Using Regression Indices and Multiple Criteria Analysis for Study of Some Rice Genotypes under Interaction of Variable Environmental Conditions

Sixteen genotypes of rice (Oryza sativa L.) were evaluated during 2008 and 2009 growing seasons at two regions at the State of White Nile- Sudan (EDduim and Kosti) to assess stability of performance, and identify high yielding genotypes. The aim of the comparative study was to assess the performance of breeding lines developed for various ecosystems and to identify stable genotypes with wide adaptability. A randomized complete block design with three replications was used in each location. Combined analysis of variance revealed highly significant effects of locations, seasons, genotypes and their interactions for most of the studied traits. All the genotypes gave high grain yield which ranged from 2.17 to 4.03 t ha-1 under irrigated conditions. Simple and combined analyses of variance indicated that genotypes differed significantly in grain yield, (NERICA 4, NERICA 14, NERICA 15, YUNLU 33 and WAB-1-38-19-14-P2-HB) were higher yielding genotypes giving 3.78, 4.03, 3.24, 3.55 and 3.51 t ha-1 respectively. Due to the observed temporal and spatial variability multi-objective compromise programming technique is employed to screen these Rice (Oryza sativa L.) genotypes according to their vegetative and yield traits for purpose of selecting the most stable ones that suit irrigated farming conditions of the studied areas Ranking of alternatives was explored in reference to selection criteria weights preferred by an agronomist, in comparison to equal weights. Two genotypes, NERICA 14 and YUNLU 33, were classified as high yielding and stable genotypes across environments (locations and years) because of their high grain yield and best performance of traits, with both a regression coefficient and multi-criteria analysis. These two genotypes could be used in the breeding program and/or may be released to farmers for cultivation in the White Nile State.