GENOTYPE BY ENVIRONMENT INTERACTION ON YIELD AND MICRONUTRIENT CONCENTRATION OF BIOFORTIFIED COMMON BEAN (Phaseolus vulgaris L.) IN ETHIOPIA

Abstract

Micronutrient malnutrition has becomes the most serious challenge of humanity and most commonly lacking in human diets are Fe and Zn. Biofortification sustainably can reduce deficiencies by increasing Fe and Zn in staple foods. Genotype × Environment interaction (GEI) indicates differential reaction of genotypes to changes in environmental conditions; it becomes more important as the differences in production environment become diverse. Thus, this study was conducted to analyze GEI of yield, grain Fe and Zn content and their stability in biofortified common bean genotypes across different bean growing areas of Ethiopia and to assess the nature of associations between grain micronutrient content with agronomic traits and soil characters. Twenty five biofortified common bean genotypes were evaluated across seven differing environments in 2016 main cropping season. The experiment was laid out as a 5×5 triple lattice design. Among the seven environments, the genotypes recorded the highest grain yields in Hawassa and Arsinegelle with mean yield of 3.02t/ha and 2.97t/ha, respectively. The average grain yield of biofortified common bean genotypes were 2.31t/ha. NUA 94(2.86), NUA 99 (2.80), and Gofta (2.79t/ha) were among the top yielding genotypes. Alemtena gave the highest mean grain contents of Fe of 69.5mg/kg while, Areka recorded the highest grain Zn content with a mean of 38.3mg/kg. The across location mean of genotypes for micronutrient grain content were 64.02mg/kg for iron concentration and 35.96mg/kg for zinc concentration. Genotypes performed differently for grain Fe and Zn concentration across environments, but genotypes NUA 225 and NUA 517 had consistently high Fe and Zn grain concentration across locations. Combined ANOVA revealed highly significant difference (p< 0.01) among genotypes (G), environments (E) and GEI for grain yield, Fe/Zn and for all morpho-agronomic traits. For grain yield, environment was the largest contributor (52.93%) to the observed variation and followed by GEI (21.97%) and G (12.9%). Fe was greatly affected by G (38.88%) and moderately by E (31.41%) and GEI (20.18%). ANOVA for grain Zn indicated that GEI, G and E accounted for 32.25%, 27.33% and 20.47%, respectively. With the exception of NUA 94, no other genotype showed combined high yield and micronutrient grain concentration, since a weak correlation between these traits was observed. AMMI model was used to identify stable genotypes and genotypes with wider and specific adaptation. Accordingly, genotypes NUA 99, NUA 741 and NUA 672 had higher yield and wider adaptation for grain yield, while NUA 94 was specifically adapted to Arsinegelle. NUA 225 and NUA 345 had high concentration for both micronutrients and wider adaptation, whereas NUA 517 was specifically adapted to Hawassa. The three stability parameters used in the study selected NUA 99 and NUA 741 as a stable genotype for grain yield and NUA 345, NUA 56, NUA 739 and NUA 225 for both micronutrients. Generally, genotypes NUA 99 and NUA 741 for grain yield; NUA 225 and NUA 345 for grain micronutrients were best performing and wider adaptable, therefore can be grown in bean growing areas of Ethiopia. Seed per pod and number of pods per plant had strong positive association with grain yield. Grain Fe and Zn had strong positive phenotypic and genotypic correlation with flowering date, maturity date, pod length and pod width; and had weak correlation with grain yield. Correlation between grain Fe and Zn concentration was fairly high. This suggests ample scope for simultaneous improvement of both the micronutrients. Among soil characters pH, P and clay with positive and negative effects showed the most correlation with grain micronutrient.