©Haramaya University, 2020 ISSN 1993-8195 (Online), ISSN 1992-0407(Print) East African Journal of Sciences (2020) Volume 14 (2) 111-120 Licensed under a Creative Commons *Corresponding Author. E-mail: misganaw1129@gmail.com Attribution-NonCommercial 4.0 International License. Adaptation of Food Oat (Avena sativa L.) Genotypes in Amhara Region, Ethiopia Misganaw Ferede1*, Melle Tilahun1, Zina Demsie1, Ermias Abate2, Molla Mekonnen1, Gebremariam Asaye1, Mequanint Andualem1, Fentanesh Sendekie1, Desalegn Getaneh1, Yasin Taye1, and Sefinew Wale1 1Adet Agricultural Research Center, ARARI, EIAR, P.O. Box 08, Bahir Dar, Ethiopia 2Amhara Agricultural Research Institute, EIAR, P.O. Box 527, Bahir Dar, Ethiopia Abstract Background: Oat is one of the soil acidity tolerant crops among cereal crops. In Ethiopia, However, it is mainly cultivated for animal feed using local cultivars with poor agronomic and soil management practices in soil acidity prone areas. Objective: There are a lot of improved and commercial oat varieties released by European countries that are recommended for both food and feed. Therefore, the study was conducted to identify high-yielding and disease-resistant oat genotypes in acid soil highland areas of Amhara region. Materials and Methods: The study was conducted at Adet, Banja, Fajie, Farta, Geregera, Sekela, Sekota and Sinan in the Amhara Regional State of Ethiopia. Thirteen introduced food oat genotypes and one local cultivar as a check were used as experimental treatments. The experiment was laid out as a randomized complete block design with three replications. Results: The combined analysis of variance showed significant (P≤0.05) differences for grain yield and yield related traits of among genotypes, environments, and their interactions. The combined grain yield performance range was 3904 kg/ha to 3045 kg/ha in food oat genotypes. Food oat genotypes G4, G5, G10, G2, G13, G8 and G12 showed higher interaction to the environmental factors and also higher in grain yielding performance than the remaining tested oat genotypes across the tested environments. Therefore, these genotypes are relatively wider in adaptation across the tested environments. However, food oat genotypes only Goslin (G4) and Souris (G12) were more both widely adaptable and resistance to oat diseases over the local cultivars. Conclusion: Among the 13 introduced food oat genotypes, Goslin (G4) and Souris (G12) were higher in grain yield performance, with a grain yield advantage of 26.93% and 18.16% and resistance to oat diseases over the local cultivars. Therefore, Food oat genotypes Goslin (G4) and Souris (G12) should be demonstrated and scaled out in soil acidity prone high land areas of Banja, Fajie, Farta, Geregera, Sekela and Sinan districts and in areas with similar agro-ecologies of Ethiopia. Keywords: Grain yield; Oat diseases; Resistant; Soil acidity 1. Introduction Oat (Avena sativa L.) is an important food crop as oat grain contains high levels of β-glucan, which has been found to decrease serum glucose and cholesterol levels. In addition, the high levels of oil and protein, as well as other beneficial attributes of oat grain, offer advantages for human consumption when compared with other grain cereals (Loader, 1991; Douhlert et al., 2001). In proportion to other cereal crops, oat is considered to be better suited for production under marginal environments, including acidity soils and soils with low fertility (Hoffmann, 1995). Currently Russia, Canada, Australia, Finland and USA are the major oat producing countries (FAOSTAT, 2018). However, in Ethiopia, oat is a minor crop grown in cooler highlands. Oat is remaining an important crop in marginal ecologies, for