Abstract
Pearl millet is grown by inhabitants of the semi-arid zones. Due to the unpredictable climatic conditions the genotype-by-environment interaction (GEI) makes it hard to select genotypes adapted to such conditions. The study objectives therefore were to analyse the patterns of GEI and to identify superior genotypes for grain yield and rust resistance. Seventy six genotypes were planted in four environments in 4×19 alpha design with two replications. The ANOVA results showed that main effects of environments were significant (p ≤ 0.05) for grain yield and highly significant (p ≤ 0.001) for rust resistance while the main effects of the genotypes and their interactions with environments were also important for grain yield and rust severity at 50% physiological maturity. The GGE biplot analysis revealed that environments associated with more rains received during vegetative phase performed better than those receiving more rains during post-anthesis phase. The winner in the best environment for grain yield was ICMV3771×SDMV96053 while Shibe×CIVT9206 and Shibe×GGB8735 were the best for rust resistance.
Highlights
Pearl millet is adapted to environmentally marginalised conditions worldwide (Bashir et al, 2014) and a multipurpose (IFAD, 1999) cereal for people living in semi-arid areas in Uganda (Lubadde et al, 2014)
The combined analysis of variance (ANOVA) results (Table 2) indicate the main effects of environments being significant (p ≤ 0.05) for grain yield and highly significant (p ≤ 0.001) for rust resistance at 50% physiological maturity
Results further show that generally the coefficients of determination (R2) estimated from the AMMI model were low for the traits; an indicator that a greater variation was due to the environments
Summary
Pearl millet is adapted to environmentally marginalised conditions worldwide (Bashir et al, 2014) and a multipurpose (IFAD, 1999) cereal for people living in semi-arid areas in Uganda (Lubadde et al, 2014). The economical approach to control rust is through resistance breeding (Singh, 1990) and selecting genotypes adapted to low input and drought-prone environments (Vadez et al, 2012). The potential performance of improved genotypes under marginal conditions is always obscured by the effect of genotype by environment interaction (GEI) (Yan & Racjan, 2002); leading to selection of genotypes not suitable for particular environments (Cooper & Delacy, 1994) and subsequently leading to low yield. Several methods have been adopted to assess GEI in pearl millet breeding but the GGE-biplot analysis was used in this study because of the ability to graphically better explain the genotype and genotype by environment components of variation and being more efficient in discriminating genotypes and environments (Yan et al, 2007)
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