Evaluation of Food Barley Genotypes for Grain Yield and Agronomic Traits in the Central Highlands of Ethiopia

The present study was undertaken to evaluate the performance of promising food barley genotypes for grain yield and yield related traits. The trial was conducted in 2017 and 2018 main cropping season using randomized complete block design with three replications. Variance analysis and GGE biplot were used to understand the nature of genotype × environment interaction (G × E) in a grain yield data collected from eighteen barley genotypes grown in eight environments (Location and year combinations). The combined analysis of variance (ANOVA) showed significantly higher genotype, environment and genotype by environment interaction effects for all the traits studied. Accordingly, genotypes EH1493 X HB1307 (G10) and HB 1307 X ND25160 (G2) showed the highest mean grain yield of 4558 kg ha -1 and 4499 kgha -1 , respectively. GGE biplot showed that G10 was the winner genotype at BK18, DB18 and HO18 environments and it has good grain yield stability across the testing environments. Therefore, G10 is a potential candidate variety to be included in the variety verification trial for possible release.


INTRODUCTION
Barley (Hordeum vulgare L) is an important stable food crop and has high potential in narrowing food deficit and enables to achieve food security in Ethiopia. It sustains a livelihood of millions of people residing on the highlands and fetches a substantial income for farmers. It is widely grown in diverse rain-fed agro-ecological zones of Ethiopia at an altitude of 1400 to over 3600 m.a.s.l. The crop is more diversified and prominent in areas between 2300 to 3400 m.a.s.l (Zemede, 2002). Food barley is commonly cultivated in stressed areas where soil erosion, soil acidity, occasional drought or frost limits the choice of other crops. It is cultivated in different production systems, namely; early, late, Belg and residual moisture (Yirga et al, 1998).
Barley is the fifth important cereal crops after maize, tef, wheat and sorghum. It is produced on about 1 million hectares of land from which 2.0 million tons of grain are produced annually (CSA, 2018). The productivity of barley in Ethiopia is low (2.1 t/ha) as compared to world average of 3.1 t/ha. The low productivity is mainly attributed to abiotic stresses (soil acidity, frost, water logging, low moisture and low soil fertility) and biotic stresses (diseases, pests and weeds).
In general, barley remains an important crop in the Ethiopian agriculture because of its role in providing food for the rapidly growing population (3.0 % per year). Therefore, there is a need to focus on barley improvement and developing alternative varieties to the different production systems and agro ecologies. Variety development effort is a dynamic process as one breeding program is required to provide a large option of varieties for diverse environmental conditions. Moreover, available varieties become obsolete due to break down of disease resistance and poor performance. Hence, it is crucial to provide new improved varieties that could go with the improved production packages identified on a continuous basis. Increasing the productivity of food barley is very important for the resource poor smallholder farmers in Ethiopia to improve the output and income to satisfy the local food demand of the rapidly growing population.
The National Barley Research program at Holetta and Kulumsa in collaboration with D/Berhane regional research center has conducted a multi-location variety trial, including lines developed from local collections, introductions and local crosses with the main objective of identifying stable and superior varieties to be released for production and use in the future breeding.

MATERIALS AND METHODS
A total of eighteen food barley genotypes including three check varieties were evaluated using completely randomized block design with three replications. The experiment was executed at Holetta, Jeldu, Debrebirhan, Bekoji and Kofole during the main cropping season in 2017 and 2018 under rain-fed conditions. Descriptions of the testing sites are described in Table 1. The materials were evaluated for eight quantitative traits at eight locations across years ( Table 2). The traits studied were days to heading (days), days to maturity (days), plant height (cm), thousand kernel weight (gm), hectoliter weight (Kg hl -1 ), grain yield (Kg ha -1 ), scald and net blotch disease severity (%). A plot size of 1.2 m by 2.5 m was used to lay the experiment and the spacing between blocks and plots within blocks were 1.5 m and 0.4m, respectively. Analysis of variance (ANOVA) was carried out using R software to determine the effect of genotype, environment and their interaction on various traits of the food barley genotypes. Linear mixed effect model (lmer) of package lme4 was used for data analysis and the environments were considered as random and genotypes as fixed effects (R Core Team, 2017). The following ANOVA models have been used to test the performance of genotypes at each and combined locations, respectively (Singh and Ceccarelli 1996). Y ij = µ + G i +B j + e ij and Y ijk = µ + G i +E j + GE ij +Bk (j) + e ijk .
Where, Y ij = observed value of genotype i in block j, Y ijk = observed value of genotype i in block k of environment j, µ = grand mean of the experiment, G i = the effect of genotype i, B j = the effect of block j, Bk (j) = the effect of block k in environment j, e ij = error effect of genotype i in block j , E j = environment effect, GE ij = the interaction effect of genotype i with environment j, e ijk = error (residual) effect of genotype i in block k of environment j. In addition GGE bi-plots were performed to determine stability of the tested food barley genotypes using GGEBiplotGUI package of R-software (R Core Team, 2017). Local check

