Suitability Analysis for Scaling Chickpea Improved Varieties in Ethiopia

Abstract Background: Appropriate decision-making on crop production will reduce various risk factors associated with unsustainable land management. The limited available arable land be taken for granted which may turn from ‘best’ to ‘worst’ irrespective of the kind of land use and management practice without understanding its special requirements and potential use. GIS has contributed to the speed and efficiency of the overall planning process in agricultural land use suitability, since it enables quick and efficient access to large amounts of information, exhibiting relationships, patterns, and trends that are useful in monitoring land use potential and suitability evaluation. As crop’s environmental requirements vary from variety to variety, it is recommended to undertake variety specific analysis and mapping for better understand the extent of scaling-up the specific crop technologyResults: GIS-based land suitability map for chickpea was generated for each variety under consideration mapped showing their percentage area coverage of suitability for each regional states in Ethiopia. Based on, the suitability analysis desi chickpea varieties Mastewal, Naatolii, Teketay and Arerti, Habru, Kasech, and Yelbey kabuli chickpea varieties classified as highly suitable that cover 0.67, 0.71, 1.4, 2.3, 1.3, 2.4 and 1.2 million ha of the country respectively. While moderately suitable areas for the same varieties cover 25.2, 11.3, 25.9, 26.4, 26.6, 9.6, 17.1 million ha.Conclusion: The suitability analysis results show that the currently available improved varieties of chickpea can be targeted for scaling out in the identified land suitability classes in Ethiopia with some caution. Amhara, Oromia, SNNP and Tigray remain the major regions with suitable areas for production of available varieties of chickpea compared to Afar, Benishangul Gumuz, Gambella, and Somali regions. However, the highly suitable areas are limited compared to moderately suitable areas, which are higher across the regions.