grain as well as for feed. It is adapted to a wide range of soil types and can perform better than other small-grain cereals on acid soils. Low soil pH and associated soil infertility problems are considered to be amongst the major challenges to acid sensitive crops production. The farmers consider it as healthy food and suitable to human health. The farmers report that the cattle also prefer oat straw to tef straw. This suggests that oat is an ideal crop for mixed farming system of acid soil affected areas as quality food and feed. Currently, there is no any research and development support for oat production in the areas. On the contrary, according to the market assessment information, imported oat is sold for over 65 birr per 500g at supermarkets in urban centers like Bahir Dar, suggesting ample opportunity for oat production, processing and marketing. Tolerant genotypes are used in rotation with crops such as potato which require acid soil (pH <5.4) so as to control potato scab disease and therefore are best options in areas where application of lime is difficult (Foy et al., 1987). Oat is tolerated to Al-toxicity through release of malate from their roots (Radmer et al., 2012). These organic acids detoxify Al ion by chelating and forming Al-carboxylate complex which cannot enter the mailto:misganaw1129@gmail.com Misganaw et al. East African Journal of Sciences Volume 14 (2) 111-120 112 root system (Kochian et al., 2005). Tolerance of oat to acid soil with high exchangeable Al is controlled by dominant genes that allow easy identification and selection of tolerant lines by using simple screening protocols (Nava et al., 2006; Radmer et al., 2012). Major limitations constraining oat production and productivity in the acid soil prone highlands are poor quality and productivity of existing cultivars. On other hand, there are high grain yielding and disease resistant oat genotypes resistant to stress environments out of Ethiopia. Therefore, it was important to introduce and evaluate the high yielding and diseases resistant oat genotypes. The study was conducted with the objective of to identify high yielding and acidic soil tolerant oat genotypes with resistance to economically important disease in soil acidity prone highlands of Amhara region. 2. Materials and Methods 2.1. Description of Experimental Sites, Materials and Procedures The study was conducted at Adet and Farta (potential areas), Banja, Sinan, Sekela and Fajie (soil acidity prone highland areas), Sekota and Geregera (moisture deficit highland areas) in 2017 cropping season. The experimental environments are depicted in Tables 1 and 2, respectively. Table 1. The description of agro ecological information of environments. Environment Geographical location Altitude (m.a.s.l.) Latitude Longitude Adet 2238 11o16՛N 37o29՛E Farta 2706 11o51՛N 38o01՛E Sekela 2490 10o51՛N 37o08՛E Banja 2560 10o57՛N 36o56՛E Sekota 2266 12o38՛N 39o02՛E Sinan 2782 10o32՛N 37o43՛E Fajie 2840 09o41՛N 39o32՛E Geregera 2865 10o68՛N 38o68՛E Note: Data organized from Ethiopia Metrological Agency (Bahirdar Branch) and GPS and m.a.s.l ₌ meters above sea level. Table 2. Soil physio-chemical properties of the study areas. Location Soil physico-chemical data PH Ex. Acidity Ex. Al %OC %N P ppm CEC Banja 5.29 0.25 - 3.01 0.25 23.75 28.91 Farta 5.41 - - 1.92 0.14 26.96 35.65 Sekela 5.30 0.21 0.00 3.55 0.28 15.64 27.70 Sinan 5.3 1.2 0.09 1.60 - 10.90 - Note: Data on soil physical and chemical properties were sourced from soil analysis laboratory of Adet Agricultural Research Center. Thirteen introduced oat genotypes and one local cultivar as check were used as experimental treatments. The trail was laid out in randomized complete block