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

Research Articles

Vol. 12 No. sp4 (2025): Recent Advances in Agriculture by Young Minds - III

Unravelling genetic variability and character association study for cooking quality attributing traits for the selection of promising genotypes in rice

DOI
https://doi.org/10.14719/pst.9706
Submitted
29 May 2025
Published
06-10-2025 — Updated on 17-10-2025
Versions

Abstract

Rice (Oryza sativa L.) is a major cereal crop in the world, particularly in Asia, where it is a staple food for 90 % of the population. The current research was aimed at determining the better genotypes for cooking quality characteristics by utilizing forty-three genotypes of rice along with two checks, viz: Pooja and RNR 15048. The experiment was carried out during the summer season of 2024 at Post Graduate Research Farm, M.S. Swaminathan School of Agriculture, Centurion University of Technology and Management, Paralakhemundi, India. The design of experiment was Randomized Block Design (RBD) with three replications. Study revealed significant difference among all the studied parameters through analysis of variance which extend scope of further study. Genetic parameters revealed that phenotypic coefficient variation is higher than genotypic coefficient of variation indicates along with genotypic environment also played key role to influence the studied characters. High heritability coupled with high to moderate genetic advance as percent of mean noted for all the studied characters signify the predominance of additive gene action henceforth, direct selection would be rewarding. Character association and partial regression study revealed significant association among the studied variables. The significant character such as seed protein content highest exhibited by POO7SD (8 %), amylose content exhibited highest in Durgasal (24 %), on contrary lowest was revealed by Mugi (10 %). Genotypes RNR 15048, Pusa Basmati and POO7SD were found to be superior for biochemical and cooking quality traits and hold promise for future programs of improvement. Which clearly signify future potential to unravel qualitative breeding by seeing India’s opportunities in global market through Basmati rice. Therefore, further exploration of aforementioned genotypes will ultimately help to strengthen India’s qualitative rice market in domestic and international pace.

