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The study was carried out on twenty varieties of upland rice (oryza sativa L.) to find out the correlation and path co-efficient values among the grain yield and its’ components. Genotypic and phenotypic coefficients of variation ranged from 6.44 (days to maturity) to 30.47% (yield per plant) and 6.51 (days to maturity) to 30.67% (yield per plant), respectively. High genotypic and phenotypic coefficients of variation with low magnitude of differences between the two were observed for days to maturity, yield per plant and number of filled grains per panicle. Highly significant (P

Analyzing Genotype-Environment interaction (GxE) is useful for exploring the opportunities and limiting the drawbacks of the effects. An investigation was conducted on 12 environments (six locations and two years) to study GxE and stability of 18 tef varieties, and to identify desirable environments. The experiment was laid in a randomized complete block design with three replications. The result of AMMI analysis of variance showed that tef grain yield was significantly (P < 0.001) affected by environments (E), genotypes (G) and GxE. Environment, G and GxE explained about 90.23%, 1.03% and 8.74% of the total sum of squares of treatments, respectively. The partitioning of the GxE by AMMI analysis showed that two of the Interaction Principal Component Axes (IPCAs) were highly significant (P < 0.001). The two IPCAs explained 66.06% of the total GxE in grain yield of the tef genotypes. AMMI1 showed that genotypes G and D had small interaction effects. Likewise, environments MR06 and KB07 had the highest interaction effects whereas SR06, KB06, JM06 and JM07 had smaller interaction effects. AMMI2 also showed that environments MR06, KB07 and CH07 exerted higher interaction effects; however, KB06, JM06 and JM07 exerted lower interaction effects. The GGE biplot identified three mega-environments: The first mega-environment is composed of environments Kobo, Jari and SR07 with genotype Tseday as a winner; genotype Ziquala represented the second mega-environment containing Jamma, Chefa and SR06; the third environment, made up of Mersa, was represented by genotype Asgori. Tseday was the most desirable variety; while Mersa was the least desirable environment.

Associationand path analysis of yield related traits is essential for breeders. Theobjectives of this study was to investigate the relationship among yield, yieldrelated traits and Striga parameters. The experiment was conducted at Koboresearch sub-center, North eastern Ethiopia in 2018 main cropping season usingsimple lattice design. Phenotypically positivelysignificant traits were head weight(0.79*),head number(0.45*),panicle width(0.29*),andpanicle length(0.26*)Whereas, phenotypically and genotypically negative significant(P < 0.05) for DF (rp = -0.28,rg = -0.32), DM (rp = -0.27, rg= -0.28) andStm-2( rp = -0.36, rg = -0.61),SV(rp= -0.48, rg = -0.73) and SSV (rp = -0.37, rg =-0.69), respectively. Generally, positive and significantgenotypic correlation in grain yield (kg ha-1) showed with head weight, panicle width, above ground biomass, head number (rg =0.23*) and thousand kernel weight.

Striga is major biotic constraint and a serious threat to sorghum production in areas of semi- arid tropics. The objectives of this study were to evaluate the performance of 49 sorghum genotypes including resistance and susceptible checks to Striga hermonthica and estimate genetic variability, heritability and genetic advance. The experiment was conducted at Kobo research sub-center, North Eastern Ethiopia in 2018 main cropping season using simple lattice design. The analysis of variance revealed significance difference among the genotypes for all traits including grain yield, days to maturity, plant height and Striga count ranged from 1462-7972 kgha-1, 112-130days, 120-285cm and 3.35-34.25 Striga counts, respectively. Genotypes ETSC-14118-2-1, ETSC-14019-9-1, ETSC-14184-8-3, ETSC-14019-14-2, ETSC-14127-1-3, ETSC-14018-1-3, ETSC-14217-10-1, host low number of Striga count. The genotypic coefficient of variation (GCV) ranged from 2.97% for days to maturity (DM) to 24.94% for grain yield, while phenotypic coefficient of variation (PCV) ranged from 2.26% for DM to 33.34% for biomass (BM). Plant height and head weight show high heritability and high genetic advance. The first seven PCA explained 89.5% of the total variation and the traits plant height (0.83), Striga severity (0.71) days to maturity (0.59), panicle length (0.56) and days to flowering (0.54) accounted for most of the variability. Six clusters were found and significant distances were observed among cluster IV and V, and III and IV. Accordingly, resistance, tolerance and susceptible genotypes were identified. However, further research is needed to test these genotypes to prove the current results.

The knowledge of genetic diversity is valuable for germplasm conservation and for crop improvement. An investigation was undertaken at Sirinka and Kobo Research Stations in 2006 to assess phenotypic diversity of 160 landraces and 6 varieties of tef and to identify the most important traits in differentiating the landraces. The result showed appreciable ranges of values for traits like days to maturity, plant height, biomass- and grain-yield suggesting the presence of sizable variability in the tef landraces. Grain yield was positively and significantly correlated with plant height (0.245**), panicle length (0.22**), biomass (0.907**), harvest index (0.474**) and days to heading (0.284**). The stepwise regression analysis suggests linear increment in plant height, harvest index and biomass yield could lead to significant increase in tef grain yield. In the principal component (PC) analysis, 74% of the total variability was explained by three PCs. Biomass yield from the first PC; and day to heading, grain-filling duration, plant height, panicle length and culm length from the second PC axis were important in discriminating the landraces. Two-step cluster analysis divided the landraces into three groups. Landraces with late flowering, short grain-filling period, high biomass, high grain yield and high harvest index were grouped in cluster II. Landraces in cluster II could therefore be used as parent lines for future breeding programs. Biomass yield, harvest index and plant height could be set as indirect selection criteria to improve yield of tef., Abyssinia Journal of Science and Technology, Vol. 2 No. 1 (2017)

Genetic diversity is of paramount importance for the success of any plant breeding program. An experiment was conducted to assess the extent of genetic diversity and similarity of 24 rice cultivars from various origins using 29 simple sequence repeat (SSR) markers. A total of 144 alleles were detected at the 29 SSR primer pairs evaluated in the 24 cultivars. The number of alleles per loci ranged from 3 to 8 with a mean of 4.966 alleles per locus. The mean unbiased expected hetrozygosity (UHe) and expected hetrozygosity (He) were 0.674 and 0.659, respectively. Cluster analysis using UPGMA algorism divided the 24 cultivars into two major groups. Group I contained the two NERICA, all japonica, and a tropical japonica cultivar. Group II contained the NPT and all indica cultivars. The genetic diversity analysis showed the presence of higher allelic diversity in the cultivars analyzed. NERICA cultivars, which showed greater dissimilarity from all the other cultivars, could be used as parents in future breeding programs so as to come up with transgresive segregants.Keywords: Genetic diversity, hetrozygosity, NERICA, rice, simple sequence repeat (SSR) markersAfrican Journal of Biotechnology Vol. 12(26), pp. 4074-4081