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Research Articles

Early Access

Genetic studies on Quality Protein Maize (QPM) for variability and diversity analysis under temperate conditions (Zea mays L.)

DOI
https://doi.org/10.14719/pst.11688
Submitted
8 September 2025
Published
23-01-2026

Abstract

Despite significant progress in maize improvement, information on the extent of genetic variability and trait relationships in Quality Protein Maize (QPM) germplasm under temperate conditions remains limited, constraining effective selection for yield and nutritional quality. The present investigation was conducted to assess genetic variability, heritability, character associations and genetic divergence among 50 QPM genotypes, including five checks. The experiment was laid out in an augmented block design (ABD) without replications at the Dryland Agriculture Research Station (DARS), Budgam and observations were recorded on 13 morphological and quality traits. A wide range of variability was observed for all traits. The phenotypic coefficient of variation (PCV) and genotypic coefficient of variation (GCV) were in a moderate range for most of the characters except for the number of days to maturity, shelling percentage and protein content. High heritability of characters like grain yield, kernels cob-1, number of cobs plant-1 and 100-seed weight, along with extensive genetic advance, suggests that additive gene effects are playing a predominant role and direct selection will be effective for improvement of these traits. After correlation analysis, it was observed that grain yield was robustly and positively allied with plant height, ear height, number of cobs plant-1, cob length, kernel rows cob-1, kernels cob-1 and 100-seed weight, whereas protein content showed negative association with yield. Genetic divergence assessed through Mahalanobis D² statistics classified the genotypes into eight clusters, with the highest inter-cluster distance observed between cluster IV and cluster VIII with 341.59, indicating scope for heterotic hybrid development. The mean grain yield was highest in cluster II, while superior protein content was observed in clusters III and cluster VIII. The current findings identified ten early-maturing genotypes with commendable yield and protein content, which can be effectively used in QPM breeding programs aimed at improving productivity and nutritional quality.

