AMMI and GGE Biplot Analyses for Mega-Environment Identification and Selection of Some High-Yielding Oat (Avena sativa L.) Genotypes for Multiple Environments.

This paper reports an evaluation of eleven oat genotypes in four environments for two consecutive years to identify high-biomass-yielding, stable, and broadly adapted genotypes in selected parts of Ethiopia. Genotypes were planted and evaluated with a randomized complete block design, which was repeated three times. The additive main effect and multiplicative interaction analysis of variances revealed that the environment, genotype, and genotype-environment interaction had a significant (p ≤ 0.001) influence on the biomass yield in the dry matter base (t ha-1). The interaction of the first and second principal component analysis accounted for 73.43% and 14.97% of the genotype according to the environment interaction sum of squares, respectively. G6 and G5 were the most stable and widely adapted genotypes and were selected as superior genotypes. The genotype-by-environment interaction showed a 49.46% contribution to the total treatment of sum-of-squares variation, while genotype and environment effects explained 34.94% and 15.60%, respectively. The highest mean yield was obtained from G6 (12.52 kg/ha), and the lowest mean yield was obtained from G7 (8.65 kg/ha). According to the additive main effect and multiplicative interaction biplot, G6 and G5 were high-yielding genotypes, whereas G7 was a low-yielding genotype. Furthermore, according to the genotype and genotype-environment interaction biplot, G6 was the winning genotype in all environments. However, G7 was a low-yielding genotype in all environments. Finally, G6 was an ideal genotype with a higher mean yield and relatively good stability. However, G7 was a poor-yielding and unstable genotype. The genotype, environment, and genotype x environment interaction had extremely important effects on the biomass yield of oats. The findings of the graphic stability methods (additive main effect and multiplicative interaction and the genotype and genotype-environment interaction) for identifying high-yielding and stable oat genotypes were very similar.

Growth, yield, and yield variables of onion (Allium Cepa L.) varieties as influenced by plantspacing at DambiDollo, Western Ethiopia.

Onion (Allium cepa L.) is an important bulb plant grown worldwide. Proper use of the agronomic practice has undoubtedly contributed to growing crop yields. The right level of any farming practice, like the distance between plants, plant density, date of planting, and time of harvest, can produce the wanted outcomes. Therefore, this research was piloted to evaluate the influence of plant spacing on the development of bulb harvest-related traits of onion varieties in Dambi Dollo University, Western Ethiopia, in 2021. Three onion varieties (Adama red, Monarch, Nafis) and four intra-row spaces (6 cm, 8 cm, 10 cm, and 12 cm) in factorial combinations were settled by a complete randomized block design which was simulated three times. The findings of the study indicate that all the factors related to crop growth and bulb yield of onion varieties were mainly influenced by different kinds and plant spacing. Conversely, the collaboration of these two factors did not affect all other factors, but the interaction of the two factors had a great effect on the days to maturity measured in this study. The highest plant height was registered on the onion planted at a distance of 10 cm (59.83 cm) and 12 cm (59.08 cm) distance between plants. The high commercial yields (34.44 t ha-1) and entire bulb yield (35.40 t ha-1) were found in the Nafis variety. The highest marketable yields (31.12 ha-1) and entire marketable yield (31.78 ha-1) were recorded on an onion plant planted 10 cm between plants. Therefore, in the research area, farmers can use a variety of Nafis and a 10 cm distance between plants to increase their onion production.

Evidences of climate change presences in the wettest parts of southwest Ethiopia.

Climate change has been identified as a major challenge of rainfed agriculture. To contextualize whether there is climate change footprint, identification of rainfall and temperature trend at regional and local scale is helpful for designing long-term adaptation and mitigation strategies. The present study therefore aims to assess evidences of climate change presences in terms of, climate variability and trend in the wettest parts of Southwest Ethiopia. Daily and monthly historical gridded rainfall and temperature data (1983-2016) of ten stations were provided by Ethiopian National Metrological Agency. Moreover, long years historical recorded climate data of Nekemte and Bedele (1971-2020) and Sekoru (1981-2020) were used in the present study. Coefficient of variation, the Mann-Kendall non-parametric statistical test and Sen's slope estimator, linear regression analysis and the precipitation concentration index were applied to detect the presence of climate change in the southwest parts of Ethiopia. In this study, the trend package of open R software employed for trend identification and rate of change per year. The results indicate that the annual rainfall has declining trend at five stations with statistically significant at one station while the mean maximum and minimum temperature shows a statistically significant increasing trend at eight and six stations, respectively. At a seasonal scale, the amount of rainfall in the main rainy season (June to August) is dominated by a downward trend (eight out of ten stations) while, the autumn season (September to November) shows an increasing trend in all stations with statistically significant at one station. The precipitation concentration index analysis revealed that inconsistent and significantly irregular precipitation is observed at six stations (60%) of the ten stations. This study concludes that the climate of the wettest parts of Ethiopia is getting warmer and the amount of rainfall in the main rainy season has declined in the vast majority of the study area.