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Plant Science Today (PST)

Research Articles

Vol. 13 No. sp9 (2026): Recent Advances in Agriculture

Identification of potential maize inbred lines through morphological and molecular heterotic grouping

DOI
https://doi.org/10.14719/pst.14493
Submitted
10 March 2026
Published
27-10-2026

Abstract

This study was conducted to identify potential maize inbred lines for hybrid development through morphological and molecular heterotic grouping. A total of 120 test crosses developed using 60 inbred lines and two heterotic testers (LM-13 and LM-14) in a line × tester mating design (rabi, 2019–20) were evaluated for grain yield along with parental lines across 3 locations (Maize Research Center (MRC), Rajendranagar and Agricultural Research Station (ARS) at Karimnagar and Madhira, Telangana, India) during rabi, 2020–21. Molecular diversity among 62 parental lines was assessed using 30 simple sequence repeat (SSR) markers at the Institute of Biotechnology, Rajendranagar, Hyderabad, Telangana, India. Pooled analysis of variance revealed significant differences among genotypes across locations, indicating the presence of ample genetic variability for grain yield. Based on the heterotic group specific and general combining ability (HSGCA) method, the inbred lines were classified into two distinct heterotic groups, while molecular diversity analysis grouped them into 4 clusters, revealing substantial genetic divergence. The integration of both morphological and molecular analyses enabled the identification of 12 promising inbred lines common to both approaches; six lines (MGC-90, PFSR-51, GP-35, GP-111, BML-11 and BML-20) associated with tester LM-13 and six lines (PFSR-151, PFSR-46, MGC-15, MGC-137, PFSR-129 and PFSR-95) associated with tester LM-14. These diverse inbred lines hold potential for generating superior segregants in hybridisation and advancing precision breeding programmes in maize.