design with three replications. Each genotype was planted on 6 rows with 2.5 m length. Spacing between rows, plots, and replications were 0.2 m, 0.4 m, and 1.5 m, respectively. The gross and net harvestable plot area were 2.5m x 1.2m and 2.5m by 0.8 m respectively. Seed, Nitrogen+Phosphorus+Sulphur (NPS) and Urea fertilizers were used at rates of 100,100 and 50 kg ha-1, respectively. Planting was carried out from end of May to 2nd week of July in 2017 cropping season. All NPS and one third of urea was applied at planting while the remaining two third of urea was top dressed at tillering just after first weeding. Misganaw et al. Adaptation of Food Oat Genotypes 113 Table 3. Pedigree, origin and growth habit food oat genotypes for the study. Genotype Pedigree Origin Growth habit Chaps Ogle (Brave/unnamed_336)X Unnamed_5458(IL75- 5667/Ogle) Illinois Spring Florida501 Florad (Floriland Irradiated/Unknown) X Unnamed_6485(unnamed_6484/Unnamed_6483) - Florida Winter Gem (X6166-2) WI X6051 (MO 07468/unnamed_4882) X Ogle (Brave/unnamed_336) Wisconsin Spring Goslin OA952-3(OA797-7/02540-3-7-2) X 06196(Pc48/OA952-3) Ottawa Spring Horizon Ck92Ab719/Horizon314 Florida Winter Kangaroo Unnamed_15143(SV88123-104/WA84Q406) X SV86153_101(unnamed_11891/Unknown) Australia Winter Noble-2 Noble(Tippecanoe/unnamed_10546) X Noble(Tippecanoe/unnamed_10546) Minnesota Spring OA600-32 NA NA NA OA602-4 NA NA NA Pusa hybrid G Unknown India Unknown Souris(ND961161) ND90141(ND894904/ND852107) X ND900118(MN78142/ND852158) North Dakota Spring TAM 0-397 re-selection from TAMO- 386(TAMO-386/TAMO -386) X reselection from TAMO-386(TAMO-386/TAMO-386) Texas Winter UFRGS930605 Unknown Brazil Winter Local Ethiopian cultivar NA = Not available. 2.2. Data Collection and Statistical Analyses Data were collected on days to physiological maturity, plant height, panicle length, number of seeds per spike, thousand seed weight, straw yield, grain yield and disease severity and reaction of the varieties. Data on days to physiological maturity was collected at 75% of the harvestable plot area become physiologically mature. The agronomic traits, namely, plant height, panicle length, and number of seeds per panicle data were collected from randomly selected 5 plants per plot whereas straw yield and grain yield data were collected on the harvestable plot area per plot across environments. Thousand seed weight was measured from the randomly taken thousand seed in each plot counted by electronic seed counter. The oat rust diseases severity scoring was done based on Cobb modified scoring method (Peterson et al., 1948). The oat rust and scab diseases varietal reaction/response scoring was done based on Cobb modified scale (Stakman et al., 1962). Oat leaf blotch was scored based on modified version of Saari and Prescott’s scale of two digits scoring system (00-99: the 1st digit is appearance of disease on plant height whereas the 2nd digit represents the severity % of the disease) (Saari and Prescott, 1975). The data were analyzed using GenStat statistical software (17thedn). The AMMI analysis of variance summarizes most of the magnitude of genotype by environment interactions into one or a few interaction principal component axes (IPCA) (Crossa, 1990). Least significant difference (LSD) method (P<0.05) was used for mean separation among genotypes. 