Low nitrogen narrows down phenotypic diversity in durum wheat
Breeding for nitrogen use efficiency has become the major global concern and priority to improve agricultural sustainability. In an attempt to quantify genetic variation and identify traits for optimum and low N environments, 200 durum wheat genotypes were evaluated at three locations in the central highlands of Ethiopia during the 2020 growing season. The experiments were arranged in alpha lattice design with two replications. The results revealed significant differences among genotypes for all studied traits under both N conditions, indicating ample opportunities for genetic improvement. All traits except days to heading and maturity, grain filling period and grain protein content were higher under optimum than under low N. High values of genotypic and phenotypic coefficients of variations, broad sense heritability and genetic advance as percent of the mean were observed for number of fertile tillers and number of seed per spike (NSPS) under optimum, and spike length and NSPS under low N conditions. Cluster analysis classified the durum wheat genotypes into thirteen and eight clusters under optimum and low N, respectively. Principal component analysis detected five and four components which explained 81.29% and 73.63% of the total variations under optimum and N stress conditions, respectively. The present study confirmed the existence of wide genetic variability among the durum wheat genotypes under optimum and low N conditions; and low N lowers the level of diversity. Thus, our study paves the possibility for improvement of durum wheat genotypes through selection and hybridization for increased grain yield and adaptation to N stressed conditions.
| Main Authors: | , , , , , |
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| Format: | Article biblioteca |
| Language: | English |
| Published: |
Taylor and Francis
2023
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| Subjects: | AGRICULTURAL SCIENCES AND BIOTECHNOLOGY, Clusters, Durum Wheat, Nitrogen Efficiency, HARD WHEAT, GENETIC DIVERGENCE, NORMALIZED DIFFERENCE VEGETATION INDEX, NITROGEN, PRINCIPAL COMPONENT ANALYSIS, Wheat, |
| Online Access: | https://hdl.handle.net/10883/22840 |
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