A significant Genotype by Environment Interaction (GEI) makes selection of stable genotypes difficult. This study was conducted to establish the effect of GEI on yield of Common bean genotypes and reduce complaints on the under performances. Eighteen (18) Common bean genotypes were assessed for variation in gene expression linked to yield and yield predictors on three different districts in Mbeya region (Mbarali, Mbozi and Mbeya districts).  Regression, pooled ANOVA and AMMI biplot models were used to evaluate the data. Variety performance showed significant variations in yield between the districts.  A similar scenario was observed in regard to yield predictors. Regression analysis showed that in Mbarali 50% was the significant yield predictor (P = 0.027) while pods/ plant was the trait mostly linked to yield in Mbozi. (GEI) analysis using the AMMI model revealed that best variety performance by location based on yield. Interaction principle component (IPC1) was highly significant (P = 0.0001) and contributed about 69.1% of GEI variation.  The genotypes SER 83 and RCB 266 where highly adaptable in Mbarali site.  The genotypes SER 45 and KG 521 showed specific interaction with the environment of Mbozi district. A total of five genotypes proved to be superior in Mbeya district.  The most adapted stable variety with highest grand mean yield across all three mega environments was RCB233 (IPC1= 0.07, yield = 1073 t/ha). The environment in Mbarali was found to be most predictable for evaluation of Common bean genotypes.

Given the efforts invested on addressing climate change adaptation particularly in agriculture, the adoption of climate smart varieties has not met the expectations. A number of crop varieties developed targeting drought prone areas largely remained un-adopted hence unknown to the majority of farmers or lack traits deemed special for adaptation to climate change in target areas. Variety adoption rate is highly dependent on its adaptation to particular environmental conditions including suitability to tolerate drought, salinity and acidity and ability to meet different livelihood needs such food, fodder and cash. Poor adoption emanates from lack of awareness and the volatility of the farming environment coupled with poor integration of seed business into private public partnership. Rapid adoption of climate smart varieties in Tanzania would require better policy intervention with a well-organized extension system and modifications in variety testing procedures, including the current guidelines for variety release. In this work the authors discuss some approaches that can be used to enhance the adoption of climate smart varieties in Tanzania and cite a few specific cases based on experience from Tanzania.