3. Results and Discussion 3.1. Analysis of Variance of Grain Yield and Yield Related Traits of Food Oat Genotypes The combined analysis of variance of varieties, environments and their interactions showed the presence of significant (P≤0.05) difference among varieties for days to maturity, plant height, panicle length, and number of seeds per panicle, thousand seed weight, straw dry biomass and grain yield (Table 4). The higher variation due to the main effect of varieties on panicle length was 71.08 % followed by plant height (57.05 %) and thousand seed weight (51.52 %) and whereas the higher variation expressed by environment main effect on straw dry biomass was 87.83% followed by number of seeds per panicle (70.39%) and grain yield (69.04) in food oat genotypes. The findings of this study were in line with as Atefah and Sohbat (2012) reported in oat genotypes. In addition, the variation accounted by the interaction of genotypes by environments on thousand seed weight was (39.39%) followed by straw dry biomass and grain yield were 24.86 % and 24.54%, respectively. According to Atefah and Sohbat (2012) and Mushtag et al. (2013) report, higher variations on grain yield and number of seeds per panicle response was accounted by environment main effects where as higher variations on plant height and thousand seed weight was accounted by genotype main effects and higher variations scored on straw yield due to the interaction of genotypes by environments. Misganaw et al. East African Journal of Sciences Volume 14 (2) 111-120 114 Table 4. The AMMI analysis of variances accounted by genotypes, environments and their interaction of food oat varieties across environments. Trait Gen SS Env SS G*E SS IPCA1 IPCA2 Error SS % SS Gen % SS Env % SS G*E DM 16470 160641 7125 3894** 1297** 2760 8.94 87.19 3.87 PH 108777 72261 9642 4649** 2125** 7992 57.05 37.89 5.06 PL 4872 1026 956 454** 234 ns 1629 71.08 14.97 13.95 NSPP 20553 92299 18258 13289** 2718 ns 13996 15.68 70.39 13.93 TSW 5724 1028 4359 3365** 433* 1814 51.52 9.25 39.23 SDM 18365 15546 11186 5605** 5134** 8667 40.83 34.31 24.86 GY 1436 15433 5485 1595** 1443** 3611 6.42 69.04 24.54 Note: DM = Days to physiological maturity; PH = plant height; PL = panicle length; NSPP = Number of seed per panicle; TSW = Thousand seed weight; SDM = Straw dry biomass; GY = Grain yield; ** = Significant at 0.01; Gen = Genotype; Env = Environments; Gen*Env = Genotype by environment interactions; IPCA = Interaction principal component axis; DF = Degree of freedom; SS = Sum squares; VR = Variance ratio and F Pr = F-Probability. 3.2. Performance of Grain Yield and Yield Related Traits of Food Oat Genotypes The performance of yield related traits of food oat genotypes are depicted in Table 5. The maturity time of food oat genotypes range was from 138.1 and 138.2 days for the genotypes Horizon and UFRGS930605, respectively and 164.2 days for the genotype kangaroo across environments. The plant height in oat genotypes varies 89.2 cm to 153.1 cm for the genotypes UFRGS930605 and OA602-4 respectively. The panicle length in oat genotypes varies 15.7 cm to 29.1 cm for UFRGS930605 and Chaps, respectively. The studies reported by Amanuel et al. (2019), Dawit and Mulusew (2017), Mushtag (2013), Yasemin (2012) and Nehvi et al.(2007) the analysis of variances showed significant differences in oat genotypes. Here, in the study, the performance of yield related traits were varied in oat genotypes as per the tested materials, environments and their interactions. As showed in Table 6, analysis of variances of grain yield performance showed significant (P<0.05) differences for genotypes, environments and their interactions. The combined grain yield performance range was 3904 to 3045 kg ha-1 in food oat genotypes. As Amanuel et al. (2019), Zeki et al. (2018), Dawit and Muluse (2017), Atefah and Sohbat (2012) and Yasemin (2012) and Nehvi et al. (2007) studies the grain yield performance was different in the oat genotypes across environments. As a result, the performance of grain yield and yield related traits of oat genotypes