African Journal of
Agricultural Research

  • Abbreviation: Afr. J. Agric. Res.
  • Language: English
  • ISSN: 1991-637X
  • DOI: 10.5897/AJAR
  • Start Year: 2006
  • Published Articles: 6544

Article in Press

Correlation and multivariate analyses to select drought tolerant bread wheat (Triticum aestivum L.) genotypes using drought indices.

Tamiru Olbana, Firew Mekbib, Wuletaw Tadesse

  •  Received: 15 March 2021
  •  Accepted: 31 May 2021
Drought is one of the most common abiotic stresses affecting the productivity of wheat in Ethiopia. In this study, a total of sixty-four elite spring bread wheat genotypes from the International Center of Agricultural Research for Dry Areas (ICARDA) were used to identify drought-tolerant bread wheat genotypes. The experiment was laid out in 8*8 simple lattice designs under normal and stressed conditions at Werer Agricultural Research Center. The water stress treatment was imposed by withholding three irrigations from 50% flowering up to physiological maturity. In the non-stressed water regime, plants were watered at every 10 days interval using the furrow irrigation method. Five agronomic traits along with different drought indices were evaluated. The ANOVA showed the tested genotypes showed highly significant (p?0.01) variation for traits considered under both conditions. The correlation analysis revealed mean productivity; geometric mean productivity, yield index, and stress tolerance index have a strong positive correlation with grain yield under both conditions. The first two principal components accounted 99.15%. The first PC alone explained 56.31% while, the second PC explained 42.84%. Cluster analysis grouped sixty-four bread wheat genotypes into four distinct clusters including 20, 19, 18, and 7 genotypes respectively. Generally, G28, G10, G24, G3, G48, G26, G1 and G14 are recommended for verification trial along with the standard and local checks for potential release at moisture stressed environments of the country.

Keywords: Bread wheat, cluster, drought tolerance, principal component analysis, yield