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Plant Science Today (PST)

Research Articles

Vol. 13 No. sp1 (2026): Recent Advances in Agriculture

Pre-breeding evaluation of rice genotypes for biofortification in Telangana region

DOI
https://doi.org/10.14719/pst.12264
Submitted
14 October 2025
Published
08-04-2026

Abstract

In India, rice (Oryza sativa L.) is the primary staple food consumed by a significant percentage of its population, but the polished grain of rice is low in essential micronutrients, including iron (Fe) and zinc (Zn), which contributes to micronutrient malnutrition in a huge percentage of the Indian population. The aim of the current research was to assess genetic variation, agronomic performance, grain quality traits and micronutrient content of famous rice genotypes grown in Telangana and Andhra Pradesh regions with the aim of finding an appropriate donor to practice genetic biofortification. Evaluation of 16 rice genotypes was done at the kharif season in 2024 under irrigated conditions and with a randomized block design in 3 replications. The analysis of variance, the parameters of genetic variability, correlation and path coefficient analysis and principal component analysis (PCA) were used to analyze 18 agronomic, quality and nutritional traits. The genetic variation of most traits was found to be highly significant (p<0.01). Both grain iron and zinc levels showed a moderate level of genotypic coefficient of variation (12.50 % and 14.05 %, respectively) with high heritability and genetic progression, which mean that it is highly genetically controlled. Iron and zinc contents had a strong positive relationship (r = 0.65), which implied that it would be feasible to improve simultaneously. Principal component analysis indicated that the four major components could account 82.2 % of the overall variation and the loading of iron and zinc was also high in the second major component. KNM 118 and Bhadrakali had the best iron (15.8 and 14.5 mg kg-1) and zinc (28.3 and 27.0 mg kg-1), whereas KNM 1638 and Varalu had better grain yield and productivity. The findings show that there is a genetic variability that can be exploited to biofortify rice with micronutrients in popular rice genotypes and indicate potential donor lines to generate high yield, iron and zinc-enriched rice varieties. These genotypes can also be used in targeted breeding programmes and confirmed by multi-location trials that can be used to enhance nutritional sustainability.