were significantly affected by the main genetic, environmental and interaction of genotype by environment effects. Table 5. The phenological and agronomic traits response of food oat genotypes across environments. Genotype Trait DM PH (cm) PL (cm) NSPP TSW (g) SDM (kg ha-1) Chaps(G1) 155.9 129.4 29.1 76.9 34.1 6620 Florida501(G2) 148.7 120.4 21.0 57.6 37.9 4900 Gem(G3) 156.8 122.0 18.7 58.4 35.5 6210 Goslin(G4) 150.3 127.5 23.3 79.9 38.7 5690 Horizon(G5) 138.1 103.1 20.6 58.0 32.2 3170 Kangaroo(G6) 164.2 126.9 23.0 51.8 40.2 4670 Local(G7) 156.9 146.7 27.8 78.4 33.5 5870 Noble-2(G8) 150.1 137.9 25.0 74.0 40.9 5190 OA600-32(G9) 153.4 149.6 27.7 76.5 39.4 6570 OA602-4(G10) 155.2 153.1 28.1 66.3 43.6 5300 PusaHybridG (G11) 147.0 117.9 20.5 60.1 29.6 4560 Souris(G12) 150.0 115.4 23.5 75.0 33.3 5250 TAM 0-397(G13) 145.7 103.8 23.7 55.1 36.3 4210 UFRGS930605(G14) 138.2 89.2 15.7 60.1 29.5 2810 Mean 150.8 124.5 23.4 66.3 36.0 5070 CV(%) 2.6 5.8 12.7 20.2 8.7 22.3 LSD(5%) 6.2 11.6 4.8 21.8 5.1 1840 Gen ** ** ** ** ** ** Env ** ** ** ** ** ** Gen*Env ** * ** ** ** ** Note: DM = Days to physiological maturity; PH = Plant height; PL = Panicle length; NSPP = Number of seed per panicle; TSW = Thousand seed weight; SDM = Straw dry biomass; ** = Significant at 0.01; Gen = Genotype; Env = Environments and Gen*Env = Genotype by environment interactions. Misganaw et al. Adaptation of Food Oat Genotypes 115 Table 6. The grain yield (kg ha-1) performance of the food oat genotypes across environments. Genotype Environment Mean grain yield Yield advantage over local (%) Adet Farta Sekela Banja Sekota Sinan Fajie Geregera Chaps 5101a 4935ab 4012abcd 2583abcd 3665abc 2551d 3132cd 2510abc 3565abcd 17.08 Florida501 4682ab 4082bcd 3386def 2644abcd 3684abc 4037a 4806a 2877a 3768ab 23.74 Gem 3625cd 4066bcd 3115f 2660abcd 3103cdef 2853cd 3551bcd 2275bc 3155de 3.61 Goslin 4142bcd 5075a 4064abcd 3026a 4134ab 4180a 3717bcd 2655ab 3865a 26.93 Horizon 4413ab 3929cd 4198abc 2900ab 4235a 3815ab 4913a 2831a 3904a 28.21 kangaroo 2906e 4232abcd 4487ab 2677abcd 2895cdef 3011bcd 3465bcd 2757ab 3307bcde 8.60 Local 4095bcd 3664d 3780bcdef 2420bcd 2795def 3717abc 1401e 2537abc 3045e – Noble-2 4191bc 4409abcd 4555a 2612abcd 3318cdef 3956a 4167ab 2774a 3748ab 23.09 OA600-32 4975a 4216abcd 3201ef 2162d 2527f 3531abc 2879d 2545abc 3255cde 6.90 OA602-4 4263bc 4664abc 3756bcdef 2991ab 3372bcde 4162a 3070d 2902a 3647abc 19.77 Push hybrid-G 4245bc 3579d 4032abcde 2206cd 2737ef 4228a 4115abc 2061c 3401bcde 11.69 Souris 4053bcd 3907cd 4403ab 2841ab 3290cdef 4011a 3656bcd 2615ab 3598abcd 18.16 TAM 0-397 4079bcd 4196abcd 3503cdef 2757abc 3567abcd 3768ab 3376bcd 2975a 3528abcde 15.86 UFRGS930605 3473de 4208abcd 3892abcde 2671abcd 2693ef 3361abcd 4362ab 2912a 3447bcde 13.20 Mean 4160 4230 3880 2650 3290 3660 3620 2660 3520 CV(%) 10.1 12.9 11.8 12.9 14.3 14.4 16.4 11.1 13.6 LSD(5%) 710 912 770 579 796 884 994 497 769 Misganaw et al. East African Journal of Sciences Volume 14 (2) 111-120 116 3.3. AMMI and GGE Biplot Analysis of Grain Yield of Oat Genotypes The oat genotypes Gem (G3), Local (G7), Pusa Hybrid G (G11) and OA602-4 (G10) of the grain yield performance were weakly influenced by environmental factors (lower interaction effects). The genotypes Kangaroo (G6), OA600-32 (G),Chaps (G1), Florida501 (G2), Goslin (G4), Horizon (G5), Noble-2 (G8), Souris (G12), TAM 0-397 (13) and UFRGS930605 (G14) of gain yield performance were strongly affected by environmental factors(higher interaction effects) as showed in Figure 1. However, the genotypes were less sensitive to environmental factors may not be higher in grain yield response. As Crossa (1990), Zobel et al. (1988) and Voltas (2002) reported that genotypes near the