References

  1. 1. India Ministry of Agriculture & Farmers Welfare. Agricultural statistics at a glance 2021. New Delhi: Directorate of Economics and Statistics, Department of Agriculture and Farmers Welfare; 2022. p. 63–5. https://desagri.gov.in
  2. 2. Melchinger AE. Genetic diversity and heterosis. In: Coors JG, Pandey S, editors. The genetics and exploitation of heterosis in crops. Madison (WI): American Society of Agronomy; Crop Science Society of America; 1999. p. 99–118. https://doi.org/10.3389/fhort.2023.1250875
  3. 3. Agbaje SA, Badu-Apraku B, Fakorede MAB. Heterotic patterns of early maturing maize inbred lines in Striga-free and Striga-infested environments. Maydica. 2008;53:87–96.
  4. 4. Librando RP, Magulama EE. Classifying white inbred lines into heterotic groups using yield combining ability effects. J Agric Res Dev Ext Technol. 2008;16(1):99–103.
  5. 5. Hosana GC, Alamerew S, Tadesse B, Menamo T. Test cross performance and combining ability of maize (Zea mays L.) inbred lines at Bako, Western Ethiopia. Glob J Sci Front Res D Agric Vet. 2015;15(4):1–24.
  6. 6. Ejigu YG, Tongoona PB, Ifie BE. Classification of selected white tropical maize inbred lines into heterotic groups using yield combining ability effects. Afr J Agric Res. 2017;12(19):1674–7. https://doi.org/10.5897/AJAR2016.11872
  7. 7. Singh SB, Kumar P, Kasana RK, Choudhary M, Kumar S, Kumar R, et al. Unveiling combining ability and heterotic grouping of newly developed winter maize (Zea mays L.) inbreds. Indian J Agric Sci. 2021;91(11):1586–91. https://doi.org/10.56093/ijas.v91i11.118535
  8. 8. Fan XM, Zhang YM, Yao WH, Chen HM, Tan J, Xu CX, et al. Classifying maize inbred lines into heterotic groups using a factorial mating design. Agron J. 2009;101(1):106–12. https://doi.org/10.2134/agronj2008.0133
  9. 9. Konate L, Badu-Apraku B, Traore D. Combining ability and heterotic grouping of early maturing provitamin A maize inbreds across Striga-infested and optimal growing environments. J Agric Environ Int Dev. 2017;111(1):141–57. https://doi.org/10.12895/jaeid.20171.572
  10. 10. Annor B, Badu-Apraku B, Nyadanu D, Akromah R, Fakorede MAB. Identifying heterotic groups and testers for hybrid development in early maturing yellow maize (Zea mays). Plant Breed. 2020;139:708-16. https://doi.org/10.1111/pbr.12822
  11. 11. Mekasha GM, Chere AT, Ali HM, Seyoum SA. Classifying highland quality protein maize inbred lines into heterotic groups. Afr J Plant Sci. 2021;15(8):225–36. https://doi.org/10.5897/AJPS2021.2160
  12. 12. Maazou ARS, Gedil M, Adetimirin VO, Unachukwu N, Mengesha W, Meseka S, et al. Heterotic grouping of provitamin A-enriched maize inbred lines for increased provitamin A content in hybrids. BMC Genomic Data. 2023;24:1–8.
  13. https://doi.org/10.1186/s12863-023-01156-z
  14. 13. Punya, Sharma VK, Kumar P. Microsatellite marker dependent genetic divergence assessment within and among heterotic groups of tropical maize inbred lines. Maydica. 2018;63(23):1–13.
  15. 14. Jambhale VM, Pawar SV, Raut VK, Vidyapeeth MP, K, Rahuri. Assessment of molecular diversity in maize genotypes (Zea mays L.) through SSR markers. Int Res J Eng Technol. 2020;7(1):800–6.
  16. 15. Joshi BK, Rawat J, Adhikari B, Pokhrel R. SSR markers based genetic diversity in Nepalese maize landraces. SAARC J Agric. 2020;18(1):23–37. https://doi.org/10.3329/sja.v18i1.48379
  17. 16. Kamara MM, Ghazy NA, Mansour E, Elsharkawy MM, Kheir AM, Ibrahim KM. Molecular genetic diversity and line × tester analysis for resistance to late wilt disease and grain yield in maize. Agronomy. 2021;11:898. https://doi.org/10.3390/agronomy11050898
  18. 17. Menkir A, Berhan M, Ingelbrecht I, Adepoju A. Grouping of tropical mid-altitude maize inbred lines on the basis of yield data and molecular analysis. Theor Appl Genet. 2004;108:1582–90. https://doi.org/10.1007/s00122-004-1585-0
  19. 18. Murray MG, Thompson WF. Rapid isolation of high molecular weight plant DNA. Nucleic Acids Res. 1980;8(19):4321–6. https://doi.org/10.1093/nar/8.19.4321
  20. 19. Ribaut JM, Hoisington D. Marker-assisted selection: New tools and strategies. Trends Plant Sci. 1998;3:236–9. https://doi.org/10.1016/S1360-1385(98)01280-6
  21. 20. Botstein D, White RL, Skolnick M, Davis RW. Construction of a genetic linkage map in man using restriction fragment length polymorphisms. Am J Hum Genet. 1980;32:314–31.
  22. 21. Perrier X, Jacquemoud-Collet JP. DARwin: Dissimilarity Analysis and Representation for Windows [software]. Version 6.0. Montpellier: CIRAD; 2006. http://darwin.cirad.fr/darwin
  23. 22. Liu K, Muse SV. PowerMarker: An integrated analysis environment for genetic marker analysis. Bioinformatics. 2005;21:2128–9. https://doi.org/10.1093/bioinformatics/bti282
  24. 23. Maniruzzaman, Azam MG, Islam S, Hossain MG, Rohman MM. Molecular assessment of maize inbred lines (Zea mays L.) using microsatellite markers. Bangladesh J Agric Res. 2018;43(4):533–42. https://doi.org/10.3329/bjar.v43i4.39151
  25. 24. Amegbor IK, Badu-Apraku B, Annor B. Combining ability and heterotic patterns of extra-early maturing white maize inbreds with genes from Zea diploperennis under multiple environments. Euphytica. 2017;213:24. https://doi.org/10.1007/s10681-016-1823-y
  26. 25. Kumar A, Akilan M, Nirmala Ruban R. Morphological characterization and genetic diversity analyses of yield and yield attributing traits in sweet corn (Zea mays var. saccharata). J Sci Res Rep. 2024;30:635–46. https://doi.org/10.9734/jsrr/2024/v30i72177
  27. 26. Gichuru L, Derera J, Tongoona P, Murenga M. Combining ability and molecular genetic distances in tropical maize lines for grain yield and agronomic traits. S Afr J Plant Soil. 2017;34(3):175–83. https://doi.org/10.1080/02571862.2016.1213323
  28. 27. Synrem GJ, Marker S, Ramteke PW, Charan AA. Simple sequence repeat (SSR) markers for molecular diversity and heterozygosity analysis in maize (Zea mays L.) inbred lines. J Pharmacogn Phytochem. 2017;6(6):732–7.
  29. 28. Kumari A, Sinha S, Rashmi K, Mandal SS, Sahay S. Genetic diversity analysis in maize (Zea mays L.) using SSR markers. J Pharmacogn Phytochem. 2018:1116–20.

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