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Research Paper | August 1, 2017

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Multivariate analysis of genetic divergence in wheat (Triticuma estivum) using yield traits

Rehmat Kabir, Anisa Intikhab, Misbah Zahoor, Israr Ahmed, Bazeer Khan, Muhammad Zakriya, Mujeeb-ur-Rehman, Muhammad Atif Muneer, Muhammad Zeeshan Munir

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Int. J. Biosci.11(2), 43-48, August 2017

DOI: http://dx.doi.org/10.12692/ijb/11.2.43-48

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Abstract

The study was conducted to assess genetic divergence in wheat (Triticum aestivum L.) using yield traits. The experiment was planted at Mountain Agricultural Research Center, Juglot, Pakistan during 2014-15 following randomized complete block design with three replications. Plant material for the study comprised of 16 lines and four commercial cultivars of bread wheat. The data recorded were days to 50% heading, days to 50% maturity, plant height (cm), Number of grains spike-1, grain yield per plot, straw yield per plot, 1000 grain weight and yield per hectare. On the basis of multivariate analysis, genotypes 110, 119, 128, 143 and Pirsabak-2013 were showing maximum divergence from other genotypes. This study has shown the existence of considerable genetic variation among the genotypes considered with may help for further selection and breeding. Parents may be selected from clusters which had significant genetic distance for crossing in order to obtain genetic recombination and transgressive segregation in the subsequent generations. However further study across location and years needs to be done in order to corroborate the results obtained in the present investigation.

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Multivariate analysis of genetic divergence in wheat (Triticuma estivum) using yield traits

Anon. 2016. Pakistan Economic Survey 2015-16. Statistic division, Federal Bureau of Statistics. Govt. of Pakistan, Islamabad.28p.

Fu Y, Somers D.  2009. Genome-Wide Reduction of Genetic Diversity in Wheat Breeding Crop Sci 49,  161–168.

Jaynes DB, Kaspar TC, Colvin TS, James DE. 2003. Cluster analysis of spatiotemporal corn yield pattern in an Iowa field. Agron . J., 95, 574-586.

Van W, Hintum MV, Kik C, Treurenand VR, Visser B. 2010. Genetic diversity trends in twentieth century crop cultivars: a meta-analysis. Theor. Appl. Genet. 120, 1241–1252.

Eivazi AR, Naghavi MR, Hajheidari M, Pirseyedi SM, Ghaffari MR, Mohammadi SA, Majidi I, Salekdehand GH, Mardi M. 2007. Assessing wheat (Triticum aestivum L.) genetic diversity using quality traits, amplified fragment length polymorphisms, simple sequence repeats and proteome analysis. Ann. Appl. Biol. 15, 81-91.

Islam MR. 2004.Genetic diversity in irrigated rice. Pak. J. Biol. Sci., 2, 226-229.

Mohammadi SA, Prasanna BM. 2003. Analysis of genetic diversity in crop plants- Salient statistical tools and considerations. Crop Sci., 43, 1234-1248.

Zubair M, Ajmal SU, Anwar M, Haqqani M. 2007. Multivariate analysis for quantitative traits in mungbean [Vigna radiate (L.) Wilczek]. Pak. J. Bot., 39, 103-113.

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