origin/center of the biplot are not sensitive to environmental interaction, whereas genotypes distant from the origin of the biplot are sensitive and have large interaction effects. In addition, according to Yan et al. (2000) ideal genotypes are those having large PC1 scores (wider in adaptable) and small absolute PC2 scores (high stability). In figure 1, the environments Adet and Fajie followed by Sekela were discriminated the genotypes grain yield performance than Farta, Banja, Sekota, Sinan and Geregera. As Akter et al. (2014) report environments with short spokes exert small interactive forces, whereas environments with long spokes exert strong interaction on the performance of oat genotypes. Among oat genotypes, Goslin (G4) was ideal which was nearest to the concentric circle of the biplot. In addition to G4, the genotypes G10, G5, G13, G8, G2, G1, G12 and G14 which were more adaptable and stable across the tested environments. While the genotypes G11, G9, G7, G3 and G6 were far from the concentric circle of biplot compared to the ideal genotype Goslin (Figure 2). The genotypes closest to the ideal genotype drawn on the center of concentric and/or average environmental coordinate (AEC) are highest yielder (Zerihun, 2011 and Yan et al., 2002). In the consideration of AMMI and GGE biplot analysis of oat genotype based on the grain yield performance, Genotypes G4, G5, G10, G2, G13, G8 and G12 showed higher interaction to the environmental factors and also higher in grain yielding than the remaining tested oat genotypes across the tested environments. Therefore, these genotypes are relatively wider in adaption across the tested environments. Figure 1. Graphics of AMMI biplot of grain yield of oat genotypes using symmetrical scaling of both genotypes and environments (E1=Adet,E2 = Farta, E3 = Sekela, E4 = Banja, E5 = Sekota, E6 = Sinan, E7 = Fajie, E8 = Geregera, G1 = Chaps, G2 = Florida501, G3 = Gem, G4 = Goslin, G5 = Horizon, G6 = Kangaroo, G7 = Local, G8 = Noble-2, G9 = OA600-32, G10 = OA602-4, G11 = Pusa Hybrid G, G12 = Souris, G13 = TAM 0-397, G14 = UFRGS930605, IPCA = Interaction principal component axis and AGY = Adjusted grain yield). Misganaw et al. Adaptation of Food Oat Genotypes 117 Figure 2. Graphics of GGE biplot of grain yield of oat genotypes using comparison biplot, genotype method and scaling (E1 = Adet, E2 = Farta, E3 = Sekela, E4 = Banja, E5 = Sekota, E6 = Sinan, E7 = Faji, E8 = Geregera, G1 = Chaps, G2 = Florida501, G3 = Gem, G4 = Goslin, G5 = Horizon, G6 = Kangaroo, G7 = Local, G8 = Noble-2, G9 = OA600-32, G10 = OA602-4, G11= Pusa Hybrid G, G12 = Souris, G13 = TAM 0-397, G14 = UFRGS930605, PC = Principal component and AEC = Average environmental coordinate). 3.3. Disease Severity and Reaction of Food Oat Genotypes The food oat diseases such as scald, net blotch and rust (stem and crown) were recorded according to Cob modified scoring method. The oat genotypic responses were resistant to scald and net blotch except Horizon (84) which is categorized under moderately resistant. The response of the genotypes to stem and crown rusts were varied in severity scores (0-90%) and their reaction. Among 14 tested oat genotypes G3, G4, G9, G10, G12, G13 and G14 were resistant to stem rust whereas G6 was moderately resistant and genotypesG1, G2, G5, G7, G8, and G11 were susceptible to stem rust. On the other hand, genotypes G1, G2, G3, G4, G5, G6, G8, G12 and G14 were resistant to crown rust while genotypes G7, G9, G10, G11 and G13 were susceptible to crown rust (Table 7). The studies illustrated that oat rusts, blotch and scald could cause economical yield losses when the oat genotypes are susceptible to oat diseases (Paul, 2019 and Bowen et al., 