A total of 78 alleles and 29 loci were detected from nine microsatellite and three minisatellite markers, respectively across 26 blast and ufra disease resistant genotypes. For blast resistant genotypes, the Polymorphic Information Content (PIC) values ranged from 0.280 to 0.726 and RM21 was considered as the best marker. PIC values ranged from 0.5953 to 0.8296 for ufra resistant genotypes and RM23 was the best marker for characterization of ufra resistant genotypes. The genetic similarity analysis using UPGMA clustering generated nine clusters with coefficient of 0.66 for blast resistant genotypes while five genetic clusters with similarity coefficient of 0.42 for ufra resistant genotypes. In order to develop resistant varieties of two major diseases of rice, hybridisation should be made using the parents, BR29 and NJ70507, BR36 and NJ70507 for blast, while BR11 and Aokazi, BR3 and Aokazi, Rayda and BR3 and Rayda and BR11 for ufra.
Studies were conducted to assess the genetic relationships between the parental palms (dura and pisifera) and performance of their progenies based on nine microsatellite markers and 29 quantitative traits. Correlation analyses between genetic distances and hybrids performance were estimated. The coefficients of correlation values of genetic distances with hybrid performance were non-significant, except for mean nut weight and leaf number. However, the correlation coefficient of genetic distances with these characters was low to be used as predicted value. These results indicated that genetic distances based on the microsatellite markers may not be useful for predicting hybrid performance. The genetic distance analysis using UPGMA clustering system generated 5 genetic clusters with coefficient of 1.26 based on quantitative traits of progenies. The genotypes, DP16, DP14, DP4, DP13, DP12, DP15, DP8, DP1 and DP2 belonging to distant clusters and greater genetic distances could be selected for further breeding programs.
Upland rice is important for sustainable crop production to meet future food demands. The expansion in area of irrigated rice faces limitations due to water scarcity resulting from climate change. Therefore, this research aimed to identify potential genotypes and suitable traits of upland rice germplasm for breeding programmes. Forty-three genotypes were evaluated in a randomised complete block design with three replications. All genotypes exhibited a wide and significant variation for 22 traits. The highest phenotypic and genotypic coefficient of variation was recorded for the number of filled grains/panicle and yields/plant (g). The highest heritability was found for photosynthetic rate, transpiration rate, stomatal conductance, intercellular CO₂, and number of filled grains/panicle and yields/plant (g). Cluster analysis based on 22 traits grouped the 43 rice genotypes into five clusters. Cluster II was the largest and consisted of 20 genotypes mostly originating from the Philippines. The first four principle components of 22 traits accounted for about 72% of the total variation and indicated a wide variation among the genotypes. The selected best trait of the number of filled grains/panicle and yields/plant (g), which showed high heritability and high genetic advance, could be used as a selection criterion for hybridisation programmes in the future.