Morphological and agronomical comparative study of genetic diversity of common winter wheat cultivars

Authors

  • Gergana Desheva Institute of Plant Genetic Resources “Konstantin Malkov”, Sadovo, Agricultural academy, Sofia, Bulgaria Author
  • Manol Deshev Institute of Plant Genetic Resources “Konstantin Malkov”, Sadovo, Agricultural academy, Sofia, Bulgaria Author

Keywords:

agronomical traits; heat map; morphological traits; PCA; wheat

Abstract

The aim of this study was to assess the genetic diversity among cultivars with different geographical origin in term of 7 morphological and 7 agronomical traits. Twenty five common winter wheat varieties were included in three growing season evaluation using randomized complete block designs with 3 replications on plots of 10 m2. The significant differences among evaluated varieties for plant shape, leaf-flag attitude, spike shape, spike attitude and spike awnedness were recorded as well as the high variation for the most of the agronomical studied traits were found. The first 5 principal components explained a very large proportion of the total variation (73.56%). Spike related characters such as spike length without awn (0.62), spikelets number per spike (0.89), grain number per spike (0.92) and grain weight per spike (0.83) strongly associated with PC1. The clustered heat map based on the Ward method and using the first fives PCs grouped the genotypes into five clusters. The clustering of the studied wheat genotypes was not related to their geographical origin but it referred to specific phenotypic characters. The results of the study will be useful for the breeding improvement programs of common winter wheat.

References

Adilova, S., Qulmamatova, D., Baboev, S., Bozorov, T., & Morgunov, A. (2020) Multivariate cluster and principle component analyses of selected yield traits in Uzbek bread wheat cultivars. American Journal of Plant Sciences, 11, 903-912. doi:10.4236/ajps.2020.116066.

Anonymous. (1984). The International comecon list of descriptors for the genus Triticum L. The N.I. Vavilov All-Union Institute of Plant Industry, Leningrad, USSR.

Degewione, A., & Alamerew, S. (2013). Genetic diversity in bread wheat (Triticum aestivum L.) genotypes. Pakistan Journal of Biological Sciences, 16: 1330-1335. doi:10.3923/pjbs.2013.1330.1335.

Devesh, P., Moitra, P. K., Shukla, R. S., & Pandey, S. (2019). Genetic diversity and principal component analyses for yield, yield components and quality traits of advanced lines of wheat. Journal of Pharmacognosy and Phytochemistry, 8(3): 4834-4839. https://www.phytojournal.com/archives/2019/vol8issue3/PartBT/8-3-640-286.pdf.

Habibpour, M., Ahmadizadeh, M., & Shahbazi, H. (2012). Assessment relationship between agro-morphological traits and grain yield in bread wheat genotypes under drought stress condition. African Journal of Biotechnology, 11(35), 8698-8704. doi: 10.5897/AJB11.3421.

Kandel, M., Bastola, A., Sapkota, P., Chaudhary, O., Dhakal, P., Chalise, P., & Shrestha, J. (2018). Analysis of genetic diversity among the different wheat (Triticum aestivum L.) genotypes. Türk Tarım ve Doğa Bilimleri Dergisi, 5(2), 180–185. doi:10.30910/turkjans.421363.

Lee, J. E., Recker, M., Bowers, A. J., & Yuan, M. (2016). Hierarchical cluster analysis heatmaps and pattern analysis: an approach for visualizing learning management system interaction data. Proceedings of the 9th International Conference on Educational Data Mining, 603-604.

Li, S. Q., Li, X. D., Wang, S. H., & Zhang, Z. L. (2010). Clustering and principal component analysis of introduced black pericarp rice germplasm based on agronomic traits. Southwest China Journal of Agricultural Sciences, 23, 11-15.

Mohammad, F., Ahmad, I., Khan, N. U., Maqbool, K., Naz, A., Shaheen, S., & Khalid, A. (2011). Comparative study of morphological traits in wheat and triticale. Pak. J. Bot., 43(1), 165-170.

Mohammadi, S. A., & Prasanna, B. M. (2003). Analysis of genetic diversity in crop plants—salient statistical tools and considerations. Crop Science, 43(4), 1235-1248. https://doi.org/10.2135/cropsci2003.1235.

Naushad, A., Hussain, I., Sardar, A., Naqib, U. K., & Ijaz, H. (2021). Multivariate analysis for various quantitative traits in wheat advanced lines. Saudi Journal of Biological Sciences, 28, 347–352. https://doi.org/10.1016/j.sjbs.2020.10.011.

Priya, B., Sunil, D., Subhra, M., & Srinivasarao, M. (2015). Genetic diversity based on cluster and principal component analysis in wheat and triticale genotypes. Research on Crops, 16(4), 712-718. doi:10.5958/2348-7542.2015.00100.X.

Priya, B., Das, B., Satyanarayana, N. H., Mukherjee, S., & Sarkar, K. K. (2014). Genetic diversity of wheat genotypes based on principal component analysis in Gangetic alluvial soil of West Bengal. Journal of Crop and Weed, 10(2), 104-107. https://www.cropandweed.com/archives/2014/vol10issue2/18.pdf

Roessner, U., Nahid, A., Hunter, A.m & Bellgard, M. (2011). Metabolomics – the combination of analytical chemistry, biology and informatics. In Moo-Young, M. (ed.) Comprehensive Biotechnology 2-nd ed., vol.1, pp. 447–459.

Shen, G., Girdthai, T., Liu, Z. Y., Fu, Y. H., Meng, Q. Y.m & Liu, F. Z. (2019). Principal component and morphological diversity analysis of Job’s-tears (Coix lacryma-jobi L.). Chilean journal of agricultural research, 79 (1), 131-143. http://dx.doi.org/10.4067/S0718-58392019000100131.

Wang, S., Zhang, S., He, J., Lu, G.m & Yang, Z. (2013). The principal component analysis and cluster analysis of Coix resource characteristics. Journal of Yunnan Agricultural University, 28, 157-162.

Zimisuhara, B., Valdiani, A., Shaharuddin, N. A., Qamaruzzaman, F.m & Maziah, M. (2015). Structure and principal components analyses reveal an intervarietal fusion in malaysian mistletoe fig (Ficus deltoidea Jack) populations. Int. J. Mol. Sci., 16, 14369-14394; doi: 10.3390/ijms160714369.

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Published

20.08.2021

How to Cite

Morphological and agronomical comparative study of genetic diversity of common winter wheat cultivars. (2021). Bulgarian Journal of Crop Science, 58(4), 11-20. https://agriacad.eu/ojs/index.php/bjcs/article/view/2106