Lack of suitable varieties that exhibit stable yield performances across wide ranges of environments is the major factor among several production constraints contributing to low productivity of Arabica coffee in Ethiopia. Eleven advanced Limmu coffee genotypes were evaluated in eight environments (four locations over two years) to determine the existence of GEI and yield stability performances. The experiment was laid out in a randomized complete block design of two replications under all locations. Combined analysis of variance showed a highly significant effect of genotype by environment interaction indicating the differential yield response of genotypes across different environments. The major proportion of the variation explained by environments was 42.74% of the total variation. Nevertheless, the contribution of the genotypes to the total variance was much smaller than the environments, and the genotype by environment interaction. Different stability models such as additive main effect and multiplicative interaction (AMMI), AMMI stability value, cultivar superiority index and yield stability index were used for stability analysis. The first two Interaction Principal Component Axis (IPCAs) of AMMI exhibited a highly significant effect and cumulatively contributed about 63.21% of the total interaction sum of squares. Two high yielding genotypes, namely (L52/2001) and (L55/2001), on average, showed stable performance across environments. On the other hand, the study also illustrated the presence of location specific high yielding coffee genotype such as L56/2001. Regarding the test environments, Gera 2015/16 (E5) is considered as a more stable site over the rest environments, while Agaro 2015/16 (E7) was considered to be the most interactive environment. Based on the result of the study, coffee breeders or farmers would be recommended for wise selecting either for location specific or wider adaptable coffee genotypes leading to substantial yield increase under Limmu coffee growing areas.

Understanding the genetic variability, heritability and genetic advance of traits in any plant population is an important prerequisite for breeding program. The experiment was conducted to assess the magnitude of genetic variability, heritability and genetic advance of 24 maize inbred lines for 16 quantitative traits. The field experiment was conducted during 2016 cropping season at Jimma Agricultural Research Center (JARC). Alpha lattice (0, 1) design with three replications and nine blocks was used. Analysis of variance showed high significance (P<0.01) differences among genotypes for all traits studied except tassel size. The genotypic coefficient of variation (GCV) for all traits studied was smaller than the phenotypic coefficient of variation (PCV), indicating the significant role of environment in the expression of traits studied. The estimates of PCV and GCV was high for grain yield, thousand kernel weight, ear height, ear diameter, anthesis and silking interval and plant aspect. Heritability estimates ranged from 9.15 for tassel size to 96.02 for thousand kernel weight. Estimates of genetic advance as percent of mean at 5% selection intensity ranged from 2.76% for days to maturity to 50.69% for grain yield. High heritability along with high genetic advance was obtained for plant height, ear length and 1000-kernel weight, indicating the predominance of additive gene effects in controlling the traits and effective selection on the basis of these traits would be absolutely useful for the improvement of inbred lines. Therefore, it could be recommended that due emphasis should be given for these traits for the improvement of maize inbred lines.

Tea (Camellia sinensis) is one of the most commonly consumed beverages next to water worldwide. However its production and productivity is constrained by many fungal diseases in Ethiopia. Despite this, there is lack of information on the status of the diseases and lack of knowledge on features of the pathogens associated with the diseases as there have been no any systematic assessments conducted so far. Therefore, the current works were designed with the objectives to assess the distribution of tea diseases and identify the associated pathogens. For this purpose, field surveys were carried out across three tea estate farms (Wushwush, Chewaka and Gumaro) and tea out growers surrounding them in Kafa, Sheka and Ilu Aba Bora zones in Southwest Ethiopia during the 2019 season. Causative pathogens of the diseases were identified using cultural and morphological features. The average Fusarium wilt incidence varied from (0 to 20%), Black rot (7-15%), Bird's eye spot (4-15%), Brown blight (2-5%) and Grey blight (0.5-5%) while mean disease severity of Black rot, Eye spot, Brown blight and Grey blight ranged from 4-11%, 3-9%, 1-5% and 0.5-5%, respectively. Fusarium wilt, black rot disease and eye spot diseases of tea directly related to tea yield loss. Algal leaf spot disease caused by Cephaleuros virescens was observed at Gumaro tea estate farm on the older leaves of aged tea bushes. The present study revealed the economic importance of tea diseases in Southwest Ethiopia. Future research should be directed towards the investigation and determination of management options for the control of important diseases of tea in the country.

Forty seven Coffea arabica L. germplasm accessions collected from Limmu district were field evaluated from 2004/5 to 2013/14 with two commercial check varieties at Agaro Agricultural Research sub center in single plot. The objective of the experiment was to assess the variability among the accessions using quantitative traits. Data for about eight quantitative traits were recorded only once in experimental period, while the yield data were recorded for six consecutive cropping seasons. Cluster, genetic divergence, and principal component analysis were used to assess the variability among the genotypes. The results revealed that average linkage cluster analysis for nine traits grouped the germplasm accessions in to three clusters. The number of accessions per cluster ranged from three in cluster III to 25 in cluster II. The clustering pattern of the coffee accessions revealed that the prevalence of moderate genetic diversity in Limmu coffee for the characters studied. The maximum inter-cluster distance was observed between clusters II and III; whereas the minimum inter-cluster distance was observed between clusters I and II. The study highlighted the possibility of using accessions of the distant clusters as potential candidates for the genetic improvement of Limmu coffee through hybridization. Moreover, the principal component analysis showed that the first four PCs extracted about 82% of the total variance of the 49 coffee germplasm accessions and also confirmed moderate diversity among the germplasm accessions since the entire variation cannot be explained in terms of few PCs. This, in turn, indicates that the involvement of a number of traits in contributing towards the overall diversity.

Coffee is the main Ethiopia's most important agricultural export crop, which is providing about 25-30% of foreign exchange earnings. The estimation of stability performance of the cultivars becomes most important to detect consistently performing and high yielding genotypes. Eleven Arabica coffee genotypes were evaluated in southwestern part of the Ethiopia across four locations for two consecutive years (2014/15 -2015/16). The objective of the study was to estimate the presence of the interaction between genotypes and environments; and the stability performance of the coffee cultivars for its bean yield. The experimental design was Randomized Complete Block Design (RCBD) replicated twice in each testing location. Genotypes were evaluated by Genotype main effect and genotype x environment interaction (GGE) biplot. The combined analysis of variance indicated that genotypes, environments and GEI showed highly significant (p<0.01). Total variation explained was 41.63% for environments, 9.31% for genotypes and 32.32% for genotype by environment interaction (GEI). This obviously shows that the effect of the genotypes to the total variance was minimal when compare to the environment and the GEI. GGE biplot grouped the environments into four clusters with five genotypes being the winners in different group of environments. Top yielding cultivars namely; L52/2001 and L55/2001; and E6 (Jimma 2015/16) were identified as an ideal genotype and environment, respectively. In this study, stable genotypes, suitable environment for each of the coffee genotype and environment similarity based on bean yield were identified.