9. https://doi.org/10.9734/ijecc/2022/v12i1030905
  18. 16. Burton GW, Devane EM. Estimating heritability in tall fescue (Festuca arundinacea) from replicated clonal material. Agron J. 1953;45:478-81. https://doi.org/10.2134/agronj1953.00021962004500100005x
  19. 17. Khan MAR, Mahmud A, Islam MN, Ghosh UK, Hossain MS. Genetic variability and agronomic performances of rice genotypes in different growing seasons in Bangladesh. J Agric Food Res. 2023;14:100750. https://doi.org/10.1016/j.jafr.2023.100750
  20. 18. Gomez KA, Gomez AA. Statistical procedures for agricultural research. 2nd ed. New York: John Wiley and Sons; 1984:680.
  21. 19. Storey VC, Baskerville RL, Kaul M. Reliability in design science research. Inf Syst J. 2025;35(3):984-1014. https://doi.org/10.1111/isj.12564
  22. 20. Heera PK, Ram M, Kumar R, Murali S, Kumar AS. Analysis of genetic variability, heritability and genetic advance for yield and yield associated traits in rice (Oryza sativa L.). Ecol Environ Conserv. 2023;29:S160-3.
  23. 21. Williams K, Mishra A, Verma A, Suresh BG, Lavanya GR. Genetic variability and correlation studies for yield and yield related traits in rice (Oryza sativa L.) genotypes. Int J Curr Microbiol Appl Sci. 2021;10(1):752-64. https://doi.org/10.20546/ijcmas.2021.1001.093
  24. 22. Verma Y, Tomar NS, Saran D. Assessment of genetic variability for yield and its contributing traits in rice (Oryza sativa L.). Int J Environ Clim Change. 2023;13(5):36-9.
  25. https://doi.org/10.9734/ijecc/2023/v13i51742
  26. 23. Manohara KK, Morajkar S, Shanbagh Y. Genetic analysis of grain yield and its associated traits in diverse salt-tolerant rice genotypes under coastal salinity condition. J Cereal Res. 2020;12(3):290-6.
  27. https://doi.org/10.25174/2582-2675/2020/105442
  28. 24. Chand PA, Gangwar LK, Kumar M, Singh A, Vaishali, Kumar R, et al. Evaluation of variability, heritability and genetic advance in relation to seed yield and its attributing traits in rice (Oryza sativa L.). Int J Adv Biochem Res. 2024;8(9):1112-4. https://doi.org/10.33545/26174693.2024.v8.i9n.2351
  29. 25. Yadav SPS, Bhandari S, Ghimire NP, Mehata DK, Majhi SK, Bhattarai S, et al. Genetic variability, character association, path coefficient and diversity analysis of rice (Oryza sativa L.) genotypes based on agro-morphological traits. Int J Agron. 2024;2024:9946332.
  30. https://doi.org/10.1155/2024/9946332
  31. 26. Singh S, Singh AK, Singh SP, Singh AK, Yadav RK. Correlation and path coefficient analysis of some rice genotypes (Oryza sativa L.). Int J Environ Clim Change. 2022;12:1100-9. https://doi.org/10.9734/ijecc/2022/v12i1030905
  32. 27. Saran D, Gauraha D, Sao A, Sandilya VK, Kumar R. Correlation and path coefficient analysis for yield and yield attributing traits in rice (Oryza sativa L.). Int J Plant Soil Sci. 2023;35(18):94-101. https://doi.org/10.9734/ijpss/2023/v35i183271
  33. 28. Saran D, Gauraha D, Ragi S, Sao A, GJ A. Studies on genetic parameters for yield and yield attributing traits in rice (Oryza sativa L.). Plant Arch. 2025;25(1):1651-7.
  34. https://doi.org/10.51470/PLANTARCHIVES.2025.v25.supplement-1.227
  35. 29. Jangala DJ, Amudha K, Geetha S, Uma D. Studies on genetic diversity, correlation and path analysis in rice germplasm. Electron J Plant Breed. 2022;13(2):655-62.
