Document Type : Original Article

Author

Department of Biology, College of Education-Shaqlawa, Salahaddin University, Erbil, Kurdistan Region, Iraq.

Abstract

Cluster analysis and principal component analysis are multivariate analyses used widely to assess genetic diversity. The present study was conducted in the Autumn of 2024 at the Grdarasha experimental station, College of Agriculture Engineering Sciences, Salahaddin University, Erbil, Iraq, to assess the phenotypic genetic diversity among 20 sweet and forage corn single-cross hybrids using cluster and principal component analysis. Results demonstrated that the 20 single-cross hybrids were significantly different from each other. Moreover, almost all of the traits studied showed high broad-sense heritability, which is important for selecting corn single-cross hybrids. Cluster analysis and principal component analysis revealed a high level of genetic diversity, which has implications for characterizing, conserving, and breeding sweet and forage corn single-cross hybrids, as well as for categorizing them. The hybrids under study were divided into six different groups based on the performance of phenotypic traits, indicating that the hybrids have a varied genetic background. The cluster analysis and principal component analysis were also able to separate sweet corn well from the forage corn. This indicated the differentiation of the genetic makeup of sweet corn from forage corn. Biplot analysis showed positive correlations among ear yield and several traits such as ear weight, ear length, number of kernel rows per ear, number of leaves per plant, ear height, plant height, number of leaves per ear, leaf area, stem diameter, and number of ears per plant. A correlation of the first three principal component analyses accounted for 76.26% of the variation, indicating a significant variation among the hybrids studied .
 
 

Highlights

 

 
 

