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Plant Science Today (PST)

Research Articles

Vol. 13 No. 3 (2026)

Gamma ray-induced genetic variability and multivariate trait analysis in M2 and M3 populations of sorghum (Sorghum bicolor (L.) Moench) genotype ICSV 18002

DOI
https://doi.org/10.14719/pst.14502
Submitted
11 March 2026
Published
07-09-2026 — Updated on 30-09-2026
Versions

Abstract

Induced mutagenesis is an effective strategy for generating novel genetic variability and accelerating crop improvement in sorghum. The present study was conducted at the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru, Telangana, India, during 2023–25 to evaluate dose-dependent radiosensitivity, mutation induction and phenotypic variability in the sorghum genotype ICSV 18002 following gamma irradiation. Radiosensitivity assessment revealed a progressive reduction in seedling height with increasing radiation dose and the LD50 was estimated at approximately 230 Gy, corresponding to a 50 % reduction in seedling height relative to the control. Screening of the M2 population identified chlorophyll-deficient mutants with a mutation frequency of 1.0 %, confirming effective mutation induction. Frequency distribution and genetic parameter analyses indicated substantial induced variability for several agro-morphological and yield traits, such as plant height (PH), internode length (IL), stem girth (SG), panicle length (PL), panicle width (PW), disease score (DS), seed yield per plant (SYPP) and hundred-seed weight (HSW). High genotypic variability coupled with high heritability and genetic advance was observed for SYPP, DS, SG, PW and HSW, suggesting strong prospects for direct selection. Correlation analysis in the M3 generation showed that yield was primarily associated with panicle architecture, particularly PW and PL, while reduced disease incidence contributed positively to productivity. Principal component and hierarchical cluster analyses revealed considerable phenotypic divergence among mutant families, indicating the generation of diverse trait combinations. Standardised deviation (Z-score) analysis identified several superior mutants exhibiting early flowering (74.00 days compared with 79.33 days in the control), reduced PH (278.33 cm compared with 360.56 cm in the control), higher SYPP (up to 63.90 g compared with 16.06 g in the control) and increased HSW (up to 3.49 g compared with 2.21 g in the control). Parent-progeny analysis indicated stronger transmission of structural vegetative traits than complex yield traits, suggesting the need for further generational stabilisation for reliable selection. Overall, the study demonstrates the effectiveness of gamma irradiation in generating useful variability and identifies promising mutant lines for sorghum improvement.

