Correlation and path coefficient analyses of yield and yield components in drought-tolerant bread wheat populations
Correlation and path coefficient analyses of economic traits is important in identifying traits that can be used to simplify selection of complex traits such as grain yield. The aim of this study was to determine the degree of association between yield and yield components of drought-tolerant wheat...
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Published in | South African journal of plant and soil Vol. 36; no. 5; pp. 367 - 374 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
Taylor & Francis
20.10.2019
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Subjects | |
Online Access | Get full text |
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Summary: | Correlation and path coefficient analyses of economic traits is important in identifying traits that can be used to simplify selection of complex traits such as grain yield. The aim of this study was to determine the degree of association between yield and yield components of drought-tolerant wheat populations using correlation and path analyses. Twelve selected parents and 66 of their F
3
families were evaluated under drought-stressed and non-stressed conditions in two sites using a 6 × 13 alpha-lattice design with two replications. Partitioning of correlation coefficients into direct and indirect effects revealed strong positive direct effects of kernels per spike and fresh biomass on grain yield under the drought-stressed condition. Among the assessed traits, fresh biomass had high significant simple correlation coefficients of 0.75 and 0.90, and strong direct effects of 0.76 and 0.98 with grain yield under drought-stressed and non-stressed conditions, respectively. The high-yielding genotypes, LM02 × LM05, LM02 × LM23 and LM13 × LM45, showed high mean values for kernels per spike, thousand-kernel weight and fresh biomass. The overall association analyses indicated that the latter three traits had significant influence on grain yield performance and are useful for selection of drought-tolerant breeding populations of wheat. |
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ISSN: | 0257-1862 2167-034X |
DOI: | 10.1080/02571862.2019.1626500 |