Keywords

Abu Sin, M. B. (2019). Genetics and combining ability of corn (Zea mays L.) genotypes for forage utilization (Ph.D. thesis). Department of Crop Science, Faculty of Agriculture, Universiti Putra Malaysia. http://psasir.upm.edu.my/id/eprint/84425/
Bhardwaj, A., Sharma, A., & Lata, H. (2020). Genetic variability for pod yield and related traits in garden pea (Pisum sativum L.). Electronic Journal of Plant Breeding, 11(4), 1233–1238. https://doi.org/10.37992/2020.1104.199
Brewbaker, J. L. (2003). Corn production in the tropics: The Hawaii experience. University of Hawaii at Manoa, College of Tropical Agriculture and Human Resources.
Bruford, M. W., Davies, N., Dulloo, M. E., Faith, D. P., & Walters, M. (2017). Monitoring changes in genetic diversity. In The GEO handbook on biodiversity observation networks (pp. 107–128). Springer International Publishing. https://doi.org/10.1007/978-3-319-27288-7_5
Chavan, S., Bhadru, D., Swarnalatha, V., & Mallaiah, B. (2023). Evaluation of variations for phenotypic traits by multivariate techniques in sweet corn (Zea mays L. saccharata). Journal of Crop and Weed, 19(1), 164–172. https://doi.org/10.22271/09746315.2023.v19.i1.1675
Fotokian, M., Shahnejat Bushehri, A., & Taleie, A. (2002). Cluster analysis based on PCA in rice genotypes. Paper presented at the 6th International Conference of Statistics, University of Tarbiat Modares, Iran, 26–28.
Gopinath, P. P., Parsad, R., Joseph, B., & Adarsh, V. S. (2020). GRAPES: General Rshiny Based Analysis Platform Empowered by Statistics (Version 1.0.0) [Software]. https://www.kaugrapes.com/home
Heryanto, F. S. S., Wirnas, D., & Ritonga, A. W. (2022). Diversity of twenty-three sweet corn (Zea mays L. saccharata) varieties in Indonesia. Biodiversitas, 23(11), 6075–6081. https://doi.org/10.13057/biodiv/d231164
Ismael, N. B. (2023). Characterization and grouping of imported single cross Zea mays L. hybrids based on morphological variations. Journal of Medicinal and Industrial Plants, 1(1), 41–51.
Ivandro Bertan, de Carvalho, F. I. F., & de Oliveira, A. C. (2007). Parental selection strategies in plant breeding programs. Journal of Crop Science and Biotechnology, 10(4), 211–222.
Johnson, H. W., Robinson, H. F., & Comstock, R. E. (1955). Estimates of genetic and environmental variability in soybean. Agronomy Journal, 47(7), 314–318. https://doi.org/10.2134/agronj1955.00021962004700070009x
Jolliffe, I. T. (1986). Principal component analysis. Springer-Verlag.
Jolliffe, I. T., & Cadima, J. (2016). Principal component analysis: A review and recent developments. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 374, 20150202. https://doi.org/10.1098/rsta.2015.0202
Khodadadi, M., Fotokian, M. H., & Miransari, M. (2011). Genetic diversity of wheat (Triticum aestivum L.) genotypes based on cluster and principal component analyses for breeding strategies. Australian Journal of Crop Science, 5(1), 17–24.
Latif, A., Bilal, M., Hussain, S. B., & Ahmad, F. (2015). Estimation of genetic divergence, association, direct and indirect effects of yield with other attributes in cotton (Gossypium hirsutum L.) using biplot correlation and path coefficient analysis. Tropical Plant Research, 2(2), 120–126.
McWhirter, K. S. (1979). Breeding of cross-pollinated crops. In Plant breeding (pp. 79–121). Australian Vice-Chancellors’ Committee.
Melchinger, A. E., & Gumber, R. K. (1998). Overview of heterosis and heterotic groups in agronomic crops. In Concepts and breeding of heterosis in crop plants (Vol. 25, pp. 29–44). Crop Science Society of America. https://doi.org/10.2135/cssaspecpub25.c3
Milligan, G. W., & Cooper, M. C. (1988). A study of standardization of variables in cluster analysis. Journal of Classification, 5, 181–204. https://doi.org/10.1007/BF01897163
Mohammadi, S. A., & Prasanna, B. M. (2003). Analysis of genetic diversity in crop plants—Salient statistical tools. Crop Science, 43(4), 1235–1248. https://doi.org/10.2135/cropsci2003.1235
Mustafa, B. S., Ismael, N. B., Mustafa, N. R., Kakarash, S. A., & Abdulazeez, S. D. (2024). Chlorophyll content and leaf area correlated with corn (Zea mays L.) yield components in F1 hybrids. The Indian Journal of Agricultural Sciences, 94(4), 352–357. https://doi.org/10.56093/ijas.v94i4.140666
Mustafa, N. R. (2021). Diversity, performance, and selection of tropical sweet corn inbred lines, and their combining abilities in hybrid combinations (Ph.D. thesis). Universiti Putra Malaysia. https://core.ac.uk/download/529928169.pdf
Mustafa, N. R., Kakarash, S. A., Ismael, N. B., & Abdulazeez, S. D. (2025). Formation of potential heterotic groups of maize inbred lines using variation at simple sequence repeat loci. Iraqi Journal of Agricultural Sciences, 56(2), 657–667. https://doi.org/10.36103/tnhhjw11
Mustafa, N. R., Saleh, G. B., & Kashiani, P. (2021). Genetic potential of tropical sweet corn hybrids and combining ability among parental inbred lines. Australian Journal of Crop Science, 15(10), 1279–1288. https://doi.org/10.21475/ajcs.21.15.10.p3189
Obeng-Antwi, K., Craufurd, P. Q., Menkir, A., Ellis, R. H., & Sallah, P. Y. K. (2011). Intra-landrace variability of two landraces in Ghana. International Journal of Science and Advanced Technology, 1(9), 23–40.
Peeters, J. P., & Martinelli, J. A. (1989). Hierarchical cluster analysis as a tool to manage variation in germplasm collections. Theoretical and Applied Genetics, 78, 42–48. https://doi.org/10.1007/BF00299751
Rahman, S., Mia, M. M., Quddus, T., Hassan, L., & Haque, M. A. (2015). Assessing genetic diversity of maize (Zea mays L.) genotypes for agronomic traits. Research in Agriculture, Livestock and Fisheries, 2(1), 53–61. https://doi.org/10.3329/ralf.v2i1.23029
Ranjitha, M. C., Vaddoria, M. A., & Jethava, A. S. (2018). Genetic variability, heritability and genetic advance in garlic (Allium sativum L.) germplasm. International Journal of Pure and Applied Bioscience, 6(4), 401–407. http://dx.doi.org/10.18782/2320-7051.6784
Rohlf, F. (2002). NTSYS-pc: Numerical taxonomy system (Version 2.1). Exeter Publishing Ltd.
SAS Institute Inc. (2014). SAS/STAT® user’s guide (Version 9.4). SAS Institute Inc.
Sokal, R. R., & Michener, C. D. (1958). A statistical method for evaluating systematic relationships. The University of Kansas Science Bulletin, 38, 1409–1438.
Stephen, A., Antonia, Y. T., Patrick, T., Kingsley, B. A., & Richard, A. A. (2016). Genetic diversity in lowland, midaltitude and highland African maize landraces by morphological trait evaluation. African Journal of Plant Science, 10(11), 246–257. https://doi.org/10.5897/AJPS2016.1448
Šućur, R., Mladenov, V., Banjac, B., Trkulja, D., Mikić, S., Šumaruna, M., & Börner, A. (2023). Phenotypic marker study of worldwide wheat germplasm. Italian Journal of Agronomy, 19(1), 1–7. https://doi.org/10.4081/ija.2023.2194
Szymanek, M., Dobrzański Jr., B., Niedzióka, I., & Rybczyński, R. (2006). Sweet corn harvest and technology: Physical properties and quality. Bohdan Dobrzański Institute of Agrophysics, Polish Academy of Sciences.
Trio, R., Geetaben, & Bhumikaben. (2023). Agri Analyze [Website]. https://www.agrianalyze.com
Ward, J. H. (1963). Hierarchical grouping to optimize an objective function. Journal of the American Statistical Association, 58(301), 236–244. https://doi.org/10.1080/01621459.1963.10500845
Weising, K., Nybom, H., Pfenninger, M., Wolff, K., & Kahl, G. (2005). DNA fingerprinting in plants: Principles, methods, and applications. CRC Press.
Woldemariam, M. N. (2004). Genetic studies and selection for ear length of sweet corn (Zea mays L.) (Ph.D. thesis). Universiti Putra Malaysia. http://psasir.upm.edu.my/id/eprint/339/
Zafar, M. M., Zhang, Y., Farooq, M. A., Ali, A., Firdous, H., Haseeb, M., Fiaz, S., Shakeel, A., Razzaq, A., & Ren, M. (2022). Biochemical and associated agronomic traits in Gossypium hirsutum L. under high temperature stress. Agronomy, 12(6), 1–19. https://doi.org/10.3390/agronomy12061310