2016). Misganaw et al. East African Journal of Sciences Volume 14 (2) 111-120 118 Table 7. Diseases severity and reactions of food oat genotypes. Genotype Disease severity and reaction Scald (1-5) Net blotch (00-99) CR SR Chaps(G1) 1 R R 60S Florida501(G2) 1 R R 90S Gem(G3) 1 R R TrR Goslin(G4) 1 82 R R Horizon(G5) 1 84 R R Kangaroo(G6) 1 R R 10MR Local(G7) 1 R 85S 80S Noble-2(G8) 1 R R 60S OA600-32(G9) 1 R 20MR TrR OA602-4(G10) 1 31 85S R PusaHybrid G (G11) 1 R 80S 80S Souris(G12) 1 R TrR R TAM 0-397(G13) 1 R 40MS TrR UFRGS930605(G14) 1 R R R Note: LR = Stem rust; CR = Crown rust; TrR = Trace and Resistant; MS = Moderately susceptible; MR = Moderately resistant; R = Resistant and S = Susceptible. 4. Conclusion The analysis of variance showed significant (P<0.05) differences for grain yield and yield related traits in genotypes, environments and their interactions. The performance of grain yield and yield related traits of food oat genotypes were significantly affected by the main genetic, environmental and genotype by environment interaction effects. The source of variation for grain yield in food oat genotypes accounted by environments, genotype by environment interactions and genotypes were accounts 69.04%, 24.54% and 6.42%, respectively. Among 13 introduced food oat genotypes, Goslin and Souris were wider in adaptation, higher in grain yield and resistant to crown and stem rust which showed 26.93% and 18.16% grain yield advantage over local variety across tested environments. In the study the genotypes Horizon, Florida501, OA602-4 and Naval-2 showed no significant difference with Souris in grain yield performance, however susceptible to crown and stem rusts. Therefore, oat genotypes Goslin and Souris should be demonstrated and scaled out in soil acidity problem areas of Banja, Fajie, Farta, Geregera, Sekela and Sinan districts and in areas with similar agro- ecologies of Ethiopia. 5. Acknowledgements The authors acknowledge Adet Agricultural Research Center, Amhara Agricultural Research Institute and Dr. Higgns project based in Ethiopian Sustainable Food Project for the financial aid as well as technical support. The acknowledgment is also extended to all who actively participated in the research work from the beginning to the end. 6. References Akter, A., Hassen, J.M., Kulsum, U.M., Islam, M.R., Hossain, K. and Rahman, M.M. 2014. AMMI biplot analysis for stability of grain yield in hybrid rice (Oryza sativa L.). Journal of Rice Research, 2(2): 1– 4. Amanuel Wada, Kassa Shawle and Deribe Gemiyo. 2019. Biomass yield and nutritional quality of different oat genotypes (Avena sativa) grown under irrigation condition in Sodo Zuriya District, Wolaita Zone, Ethiopia. Agricultural Research and Technology, 20(4): 197–204. Atefah Zaheri and Sohbat Bahraminejad. 2012. Assessment of drought tolerance in oat (Avenasativa) genotypes. Annals of Biological Research, 3 (5): 2194–2201. Bowen, K.L., Hagen, A.K., Pegues, M. and Jones, J. 2016. Yield losses due to crown rust in winter oat in Alabama. Plant Health Research, 17(2): 95–100. Butler-Stoney, T.R. and Valentine, J. 1991. Exploitation of the genetic potential of oats for use in feed and human nutrition. Home-Grown Cereals Authority, London, UK. Pp. 45–56. Crossa, J. 1990. Statistical analysis of multi-location trials. Advances in Agronomy, 44: 55–85. Dawit Abate and Mulusew Fikere. 2017. Performance of fodder oat (Avena sativa L.) genotypes for yield and yield attributes in the Highland of Bale. Journal of Biology, Agriculture and Healthcare, 7(19): 29–33. Doehlert, D.C., McMullen M.S. and Hammond J.J. 2001. Genotypic and environmental effects on grain yield and quality of oat grown in North Dakota. Crop Science, 41: 1066–1072. FAOSTAT. 