RESULTS AND DISCUSSION
Combined analysis of variance showed that genotype, environment and the genotype x environment interaction had a highly significant effect on all the traits studied (Table 3). The significant genotype effect showed the existence of significant variability among the tested genotypes. Highly significant genotype x environment interaction effect observed in this trial showed the tested genotypes performed differently across the testing environments for the traits. Therefore, researches involved in the barley improvement program should have to see the adaptability of genotypes to different test environments. Similarly, significant difference among the testing environments also observed. In the present study all traits showed the higher contribution of the environmental component to the total sums of squares and similar results were reported by Abtew et al., (2015). DF=degree of freedom, DHE=days to heading, DMA= days to maturity, PLH=plant height, SC=scaled, NB=net blotch, TKW= thousand kernel weight, HLW= hectoliter weight, GYLD= grain yield, **, * Significant at 5% and 1% probability level, ns=non significant, §these traits were not recorded at DB18 and JL18 mean squares under those traits are angular transformed values Based on the average data over eight environments, G10 (4558 kg ha-1 ) and G2 (4499 kg ha-1 ) scored the highest mean grain yield, though not significantly different from the recently released standard check varieties (HB1965 andHB 1966). Accordingly, G10 and G2 had 9.75 and 8.33% grain yield advantage over the highest yielding check variety (HB 1966) (Table 4). The highest mean hectoliter weight (HLW) and thousand kernel weight (TKW) values was scored by G7. The two high grain yielding genotypes (G10 and G2) also had higher HLW and moderate TKW values. Regarding disease related traits most test genotypes showed moderate tolerance to scald and net blotch disease. The check variety HB 1965 and 1966 scored 21.2 and 26.7% severity for scald and 33.3% and 32.8% severity for net blotch. Similarly, the candidate genotypes G10 and G2 also showed moderate scald (36.2, 29.0%) and net blotch (39.0, 37.2%) resistance, respectively. The ranges of plant height values of 106-115 cm were recorded with the lower end corresponding check variety HB 1965 while the upper end corresponds to the local check variety, this longer plant height is in agreement with the inherent nature of most local varieties. Furthermore, the phenological traits showed lower variability with, five and seven days differences in mean days to heading and maturity respectively (Table 4). Based on agronomic and grain physical quality traits (HLW and TKW), G10 is the top ranking genotype. Thus, G10 and the other two promising varieties, namely G2 and G7 can be used for future breeding program as donor parents.

CONCLUSION
In the present study, the eighteen food barley genotypes showed significant genetic, environmental and genotype by environment interaction effects for all traits considered in the experiment. Genotypes, G10 and G2 showed the highest mean grain yield potential at all environments. These genotypes showed moderately resistant to scald and net blotch, and acceptable TKW and HLW values. Based on "Mean vs stability" view of GGE biplot, G10 was the highest yielding and stable genotype. While G2 was the second highest yielding genotypes but it is relatively unstable. Similarly "Which won where" pattern of GGE biplot confirmed that G10 gave consistently highest mean grain yield across the test environments and G2 specifically adapted to HO18 environment. Therefore, based on mean performance and stability, G10 is the best potential variety identified for possible variety verification trial ISSN 2224-7181 (Paper) ISSN 2225-062X (Online) Vol.84, 2020 8 for the mega and other similar environments. In addition, G10 and the other two Genotypes, G2 and G7 will be included in the food barley crossing program as potential parents for their good yield potential and physical grain quality traits.