References

  1. 1. Hadebe ST, Modi AT, Mabhaudhi T. Assessing suitability of sorghum to alleviate Sub-Saharan nutritional deficiencies through the nutritional water productivity index in semi-arid regions. Foods. 2021;10(2):385. https://doi.org/10.3390/foods10020385
  2. 2. Hossain MS, Islam MN, Rahman MM, Mostofa MG, Khan MA. Sorghum: A prospective crop for climatic vulnerability, food and nutritional security. J Agric Food Res. 2022;8:100300. https://doi.org/10.1016/j.jafr.2022.100300
  3. 3. Mwamahonje A, Mdindikasi Z, Mchau D, Mwenda E, Sanga D, Garcia-Oliveira AL, et al. Advances in sorghum improvement for climate resilience in the global arid and semi-arid tropics: a review. Agronomy. 2024;14(12):3025. https://doi.org/10.3390/agronomy14123025
  4. 4. Govintharaj VK, Arumugam Pillai M, Sumithra V, Leon AP, Habyarimana E, Yasin JK. Unraveling the genetic basis of resistance traits for fungal diseases in sorghum. Phytopathol Res. 2025;7(1):15. https://doi.org/10.1186/s42483-024-00309-x
  5. 5. Ahumada-Flores S, Gómez Pando LR, Parra Cota FI, de la Cruz Torres E, Sarsu F, de los Santos Villalobos S. Gamma irradiation induces changes of phenotypic and agronomic traits in wheat (Triticum turgidum ssp. durum). Appl Radiat Isot. 2021;167:109490. https://doi.org/10.1016/j.apradiso.2020.109490
  6. 6. Bharat RA, Prathmesh SP, Sarsu F, Suprasanna P. Induced mutagenesis using gamma rays: biological features and applications in crop improvement. OBM Genet. 2024;8(2):233. https://doi.org/10.21926/obm.genet.2402233
  7. 7. Wanga MA, Shimelis H, Horn LN, Sarsu F. The effect of single and combined use of gamma radiation and ethyl methane sulfonate on early growth parameters in sorghum. Plants. 2020;9(7):827. https://doi.org/10.3390/plants9070827
  8. 8. Food and Agriculture Organization of the United Nations, International Atomic Energy Agency. Mutant Variety Database (MVD). https://nucleus.iaea.org/sites/mvd/.
  9. 9. Konzak CF, Nilan RA, Wagner J, Foster RJ. Efficient chemical mutagenesis. In: The use of induced mutations in plant breeding. Report of the FAO/IAEA Technical Meeting. Vienna: International Atomic Energy Agency; 1965. p. 49–70.
  10. 10. Burton GW. Quantitative inheritance in grasses. Proceedings of the Sixth International Grassland Congress. Vol. 1. 1952. p. 277–83.
  11. 11. Lush JL. Intra-sire correlations or regressions of offspring on dam as a method of estimating heritability of characteristics. J Anim Sci. 1940;1940(1):293–301. https://doi.org/10.2527/jas1940.19401293x
  12. 12. Johnson HW, Robinson HF, Comstock RE. Estimates of genetic and environmental variability in soybeans. Agron J. 1955;47:314–18. https://doi.org/10.2134/agronj1955.00021962004700070009x
  13. 13. Falconer DS. Introduction to quantitative genetics. 4th ed. Harlow: Longman; 1996.
  14. 14. Rao CR. The use and interpretation of principal component analysis in applied research. Sankhya Ser A. 1964;26(4):329–58.
  15. 15. Ward JH Jr. Hierarchical grouping to optimize an objective function. J Am Stat Assoc. 1963;58(301):236–44. https://doi.org/10.1080/01621459.1963.10500845
  16. 16. Gaul H. Mutations in plant breeding. Radiat Bot. 1964;4(3):155–232. https://doi.org/10.1016/S0033-7560(64)80069-7
  17. 17. Singh RK, Chaudhary BD. Biometrical methods in quantitative genetic analysis. New Delhi: Kalyani Publishers; 1985.
  18. 18. Wanga MA, Shimelis H, Mashilo J, Horn LN, Sarsu F. Responses of elite sorghum (Sorghum bicolor [L.] Moench) lines developed via gamma radiation for grain yield, component traits and drought tolerance. Reprod Breed. 2023;3(4):184–96. https://doi.org/10.1016/j.repbre.2023.10.005
  19. 19. Anshori MF, Purwoko BS, Carsono N, Dewi IS, Bahrun AH, Baharuddin AK, et al. Integration of gamma irradiation breeding from doubled haploid and systematic screening to develop adapted rice mutants under salinity stress. BMC Plant Biol. 2025;25(1):1571. https://doi.org/10.1186/s12870-025-07542-2
  20. 20. Joshi DC, Bhinda MS, Pal RS, Hasan N, Badigannavar AM, Hedau NK, et al. The comparative mutagenic effectiveness and efficiency of electron beam, gamma rays, ethyl methane sulphonate and sodium azide to induce novel genetic variation in grain amaranth (A. hypochondriacus L.). Heliyon. 2026;12(1):e44496. https://doi.org/10.1016/j.heliyon.2025.e44496
  21. 21. Saibari I, Barrijal S, Mouhib M, Belkadi N, Hamim A. Gamma irradiation-induced genetic variability and its effects on the phenotypic and agronomic traits of groundnut (Arachis hypogaea L.). Front Genet. 2023;14:1124632. https://doi.org/10.3389/fgene.2023.1124632
  22. 22. Patel D, Davda BK, Vadodariya H, Makwana D, Parmar M. Gamma rays induced mutations in sorghum: isolating desired genetic variations for enhanced crop development. Plant Arch. 2024;24(1). https://doi.org/10.51470/PLANTARCHIVES.2024.v24.no.1.196
  23. 23. Thange VB, Bagade AB, Deshmukh JD. Correlation and path coefficient analysis studies in mutant PVK 801 genotype of sorghum (Sorghum bicolor (L.) Moench). Int J Chem Stud. 2021;9(1):1696–8. https://doi.org/10.22271/chemi.2021.v9.i1x.11471
  24. 24. Adedugba AA, Adeyemo OA, Adetumbi AJ, Amusa OD, Ogunkanmi LA. Evaluation of genetic variability for major agro-morphological and stalk sugar traits in African sorghum genotypes. Heliyon. 2023;9(3):e14622. https://doi.org/10.1016/j.heliyon.2023.e14622
  25. 25. Somu G, Meena N, Badigannavar A. Exploring genetic variability for morphological and yield contributing traits in sorghum (Sorghum bicolor (L.) Moench) germplasm from Southern India. Genet Resour Crop Evol. 2025;72(5):5179–94. https://doi.org/10.1007/s10722-024-02251-5
  26. 26. Gebre W, Mekbib F, Tirfessa A, Bekele A. Genetic variability among lowland sorghum accessions collected from southern Ethiopia for grain quality traits. Heliyon. 2024;10(4):e25323. https://doi.org/10.1016/j.heliyon.2024.e25323
  27. 27. Duresso ME, Lule D, Tirfessa A, Gelmesa D, Tesso T, Menamo T, et al. Genetic diversity in Ethiopian sorghum germplasm for root system architecture and trait association. Rhizosphere. 2023;27:100759. https://doi.org/10.1016/j.rhisph.2023.100759
  28. 28. Nagaraja TE, Bhat S, Nandini C. Evaluation of genetic diversity in germplasm accessions of finger millet [Eleusine coracana (L.) Gaertn]. Mysore J Agric Sci. 2023;57(2):238–45.
  29. 29. Mba C, Afza R, Bado S, Jain SM. Induced mutagenesis in plants using physical and chemical agents. In: Davey MR, Anthony P, editors. Plant cell culture: essential methods. Chichester: Wiley-Blackwell; 2010. p. 111–30. https://doi.org/10.1002/9780470686522.ch7
  30. 30. Ahloowalia BS, Maluszynski M, Nichterlein K. Global impact of mutation-derived varieties. Euphytica. 2004;135(2):187–204. https://doi.org/10.1023/B:EUPH.0000014914.85465.4f
  31. 31. Oladosu Y, Rafii MY, Abdullah N, Hussin G, Ramli A, Rahim HA, et al. Principle and application of plant mutagenesis in crop improvement: a review. Biotechnol Biotechnol Equip. 2016;30(1):1–16. https://doi.org/10.1080/13102818.2015.1087333

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