2018. FAOSTAT-Crops/GHDx. www.fao.org/faostat/en/#data/QC. Accessed on October, 2019). Foy, C.D. and Murray, J.J. 1998. Developing aluminium- tolerant strains of tall fescue for acid soils. Journal of Plant Nutrition, 21(13): 1–25. Hoffmann, L.A. 1995. World production and use of oats. Pp. 34–61. In: Welch, R.W. (ed.). The Oat http://www.fao.org/faostat/en/#data/QC Misganaw et al. Adaptation of Food Oat Genotypes 119 Crop-Production and Utilization. Chapman and Hall, London. Kochian, L., Piñeros, M. and Hoekenga, O. 2005. The physiology, genetics and molecular biology of plant aluminum resistance and toxicity. Plant and Soil, 274: 175–95. Lange, C.J. 2012. Reaction of North American oats (Avena sativa L.) to crown rust. MSc Thesis, Texas A and M University, United states. Mushtag, A., Gul, Z., Razvi, S.M., Mir, S.D. and Rather, M.A. 2013. Stability properties of certain oats (Avena sativa.L) genotypes for major grain yielding characteristics. International Journal of Plant Breeding and Genetics, 7(3): 182–187. Nava, I.C., Carla, A.D., Ismael, T.L.D., Marcelo, T.P. and Luiz, C.F. 2006. Inheritance of aluminum tolerance and its effects on grain yield and grain quality inoats (Avena sativa L.). Euphytica, 148: 353– 58. DOI:10.1007/s10681-005-9048-5. Nehvi, F.A., Wani, S.A., Hussain, A., Maghdoom, M.I., Allai, B.A., Yousuf, W., et al. 2007. Stability analysis for yield and yield related traits in fodder oat (Avena sativa L). Asian Journal of Plant Science, 6(4): 628–632. Paul, M.N. 2019. Cereal disease laboratory, Agricultural research service. https://www.ars.usda.gov/midwestarea/stpaul/c ereal-disease-lab/docs/cerealrusts/oat-crown- rust/. Accessed on 6 October 2019. Peterson, R.F., Campbell, A.B. and Hannah, A.E. 1948. A diagrammatic scale for estimating rust intensity on leaves and stems of cereals. Canadian Journal of Research, 26: 496–500. Radmer, L., Tesfaye, M., Somers, D.A., Temple, S.J., Vance, C.P. and Samac, D.A. 2012. Aluminum resistance mechanisms in oat (Avena sativa L.). Plant Soil, 351: 121–34. DOI 10.1007/s11104-011- 0937-1. Saari, E.E. and Prescott, L.M.A. 1975. Scale for appraising the foliar intensity of wheat diseases. Plant Disease Report, 59: 377–380. Stakman, E.C., Stewart, D.M. and Loegering, W.Q. 1962. Identification of physiologic races of Puccinia graminis var. tritici. Agricultural Service, United States Department of Agriculture. Pp. 1–54. Voltas, J., Van, E.F., Igartua, E., García del Moral, L. F.,Molina-Cano, J.L. and Romagosa, I. 2002. Genotype by environment interaction and adaptation in barley breeding: Basic concepts and methods of analysis. Pp. 205–241. In: Slafer, G.A., Molina-Cano, J.L., Savin, R., Araus, J.L. and Romagosa, I. (eds.). Barley Science: Recent Advances from Molecular Biology to Agronomy of Yield and Quality. The Harworth Press Inc., New York. Yan, W., Hunt, L.A., Sheng, Q. and Szlavnics, Z. 2000. Cultivar evaluation and mega-environment investigation based on the GGE biplot. Crop Science, 40: 597–605. Yan, W. and Rajcan, I. 2002. Biplot analysis of test sites and trait relations of soybean in Ontario. Crop Science, 42: 11–20. Yasemin, H., Rukiye, K. and Tevrican, D. 2012. Evaluation of oat (Avena sativa L.) genotypes for grain yield and physiological traits. Agriculture, 99(1): 55–60. Zerihun, J. 2011. GGE-biplot Analysis of Multi- environment Yield Trials of Barley (Hordeium vulgare L.) Genotypes in Southeastern Ethiopia Highlands. International Journal of Plant Breeding and Genetics, 5(1): 59–75. Zobel, R.W., Wright, M.J and Gauch, H.G. 1988. Statistical analysis of a yield trial. Agronomy Journal, 80: 388–393. Misganaw et al. East African Journal of Sciences Volume 14 (2) 111-120 120