Thirty bread wheat genotypes were tested to assess the genetic variability, among studied genotypes using alpha-lattice design at Tongo sub-center of Assosa Agricultural Research Center and Kulumsa Agricultural Research Center in 2015. Analysis of variance revealed that there were statistically significant differences among the genotypes for most of the traits at individual and across locations. From the combined analysis of variance, significant (p≤0.05) effect due to location, varieties and G×E was observed for most of the traits. The varieties showed wider variability in mean grain yield of 1284.4-3788.7 kg ha-1 , 2588.3-4683.3 kg ha-1 and 1936.4-4095.6 at Tongo, Kulumsa and across location, respectively. Moderate PCV values (>10%) were obtained for grain yield, 1000 kernel weight, harvest index, tillers per plant and spikes per plant at individual location and across location including days to heading, above ground biomass yield, spike length and kernels per spike at Tongo and above ground biomass yield at Kulumsa. Similarly, moderate GCV values (>10%) were obtained for grain yield, 1000 kernel weight, tillers per plant and spikes per plant at individual location including days to heading, harvest index and kernels per spike at Tongo and above ground biomass yield at Kulumsa. Lower (<10%) was obtained for all traits across location. High heritability estimates (>80%) were obtained for days to heading (86.0%) and days to maturity (85.1%) at Tongo and days to heading (86.2 and 82.69%) and spikes length (80.1 and 82.85%) at Kulumsa and across location. But relatively high genetic advance (>20%) was obtained for grain yield (28.5%) and harvest index (24.3%) at Tongo. Moderate genetic advance (10-20%) was observed for 1000 kernel weight, spikes length and days to heading at individual location and across location including spikelets per spike, tillers per plant, above ground biomass, spikes per plant and plant height at individual location. Generally, it has been observed the presence of variability among the genotypes, heritability in the tested traits of the genotypes studied. Hence, Selection and hybridization on those genotypes based on the trait with high GCV, heritability and genetic advance can be recommended for farther yield improvement of bread wheat at respective location.

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Declining soil fertility is one of the major problems causing yield reduction of rice in Benishangul Gumuz Regional state. Therefore, field experiments were carried out at Bambasi District Assosa Zone, to evaluate and determine the effects of N and P fertilizer rate application on growth, yield and yield components of upland rice. The fertilizer treatments considered in the study was consist of four levels of N (0, 46, 92 and 138 kg N ha −1 ) and four levels of P (0, 23, 46, and 69 kg P 2 O 5 ha −1 ). The experiment was laid out in a randomized complete block design (RCBD) with three replications at Sonka FTC and on three farmers fields consisting of a total of 16 treatments (mother trial). The results of the study revealed that most of yield and yield components of rice were significantly (P<0.05) affected by the main effect of N on mother and baby trails. Except grain per panicle, straw and grain yield; other parameters are not affected by the main effect of P fertilizer rate application. The highest grain yield (3244 kg ha -1 ) was recorded from 92 kg N ha -1 combined with 46 kg P 2 O 5 ha -1 and the lowest grain yield (1415.6 kg ha -1 ) was recorded from the control treatment. Partial budget analysis also indicated that the highest net return (28548 Birr ha -1 ) was obtained from the application of 92 kg N ha -1 combined with 46 kg P 2 O 5 ha -1 fertilizer rate. Thus, from the result of this study, it can be concluded that the application of 92 kg N ha -1 combined with 46 kg P 2 O 5 ha -1 was found to be superior both agronomically and economically for rice NERICA-4 variety under main cropping season in the study area.

A multiplications evaluation was conducted with twenty-eight advanced bread wheat genotypes and two standard checks for two consecutive years 2017 and 2018 at Kulumsa, Asasa, Robe Arsi, Bekoji, Areka, Shambu, Holeta, Adet, Enawari, Awalgera, and Debra Zeit, Ethiopia. The objective of the paper was to describe the agronomic and quality related traits of newly developed bread wheat varieties “Boru” for optimum moisture areas of Ethiopia. Boru is a commercial name given for a newly released variety with the pedigree name SAUAL/MUTUS/6/CNO79//PF70354/MUS/3/PASTOR/4/BAV92*2/5/FH6-1-7/7/CNO79//PF. 70354/MUS/3/PASTOR/4/BAV92*2/5/FH6-1-7 which originated from CIMMYT germplasms. Boru is adapted within the range of altitude 2050 to 2780 masl with annual rainfall amount receiving from 620 to 1290 mm. Boru showed superior overall agronomic performances over the standard check Wane and Hidasse and it had a 9% and 14% yield advantage respectively. The new variety had a bold seed size than the two checks. Boru variety showed relative resistance to stem, yellow and leaf rust as compared to wheat varieties under production at the medium to high land wheat-growing agro-ecologies. Boru offers new hope for resource-poor farmers in rust-prone areas of Ethiopia.  It’s expected to replace the variety ‘Ogolcho’ in medium areas, and ‘Hidasse’ in high land areas of Ethiopia. In addition, the Boru variety is known for its higher protein content (14.37%) than standard check Wane (12.14%) and local check Hidasse (12.3%).

A multi-locations' experiments were carried out from 2018 to 2019 main cropping seasons in moisture stress areas of Ethiopia to estimate the genotype x environment interaction and to select stable and adaptable variety/ies for grain yield of bread wheat. The genotypes consisted of 23 genotypes and two standard checks arranged in alpha lattice design replicated three times. Data were taken for agronomic traits and diseases. Analysis of variances and stability analysis were carried out for grain yield using R software. Combined analysis of variance showed a highly significant (p≤0.01) difference among the genotypes, locations, and GEI for grain yield suggesting a differential response of genotypes across testing environments. The grand mean yield over nine environments was 5251.90 kg ha -1 and the mean yield of genotypes across nine environments ranged from 1539.29 kg ha -1 in 2018 at Dhera to 7621.87 kg ha -1 in 2018 at Kulumsa, respectively. The recorded mean yield of the standard check Deka (5066.543 kg ha -1 ) and Ogolcho (4018.39 kg ha -1 ) was below the grand mean yield of genotypes across environments. The Genotypes ETBW 9136 (5731.79 kg ha -1 ), ETBW 9139 (5844.87 kg ha -1 ), ETBW 9646 (5754.01 kg ha -1 ), ETBW9172 (5634.01 kg ha -1 ), ETBW9641 (5545.03 kg ha -1 ), ETBW 9080 (5545.31 kg ha -1 ) and ETBW9396 (5467.04 kg ha -1 ) gave the highest mean grain yield across environments, whereas the standard check Ogolcho recorded lowest mean grain yield across environments. The first four principal components of the GEI explained 85.6% of the variation. Additive main effects and multiplicative interaction (AMMI) stability parameters revealed that the genotypes ETBW 9080 (G11), ETBW 9172 (G12), ETBW 9646 (G19), ETBW 9396 (G13), ETBW 9452 (G14), ETBW 9136 (G5) and ETBW 9139 (G6) were high yielder and more stable inferring little interaction of genotypes with the environment whereas Ogolcho (G25), ETBW 9119 (G3), ETBW 9647 (G20) and ETBW 9065 (G8) was low yielder and unstable suggesting high interaction with the environments. Based on stability parameters and other agronomic traits, the genotypes viz. ETBW 9396 (G13) and ETBW 9080 (G11), were proposed for variety verification and possible release in 2021.