- Black Sea Journal of Agriculture
- Volume:2 Issue:3
- Phenotypic Characterization and Assessment of Genetic Diversity for Agro-Morphological Traits of Eth...
Phenotypic Characterization and Assessment of Genetic Diversity for Agro-Morphological Traits of Ethiopian Chickpea (Cicer arietinum L.) landraces
Authors : Awol ADEM, Bulti TESSO
Pages : 146-155
View : 15 | Download : 5
Publication Date : 2019-07-01
Article Type : Research Paper
Abstract :Ethiopia has a large number of Desi type chickpea landraces. However, limited information is available about the landraces character. This experiment was conducted in 2016 at Sirinka and Jari, under rainfed condition to characterize and assess genetic diversity among the Ethiopian chickpea landraces. Two hundred two new germplasm accessions were grown in an alpha lattice design with three replications. Data on 16 traits were collected and analyzed. Differences among the genotypes were highly significant insert ignore into journalissuearticles values(p<0.01);.The genotypes were grouped into five clusters with different sizes. Genetic distances among the clusters were significant. The highest diversity indices pooled over characters within zones were recorded for accessions from South West Shewa insert ignore into journalissuearticles values(H= 2.03 ± 0.05); followed by Gurage insert ignore into journalissuearticles values(H=0.81 ± 0.08);, West Shewa insert ignore into journalissuearticles values(H=0.73 ± 0.04); and North Gonder insert ignore into journalissuearticles values(H= 0.72 ± 0.05);. The existence of wider morpho-agronomic diversity among the chickpea collections implies the potential to improve the crop and the need to conserve the diversity. Future collecting operations of chickpea germplasm should strategically focus on areas with relatively large variation. From genetic conservation point of view, it appears that South West Shewa, Gurage, West Shewa and North Gonder, could be suitable as in situ conservation sites.Keywords : Landraces, Morpho Agronomic, Diversity, Clustering