  36. https://doi.org/10.37992/2022.1302.081
  37. 30. Dabalo DY, Singh BCS, Weyessa B. Genetic variability and association of characters in linseed (Linum usitatissimum L.) plant grown in central Ethiopia region. Saudi J Biol Sci. 2020;27(8):2192-206. https://doi.org/10.1016/j.sjbs.2020.06.043
  38. 31. Bhat R, Singh AK, Salgotra RK, Sharma M, Bagati S, Hangloo S, et al. Statistical description, genetic variability, heritability and genetic advance assessment for various agronomical traits in F2 population of rice (Oryza sativa L.). J Pharmacogn Phytochem. 2018;7(3):985-92.
  39. 32. Khan MAR, Mahmud A, Islam MN, Ghosh UK, Hossain MS. Genetic variability and agronomic performances of rice genotypes in different growing seasons in Bangladesh. J Agric Food Res. 2023;14:100750. https://doi.org/10.1016/j.jafr.2023.100750
  40. 33. Sudeepthi K, Srinivas T, Ravikumar BNVSR, Jyothula DPB, Nafeezumar SK. Genetic divergence studies for yield and yield component traits in rice (Oryza sativa L.). Multilogic Sci. 2020;9:415-8.
  41. https://doi.org/10.9734/cjast/2020/v39i130482
  42. 34. Keerthiraj B, Biju S. Genetic variability, heritability and genetic advance of yield and lodging-related traits in rice (Oryza sativa L.). Electron J Plant Breed. 2020;11(4):1093-8. https://doi.org/10.37992/2020.1104.177
  43. 35. Demeke B, Dejene T, Abebe D. Genetic variability, heritability and genetic advance of morphological, yield related and quality traits in upland rice (Oryza sativa L.) genotypes at Pawe, northwestern Ethiopia. Cogent Food Agric. 2023;9:2157099.
  44. https://doi.org/10.1080/23311932.2022.2157099
  45. 36. Amegan E, Efisue A, Akorod M, Shittu A, Tonegnikes F. Genetic diversity of Korean rice (Oryza sativa L.) germplasm for yield and yield related traits for adoption in rice farming system in Nigeria. Int J Genet Genomics. 2020;8(1):19-28. https://doi.org/10.11648/j.ijgg.20200801.13
  46. 37. Chacko A, Jayalekshmy VG, Shahiba AM. Studies on PCV, GCV, heritability and genetic advance in rice genotypes for yield and yield components. Int J Plant Soil Sci. 2023;35(16):324-30. https://doi.org/10.9734/ijpss/2023/v35i163266
  47. 38. Yesmin MA, Salim M, Monshi FI, Hasan AK, Hannan A, Islam SS, et al. Morpho-physiological and genetic characterization of transplanted Aman rice varieties under old Brahmaputra flood plain (AEZ-9) in Bangladesh. Trop Agric Res Ext. 2022;25(1):71-84. https://doi.org/10.4038/tare.v25i1.5573
  48. 39. 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 Breed Biotechnol. 2023;11(2):117-29. https://doi.org/10.9787/PBB.2023.11.2.117
  49. 40. Mandavi J, Lokesh P, Nair S, Sao A, Verulkar S, Saxena RR, et al. Cluster analysis of 55 rice (Oryza sativa L.) germplasm. Int J Stat Appl Math. 2023;8(SP-6):71-4. https://doi.org/10.33545/26174693.2023.v7.i2Sg.256
  50. 41. Faysal ASM, Ali L, Azam MG, Sarker U, Ercisli S, Golokhvast KS, et al. Genetic variability, character association and path coefficient analysis in transplant Aman rice genotypes. Plants. 2022;11(21):2952. https://doi.org/10.3390/plants11212952

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