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BASIC RESEARCH JOURNALS OF AGRICULTURAL SCIENCE AND REVIEW ISSN 2315-6880
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Basic Research Journal of Agricultural Science and Review ISSN 2315-6880 Vol. 4(4), pp. 127-134 April 2015 Copyright© 2015 Basic Research Journals

International Scientific Indexing (Impact Factor (0.401))

 

 

Full Length Research Paper
 

Genotype by trait analysis and estimates of heritability of wheat (Triticum aestivum L.) under drought and control conditions

 

Shoaib Ur Rehman1,2, Muhammad Ali Abid1,3*, Muhammad Bilal2, Javaria Ashraf3, Shoaib Liaqat4, Rana Imtiaz Ahmed4 and Ghulam Qanmber3

 

1Four Brothers Group, Pakistan

2Department of Plant Breeding and Genetics, PMAS Arid Agricultural University,

3Department of Plant Breeding and Genetics, Bahauddin Zakariya University, Multan,

4Cotton Research Station, Multan,

 

*Corresponding author e-mail: ali_abid0344@hotmail.com

 

Received 6 March, 2015; Accepted 19 March, 2015

 

Abstract

 

In order to observe the behaviour of 100 wheat genotypes under drought stress, an experiment was conducted following randomized complete block design (RCBD) with three replications. The outcomes of analysis of variance (ANOVA) depicted highly significant variation among wheat genotypes for all studied attributes in both control and drought stress conditions. Heritability assessed the relative significance of gene action in genetic variation and plays vital role in selection process for yield improvement in collaboration with genetic advance. Principle component analysis (PCA) was also performed to explore the divergent genotypes in wheat germplasm. Positive and significant correlation observed between peduncle length, spike length, spikelet per spike and grain yield under both control and drought stress conditions. PCA and heritability along with genetic advance suggested that these traits and diverse genotype should be given importance in selection programs to get better grain yield in wheat under rainfed conditions.

 

Keywords: Broad sense heritability; Drought; Genetic advance; Principle component analysis (PCA).

 

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