References

  1. 1. Amanjyoti, Singh J, Sowdhanya D, Rasane P, Singh J, Ercisli S, et al. Maize. In: Singh J, Kaur S, Rasane P, Singh J, editors. Cereals and nutraceuticals. Singapore: Springer Nature Singapore; 2024. p. 47–80. https://doi.org/10.1007/978-981-97-2542-7_3
  2. 2. Sleper AD, Poehlman JM. Breeding field crops. 5th ed. Ames (IA): Blackwell Publishing; 2006. p. 277–96.
  3. 3. M’mboyi F, Mugo S, Mwimali M, Ambani L. Maize production and improvement in Sub-Saharan Africa. Nairobi: African Biotechnology Stakeholders Forum; 2010. p. 34–45.
  4. 4. Flint-Garcia SA, Buckler ES, Tiffin P, Ersoz E, Springer NM. Heterosis is prevalent for multiple traits in diverse maize germplasm. PloS One. 2009;4(10):e7433. https://doi.org/10.1371/journal.pone.0007433
  5. 5. Anonymous. World corn production; 2017. Available from: http://www.worldcornproduction.com
  6. 6. Anonymous. Jammu and Kashmir Department of Ecology, Environment and Remote Sensing; 2016.
  7. 7. Anonymous. United States Department of Agriculture. 2016.
  8. 8. Prasanna BM, Vasal SK, Kassahun B, Singh NN. Quality protein maize. Curr Sci. 2001;81:1308–19.
  9. 9. Zhang W, Sangtong V, Peterson J, Scott MP, Messing J. Divergent properties of prolamins in wheat and maize. Planta. 2013;237(6):1465-73. https://doi.org/10.1007/s00425-013-1857-5
  10. 10. Vietmeyer ND. A drama in three long acts: the story behind the story of the development of quality-protein maize. Cereal Foods World. 2000;16:29–32.
  11. 11. Zhang S, Zhan J, Yadegari R. Maize opaque mutants are no longer so opaque. Plant Reprod. 2018;31(3):319-26. https://doi.org/10.1007/s00497-018-0344-3
  12. 12. Nedi G, Alamerew S, Tulu L. Review on quality protein maize breeding for Ethiopia. J Biol Agric Health. 2016;6:84-96.
  13. 13. Chand G, Muthusamy V, Zunjare RU, Mishra SJ, Sharma G, Mehta BK, et al. Molecular analysis of opaque2 gene governing accumulation of lysine and tryptophan in maize endosperm. Euphytica. 2024;220(10):155. https://doi.org/10.1007/s10681-024-03414-2
  14. 14. Kaur R, Kaur G, Vikal Y, Gill GK, Sharma S, Singh J, et al. Genetic enhancement of essential amino acids for nutritional enrichment of maize protein quality through marker assisted selection. Physiol Mol Biol Plants. 2020;26(11):2243-54. https://doi.org/10.1007/s12298-020-00897-w
  15. 15. Hossain F, Sarika K, Muthusamy V, Zunjare RU, Gupta HS. Quality protein maize for nutritional security. In: Reddy MS, Yadav RC, Mishra JS, editors. Quality breeding in field crops. Cham: Springer International Publishing; 2019. p. 217–37. https://doi.org/10.1007/978-3-030-04609-5_11
  16. 16. Kumar R, Singh V, Das AK, Chaudhary DP, Chikkappa GK, Singh A, et al. Genetic variation for methionine, tryptophan and lysine in maize (Zea mays L.) inbred lines. Indian J Genet Plant Breed. 2025;85(1):87-94.
  17. 17. Vivek BS, Krivanek AF, Rojas NP, Afriyie ST, Diallo AO. Breeding quality protein maize (QPM): protocols for developing QPM cultivars. Mexico: CIMMYT; 2008.
  18. 18. Zhang S, Zhan J, Yadegari R. Maize opaque mutants are no longer so opaque. Plant Reprod. 2018;31(3):319–26. https://doi.org/10.1007/s00497-018-0344-3
  19. 19. Al-Jibouri H, Miller PA, Robinson HF. Genotypic and environmental variances and covariances in an upland cotton cross of interspecific origin. Agron J. 1958;50(10):633–6. https://doi.org/10.2134/agronj1958.00021962005000100020x
  20. 20. Warner JN. A method for estimating heritability. Agron J. 1952;44:427–30.
  21. 21. Burton GW. Quantitative inheritance in grasses. In: Proceedings of the VI International Grassland Congress; 1952. p. 277–83.
  22. 22. Sivasubramaniam S, Madhava Menon P. Heterosis and inbreeding depression in rice. Madras Agric J. 1973;60:1339.
  23. 23. Allard RW. Principles of plant breeding. New York: John Wiley & Sons; 1999. p. 485.
  24. 24. Johnson HW, Robinson HF, Comstock RE. Estimates of genetic and environmental variability in soybeans. Agron J. 1955;47(7):314–8. https://doi.org/10.2134/agronj1955.00021962004700070009x
  25. 25. Rao CR. Advanced statistical methods in biometric research. New York: John Wiley & Sons; 1952. p. 357–63.
  26. 26. Singh RK, Chaudhary BD. Biometrical methods in quantitative genetic analysis. 2nd ed. New Delhi: Kalyani Publishers; 1981. p. 304. https://www.cabidigitallibrary.org/doi/full/10.5555/19801689021
  27. 27. Suresh Handi SH, Sasidharan N, Chakraborty S, Patel JN, Trivedi R, Panwar BS, et al. Genetic analysis and character association studies for yield and phenotypic characters in maize (Zea mays L.). Int J Plant Sci. 2012;7:341–50.
  28. 28. Nayak VH, Singh R, Potla KR. Genetic variability analysis of yield and yield-related traits in inbred lines of maize (Zea mays L.). Environ Ecol. 2013;31:1669–71.
  29. 29. Gupta SP, Salgotra RK. Variability and correlation studies in Zea mays under intermediate zone of Jammu. Environ Ecol. 2004;22:554–57.
  30. 30. Sofi PA, Rather AG. Studies on genetic variability, correlation and path analysis in maize (Zea mays L.). Int J Agric Sci. 2007;3:290–3.
  31. 31. Bartaula S, Panthi U, Timilsena K, Acharya SS, Shrestha J. Variability, heritability and genetic advance of maize (Zea mays L.) genotypes. Res Agric Livest Fish. 2019;6(2):163-69.
  32. 32. Ababulgu D, Shimelis H, Laing M, Amelework B. Phenotypic characterization of elite quality protein maize (QPM) inbred lines adapted to tropical highlands and the association studies using SSR markers. Aust J Crop Sci. 2018;12(1):22-31.
  33. 33. Rafique M, Hussain A, Mahmood T, Alvi AW, Alvi MB. Heritability and interrelationships among grain yield and yield components in maize (Zea mays L.). Int J Agric Biol. 2004;6(6):1113-14. https://www.cabidigitallibrary.org/doi/full/10.5555/20053026671
  34. 34. Umakanth AV, Satyanarayana E, Nagesh Kumar MV. Correlation and heritability studies in Ashwini maize composite. Annu Agric Res. 2000;21:328–30.
  35. 35. Sadek SE, Ahmed MA, Abd El-Ghaney HM. Correlation and path coefficient analysis in white maize (Zea mays L.) single crosses developed in Egypt. J Appl Sci Res. 2006;2(3):159–67.
  36. 36. Singh D, Kumar A, Kumar R, Kushwaha N, Mohanty TA, Kumari P. Genetic variability analysis of QPM (Zea mays L.) inbreds using morphological characters. Int J Curr Microbiol Appl Sci. 2020;9(2):328-38. https://doi.org/10.20546/ijcmas.2020.902.042
  37. 37. Tulu BN. Correlation and path coefficients analysis studies among yield and yield related traits of quality protein maize (QPM) inbred lines. Int J Plant Breed Crop Sci. 2014;1(2):6-17.
  38. 38. Reddy YR, Ravi D, Reddy CR, Prasad KV, Zaidi PH, Vinayan MT, Blümmel M. A note on the correlations between maize grain and maize stover quantitative and qualitative traits and the implications for whole maize plant optimization. Field Crops Res. 2013;153:63-69. https://doi.org/10.1016/j.fcr.2013.06.013
  39. 39. Begna T, Begna T. Role and economic importance of crop genetic diversity in food security. Int J Agric Sci Food Technol. 2021;7(1):164-69. https://dx.doi.org/10.17352/2455-815X.000104
  40. 40. Miranda GV, Coimbra RR, Godoy CL, Souza LV, Guimarães LJ, Melo AV. Potential for breeding and genetic divergence in popcorn cultivars. Pesqui Agropecu Bras. 2003;38:681–88. https://doi.org/10.1590/S0100-204X2003000600003
  41. 41. Khumkar MS, Singh RD. Divergence analysis of elite inbred lines of maize (Zea mays L.). Ann Agric Res. 2002;23(4):595–601.
  42. 42. Beyene Y, Botha AM, Myburg AA. A comparative study of molecular and morphological methods of describing genetic relationships in traditional Ethiopian highland maize. Afr J Biotechnol. 2005;4(7):586–95. https://doi.org/10.5897/AJB2005.000-3107

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