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Multi environment and spatial analysis of early maturing sorghum [Sorghum bicolor (L.) Moench] genotypes in dry lowland areas of Ethiopia	 	Amare Seyoum1, Amare Nega1, Kedanemaryam Wagaw1, Taye Tadesse2, Diriba Tadesse2, Alemu Tirfessa1, Habte Nida3, Adane Gebereyhones1, Sewmehone Siraw1, Tsegaye Gebremariam4, Chalachew Endalamaw1, Hailemariam Solomon1, Tamirat Bejiga1, Tokuma Legesse1, David Jordan5, Emma Mace5, Daniel Nadew1, Ligaba Ayele1 and Meron Bogale1	 	1Ethiopian Institute of Agricultural Research (EIAR), Melkassa Agriculture Research Center, P. O. Box 436, Adama, Ethiopia.	2Ethiopian Institute of Agricultural Research (EIAR), Head Quarter, P. O. Box 2003 Addis Ababa, Ethiopia.	3Purdue University, 610 Purdue Mall, West Lafayette, IN 47907, United States.	4Tigray Agricultural Research Institute (TARI), P. O. Box 492, Mekelle, Ethiopia.	5Queensland Alliance for Agriculture and Food Innovation, Hermitage Research Facility 604 Yangan Rd Warwick QLD 4370, Australia.	 	Received 28 September, 2019; Accepted 31 January, 2020	 	In Ethiopia, drought usually occur due to delay in onset, dry spell after sowing, drought during critical crop stage (flowering and grain filling stage) and too early cessation of rainfall. These situations can be addressed by developing improved sorghum varieties which are resistance to drought. Developments of sorghum varieties resistant to drought and producing better grain yield while addressing the plant biomass requirement is one of the strategies in the sorghum breeding program in dry lowland environment. A total of 90 early maturing sorghum genotypes were evaluated along with two standard check varieties to estimate the grain yield, plant height, days to flowering, days to maturity and overall agronomic aspects and stability of performance across the test environments. The trial was conducted using Randomized Complete Block Design (RCBD) in row and column arrangement. Linear mixed model has been used to predict and identify stable and superior varieties across the test environment. Correlations of the trials range from positive +1 to -1 where positive correlation is an indication of similarity among the testing environments while negative correlation is an indication of non-similarity among testing environments. Moreover, using the biplot it was observed that the stability and correlation among testing site where the angle between the two lines measure the strength of correlation. Improvement in heritability has been obtained due to spatial variation using advanced statistical analysis methods without any additional cost. Three genotypes exhibited better yield advantage, higher plant biomass and overall plant aspect including drought tolerance. In addition, these genotypes were preferred by farmers in their overall agronomic desirability (drought tolerance, earliness, head exertion and compactness, grain size and shape and threshability. Also, the national variety releasing committed has evaluated the variety verification trial both on station and farmers’ field condition in 2018/2019 and they decided the release of the candidate variety 14MWLSDT7114 (2005MI5060/E-36-1) for commercial production in dry lowland environment.	Key words: Genotype, heritability, mixed model, Spatial analysis, GEI, correlated environment.