References

  1. 1. Tripathy S, Meena S, Babu S, Das TK, Dhar S. Productivity and economics of rice (Oryza sativa L) through phosphorus management in North-East India. Indian J Agric Sci. 2021;91:799-801. https://doi.org/10.56093/ijas.v91i5.113109
  2. 2. Bao J, Deng B, Zhang L. Molecular and genetic bases of rice cooking and eating quality: An updated review. Cereal Chem. 2023;100.
  3. https://doi.org/10.1002/cche.10715
  4. 3. Huang Y, Wang H, Zhu Y, Huang X, Li S, Wu X, et al. THP9 enhances seed protein content and nitrogen-use efficiency in maize. Nature. 2022;612:292-300. https://doi.org/10.1038/s41586-022-05441-2
  5. 4. Fu YY, Hua Y, Luo T, Liu C, Zhang B, Zhang X, et al. Generating waxy rice starch with target type of amylopectin fine structure and gelatinization temperature by waxy gene editing. Carbohydr Polym. 2023;306. https://doi.org/10.1016/j.carbpol.2023.120595
  6. 5. Li X, Zhang M, Xiao Z, Liu L, Cao F, Chen J, et al. Relationships between texture properties of cooked rice with grain amylose and protein content in high eating quality indica rice. Cereal Chem. 2024;101(3):577-82. https://doi.org/10.1002/cche.10759
  7. 6. Wang C, Li H, Long Y, Dong Z, Wang J, Liu C, et al. Systemic investigation of genetic architecture and gene resources controlling kernel size-related traits in maize. Int J Mol Sci. 2023;24(2):1025. https://doi.org/10.3390/ijms24021025
  8. 7. Juliano BO. A simplified assay for milled-rice amylose. Cereal Sci Today. 1971;16(10):334-8.
  9. 8. Lowry OH, Rosebrough NJ, Farr AL, Randall RJ. Protein measurement with the folin-phenol reagent. J Biol Chem. 1951;193:265-75.
  10. https://doi.org/10.1016/S0021-9258(19)52451-6
  11. 9. Hussain AA, Maurya DM, Vaish CP. Studies on quality status of indigenous upland rice (Oryza sativa L). Indian J Genet. 1987;47(2):145-52.
  12. 10. Hsu YC, Tseng MC, Wu YP, Lin MY, Wei FJ, Hwu KK, et al. Genetic factors responsible for eating and cooking qualities of rice grains in a recombinant inbred population of an inter-subspecific cross. Mol Breed. 2014;34(2):655-73. https://doi.org/10.1007/s11032-014-0065-8
  13. 11. Cruz M, Arbelaez JD, Loaiza K, Cuasquer J, Rosas J, Graterol E. Genetic and phenotypic characterization of rice grain quality traits to define research strategies for improving rice milling, appearance and cooking qualities in Latin America and the Caribbean. Plant Genome. 2021;14(3):e20134. https://doi.org/10.1002/tpg2.20134
  14. 12. Panse VG, Sukhatme PV. Statistical methods for agricultural workers. New Delhi: ICAR; 1967.
  15. 13. Fisher RA, Yates F. Statistical tables for biological, agricultural and medical research. London: Oliver and Boyd; 1963:46-63.
  16. 14. Kobayashi K, Alam SB. Explainable, interpretable and trustworthy AI for an intelligent digital twin: A case study on remaining useful life. Eng Appl Artif Intell. 2024;129:107620. https://doi.org/10.1016/j.engappai.2023.107620
  17. 15. Alam M, Lou G, Abbas W, Osti R, Ahmad A, Bista S, et al. Improving rice grain quality through ecotype breeding for enhancing food and nutritional security in Asia-Pacific region. Rice.2024;17:47.https://doi.org/10.1186/s12284-024-00725-9
  18. 16. Maurya RK, Dwivedi D, Khan N, Giri S, Dixit S. Genetic variability studies for qualitative and quantitative traits in rice (Oryza sativa L). Pharma Innov J. 2022;11(5):1140-3.
  19. 17. Singh AK, Dwivedi DK, Kumar D, Singh A, Dixit S, Khan NA, et al. Genetic variability, character association and path coefficient analysis in rice (Oryza sativa L) genotypes of semi-arid region of India. Indian J Agric Sci. 2023;93(8):844-9.
  20. https://doi.org/10.56093/ijas.v93i8.137199
  21. 18. Nirmaladevi G, Padmavathi G, Kota SS, Babu VR. Genetic variability, heritability and correlation coefficients of grain quality characters in rice (Oryza sativa L). Food Addit Contam. 2015;25(7):841-50.
  22. 19. Sadhana P, Raju CD, Rao LV, Kuna A. Studies on variability, correlation and path coefficient analysis for yield and quality traits in rice (Oryza sativa L) genotypes. Electron J Plant Breed. 2022;13(2):670-8. https://doi.org/10.37992/2022.1302.084
  23. 20. Roy A, Hijam L, Roy SK. Genetic variability and character association studies for quality attributing traits in rice (Oryza sativa L). Electron J Plant Breed. 2021;12(4):1201-8. https://doi.org/10.37992/2021.1204.165
  24. 21. Samak NA, Hittalmani S, Shashidhar N, Biradar H. Exploratory studies on genetic variability and genetic control for protein and micronutrient content in F1 and F2 generation of rice (Oryza sativa L). Asian J Plant Sci. 2011;10(7):376-9.
  25. https://doi.org/10.3923/ajps.2011.376.379
  26. 22. Patel JR, Saiyad MR, Prajapati KN, Patel RA, Bhavani RT. Genetic variability and character association studies in rainfed upland rice (Oryza sativa L). Electron J Plant Breed. 2014;5(3):531-7.
  27. 23. Roy A, Rout S, Hijam L, Sadhu S, Sekar P, Ghosh A, et al. Multivariate genetic analyses unveil the complexity of grain yield and attributing traits diversity in rice (Oryza sativa L) landraces from north-eastern India. Plant Sci Today. 2024;11(2):29-37.
  28. 24. Taghinezhad E, Khoshtaghaza MH, Minaei S, Suzuki T, Brenner T. Relationship between degree of starch gelatinization and quality attributes of parboiled rice during steaming. Rice Sci.2016;23(6):339-44. https://doi.org/10.1016/j.rsci.2016.06.007
  29. 25. Chakraborty R, Chakraborty S, Dutta BK, Paul SB. Genetic variability and genetic correlation among nutritional and cooking quality traits in bold grain rice. Oryza. 2009;46(1):1-5.
  30. 26. Singh AK, Singh PK, Nandan R, Rao M. Grain quality and cooking properties of rice germplasm. Ann Plant Soil Res. 2012;14(1):52-7.
  31. 27. Lenka D, Mishra B. Path coefficient analysis of yield in rice varieties. Indian J Agric Sci. 1971;43:376-9.
  32. 28. Khan M, Dar Z, Dar S. Breeding strategies for improving rice yield-A review. Agric Sci. 2015;6:467-78.
  33. https://doi.org/10.4236/as.2015.65046
  34. 29. Singh V, Singh AK, Mohapatra T, G S, Ellur R. Pusa Basmati 1121 - a rice variety with exceptional kernel elongation and volume expansion after cooking. Rice. 2018;11(1):19. https://doi.org/10.1186/s12284-018-0213-6
  35. 30. Sarkar S, Sarkar J, Limboo S, Yonzon BT, Roy SC. Characterization of some cultivated rice (Oryza sativa L) based on phenotypic, physicochemical and cooking properties. NBU J Plant Sci. 2022;14:25-31. https://doi.org/10.55734/NBUJPS.2022.v14i01.004
  36. 31. Abdelsalam KMH, Shaalan AM, Abou El-Soud GM, El-Dalil MA, Marei AM, El-Moneim DA, et al. Comprehensive quality profiling and multivariate analysis of rice (Oryza sativa L) cultivars: integrating physical, cooking, nutritional and micronutrient characteristics for enhanced varietal selection. BMC Plant Biol. 2025;25:492. https://doi.org/10.1186/s12870-025-06438-5
  37. 32. John D, Raman M. Physicochemical properties, eating and cooking quality and genetic variability: A comparative analysis in selected rice varieties of South India. Food Prod Process Nutr. 2023;5:49. https://doi.org/10.1186/s43014-023-00164-x
  38. 33. Banerjee S, Mukherjee A, Kamboj S. Precision agriculture revolution: Integrating digital twins and advanced crop recommendation for optimal yield. 2025;5(1):1-12.

Downloads

Download data is not yet available.