References

  1. 1. Hoyos V, Plaza G, Li X, Caicedo AL. Something old, something new: evolution of Colombian weedy rice (Oryza spp.) through de novo de-domestication, exotic gene flow and hybridization. Evol Appl. 2020;13(8):1968–83. https://doi.org/10.1111/eva.12955
  2. 2. Chang YE, Song CH, Guang CH. Geographic variation in the yield formation of single-season high-yielding hybrid rice in southern China. J Integr Agric. 2021;20(2):438–49. https://doi.org/10.1016/S2095-3119(20)63360-3
  3. 3. Amagliani L, O'Regan J, Kelly AL, O'Mahony JA. The composition, extraction, functionality and applications of rice proteins: a review. Trends Food Sci Technol. 2017;64:1–12. https://doi.org/10.1016/j.tifs.2017.01.008
  4. 4. U.S. Department of Agriculture, Agricultural Research Service. FoodData Central [Internet]. 2020 [cited 2026]. https://fdc.nal.usda.gov/fdc-app.html#/food-details/790214/nutrients
  5. 5. National Institutes of Health, Office of Dietary Supplements. Iron: fact sheet for health professionals [Internet]. Bethesda (MD): NIH; 2020 [cited 2026]. https://ods.od.nih.gov/factsheets/Iron-HealthProfessional/
  6. 6. Hussain A, Jiang W, Wang X, Shahid S, Saba N, Ahmad M, et al. Mechanistic impact of zinc deficiency in human development. Front Nutr. 2022;9:717064. https://doi.org/10.3389/fnut.2022.717064
  7. 7. Yilmaz H, Yilmaz A. Hidden hunger in the age of abundance: the nutritional pitfalls of modern staple crops. Food Sci Nutr. 2025;13(2):e4610. https://doi.org/10.1002/fsn3.4610
  8. 8. Zulfiqar U, Khokhar A, Maqsood MF, Shahbaz M, Naz N, Sara M, et al. Genetic biofortification: advancing crop nutrition to tackle hidden hunger. Funct Integr Genomics. 2024;24(2):34. https://doi.org/10.1007/s10142-024-01308-z
  9. 9. Saikanth D, Kesarwani A, Nain M, Pandey SK, Singh BV, Maurya C. Bio-fortification and its impact on global health. J Exp Agric Int. 2023;45(10):106–15. https://doi.org/10.9734/jeai/2023/v45i102203
  10. 10. Kiran A, Wakeel A, Mahmood K, Mubaraka R, Hafsa, Haefele SM. Biofortification of staple crops to alleviate human malnutrition: contributions and potential in developing countries. Agronomy. 2022;12(2):452. https://doi.org/10.3390/agronomy12020452
  11. 11. Fisher RA, Yates F. Statistical tables for biological, agricultural and medical research. Edinburgh (UK): Oliver & Boyd; 1938.
  12. 12. Wright S. Correlation and causation. J Agric Res. 1921;20(7):557–85.
  13. 13. Wright S. The analysis of variance and the correlations between relatives with respect to deviations from an optimum. J Genet. 1935;30:243–56. https://doi.org/10.1007/BF02982239
  14. 14. Dewey DR, Lu K. A correlation and path-coefficient analysis of components of crested wheatgrass seed production. Agron J. 1959;51(9):515–18. https://doi.org/10.2134/agronj1959.00021962005100090002x
  15. 15. Jambhulkar RK, Chitrala T, Bhor T. Genetic variability, heritability and correlation analysis of rice (Oryza sativa) for iron and zinc content: implications for biofortification and yield improvement. Int J Adv Biochem Res. 2024;8(5):39–44. https://doi.org/10.33545/26174693.2024.v8.i5a.1054
  16. 16. Ratnam TV, Kumar BR, Rao LV, Srinivas T, Kumar AA. Assessment of genetic variability, character association and path analysis for yield and quality traits in zinc- and iron-rich landraces of rice. Agric Sci Dig. 2024;44(2):289–94. https://doi.org/10.18805/ag.D-5678
  17. 17. Bhor TJ, Jambhulkar RK, Kashid NV. Genetic variability for yield components, iron and zinc contents in rice (Oryza sativa L.) genotypes. J Rice Res. 2024;17(2):13. https://doi.org/10.58297/OLXU5090
  18. 18. Kumar B, Singh MK, Kumari N, Kumari S, Singh D. Variability assessment and screening of superior rice (Oryza sativa L.) genotypes for grain micronutrients and yield components. Electron J Plant Breed. 2024;15(3):794–800. https://doi.org/10.37992/2024.1503.088
  19. 19. Begum S, Srinivas B, Ram Reddy V, Aruna Kumari C. Multiple regression, correlation and path analysis of gall midge incidence, yield and yield components in rice (Oryza sativa L.) hybrids. Curr J Appl Sci Technol. 2021;40(2):33–45. https://doi.org/10.9734/cjast/2021/v40i231250
  20. 20. Vanlalrinngama C, Jha B, Singh SK, Tigga A, Kumar B, Kumari N, et al. Trait association studies in diverse genotypes of rice for their utilization in biofortification. Environ Conserv J. 2023;24(3):152–6. https://doi.org/10.36953/ECJ.14472440
  21. 21. Nachimuthu VV, Robin S, Sudhakar D, Rajeswari S, Raveendran M, Subramanian KS, et al. Genotypic variation for micronutrient content in traditional and improved rice lines and its role in biofortification programme. Indian J Sci Technol. 2014;7(9):1414–25. https://doi.org/10.17485/ijst/2014/v7i9.15
  22. 22. Babu VR, Rani GU, Reddy TD, Reddy DVV. Association of grain iron and zinc content with yield in high-yielding rice cultivars. Oryza. 2013;50(1):41–44.
  23. 23. Maneesha M, Shankar VG, Srinivas B, Hari Y. Correlation and path coefficient analysis for grain yield, head rice recovery and quality traits in rice hybrids (Oryza sativa L.). Int J Plant Soil Sci. 2024;36(8):808–16. https://doi.org/10.9734/ijpss/2024/v36i84911
  24. 24. Gudepu S, Chennamadhavuni DR, Katragadda S. Variability and association studies for yield and yield contributing traits in long grain rice (Oryza sativa L.). Oryza. 2022;59(4):409–17. https://doi.org/10.35709/ory.2022.59.4.3
  25. 25. Madishetty AR, Adarsh K, Lal GM. 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
  26. 26. Chattar BR, Bhor TJ, Chavan SS, Chopade GU. Genetic variability, character association and path analysis studies in rice genotypes (Oryza sativa L.). J Adv Biol Biotechnol. 2024;27(12):438–49. https://doi.org/10.9734/jabb/2024/v27i121792
  27. 27. Raza Q, Riaz A, Sabar M, Atif RM, Bashir K. Meta-analysis of grain iron and zinc associated QTLs identified hotspot chromosomal regions and positional candidate genes for breeding biofortified rice. Plant Sci. 2019;288:110214. https://doi.org/10.1016/j.plantsci.2019.110214
  28. 28. Pippal A, Bhusal N, Meena RK, Bishnoi M, Bhoyar PI, Jain RK. Identification of genomic locations associated with grain micronutrients (iron and zinc) in rice (Oryza sativa L.). Genet Resour Crop Evol. 2022;69(1):221–30. https://doi.org/10.1007/s10722-021-01222-4

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