Performance of bread wheat genotypes under different environment in lowland irrigated areas of Afar Region , Ethiopia

Wheat is an important staple food for Ethiopian people, and its straw has been used as sources of feed for animals. Nine wheat genotypes introduced from International Center for Agricultural Research in the Dry Areas (ICARDA) were evaluated at Werer Agricultural Research Center from 2010/2011 to 2013/2014, at Gewane from 2011/2012 to 2012/2013 and at Waidulale in 2013/2014 cropping seasons using randomized complete block design (RCBD) in three replications with the objective of identifying wide adaptable and high yielding bread wheat varieties. The combined analysis of variance (ANOVA) showed that the effects of year (Y) and locations (L) were highly significant for all parameters studied. The combined ANOVA of grain yield (GY) revealed highly significant (P<0.01) G x Y interactions effects for almost all traits. The environment (E) effect accounted for 67.8% of total sum of squares (TSS) followed by the Genotype by Environment Interaction (GEI), which accounted for 8.2% and G (3.6%). The highest yielding genotypes selected from the National Variety trial (NVT) were Moontiji-3 (3488 kg/ha), Doukkala4 (3258 kg/ha) and Saamid-3 (3158.00 kg/ha) with the maturity date of 82.2, 89.5 and 84.2 days, respectively. Generally, the yields of the three candidate varieties were higher and stable over years and across locations.


INTRODUCTION
Wheat is one of the main agricultural commodities in the world.Today, it is growing on more land area than any other commercial crops and it provides 19% of human total available calories (FAOSTAT, 2014).Similarly, it is one of the most important cereal crops cultivated in a wide range of agro-ecologies of the world including Ethiopia.
Ethiopia is the second wheat producers in Sub-Sahara Africa next to South Africa; mainly by small scale farmers in mid and high altitude rainfed areas.Bread wheat is *Corresponding author.E-mail: mihratuamnuel@gmail.com.
Author(s) agree that this article remain permanently open access under the terms of the Creative Commons Attribution License 4.0 International License predominantly grown by small-scale farmers under rainfed condition in the highlands of Ethiopia (Bishaw and Alemu, 2017).The dominant Ethiopian small scale cereal crops agriculture mainly for consumption and income generation requires great attention in developing productive technology across different agro-ecologies like arid and semi-arid agro-pastorals areas (Seyoum et al., 2012).
The country breeding objectives are to develop varieties with high and stable grain yield and quality, and resistant to biotic and abiotic stresses.Ethiopia's diverse agro-ecology requires a very extensive and costly testing system to identify a large number of target varieties for the different environments (Bishaw and Alemu, 2017).It is an important staple food for Ethiopian people and the straw has been used as sources of feed.Whole grains as part of the diet is recommended for health reasons because they are good source of minerals, fibers, protein, and antioxidants and also wheat bran is a good source of minerals and fibers, and can be used to supplement bread (Heshe et al., 2016).
However, the productivity and annual production of rainfed wheat does not satisfy the wheat demands of the population, as a result the country is forced to import wheat grain from abroad with high foreign currencies as low productivity stemmed from various biotic and abiotic stresses and soil factors (Akbarzai et al., 2017).But, the country has 12 river basins in the lowland areas with total areas of nearly 4 million cultivable and irrigable lands (MoARD, 2010).
However, the major production constraints in irrigated lowland areas of Ethiopia are high temperature, soil PH and salinity.Thus, development of well-adaptable and stable wheat varieties along with their production packages should be the major task for wheat breeders and agronomists to exploit the huge untouched resources through irrigated wheat production.The research works by Werer Agricultural Research Center (WARC) at various environments of Afar, Oromiya and Amhara Regions since 2011 clearly showed that the yield of wheat genotypes could reach up to 5700 kg/ha (WARC unpublished data) indicating the suitability of the lowland irrigated areas of Ethiopia for wheat production.
Currently, the government has given due attention for irrigated agriculture with the purpose of attaining food security and earning foreign currencies by exporting agricultural products to abroad.This has created a good opportunity for development of stable and well adapted wheat varieties along with their production technologies for irrigated lowland areas of Ethiopia.Currently, the government of Ethiopia encourages cotton producer and sugarcane enterprises to incorporate wheat as one of the major crop to be produced on wide areas immediately after cotton harvesting and the second choice of development work in addition to sugarcane production.Evaluation of wheat genotypes at a number of test environments data can identify their yield performance  Naser et al. (2012) quoting Gauch (2006) stated that in addition to yield performance, the yield stability of bread wheat cultivars can be determined in order to make specific selections and recommendations to farmers.Similarly, Naser et al. (2012) quoting Ramagosa and Fox (1993) pointed out genotype x environment interaction aids to determine an optimum breeding strategy to improve specific or general adaptation strategy, which is related to the expression of yield stability under a limited or wide range of environments.Therefore, the objective of this paper is to present the results of the study on yield and yield stability of bread wheat genotypes evaluated under irrigation in different environments (Figure 1).

MATERIALS AND METHODS
Nine wheat genotypes introduced from ICARDA were evaluated at Werer Research Center from 2010/11 to 2013/14, at Gewane from 2011/12 to 2012/13, and at Waidulale (Amibera) in 2013/14 cropping seasons (Figure 2).Gewane is located latitudes 10° 10'N and 40° 32'E longitude at altitude of 626 m.a.s.l. and 400 mm annual RF with maximum and minimum temperature of 44°C and 17°C.Werer/Amibara is located latitudes 9° 16'N and 40° 09' E longitude in north Eastern part of Ethiopia at altitude of 740 m.a.s.l. with climatic data from 1970 to 2014 on average maximum, and minimum temperature in the region is 34 and 19°C respectively.
The average rainfall is irratic with 571 mm annually with crop production based on irrigation water from Awash River.The soil is predominantly Vertisol with dominant soil type being sand clay loam.The design is randomized complete block design (RCBD) in three replications with the plot size of (9m 2 ) 3 m length and 0.3 m between rows.The trial was sown every year around first week of November using hand drilling at a seed rate of 80 kg/ha, and diammonium phosphate (DAP) fertilizer was applied at the rate of 50 kg/ha whole at sowing time at all locations followed by irrigation water.On the other hand, UREA fertilizer was applied at all locations in split at the rate of 100 kg/ha (half at tillering and the remaining half at booting stages).It was applied in both times after irrigating the trials around 5:00 pm to minimize the loss of N due to leaching and volatilization, respectively.The trial was irrigated every ten days until the genotypes reached their physiological maturity which is 7 to 8 number of irrigation in furrow method.The trial was weeded three to four times using hand weeding and no herbicides were used.Data were collected before harvest from inner 8 rows on phenotypic parameters such as days to heading, days to maturity, plant height, spike length, total tillers and effective tillers.
Then after, each genotype was harvested manually using sickles and data on number of spikelets per spike, and number of seeds per spike was taken.The harvested genotypes from each plot were threshed and cleaned to determine 1000 kernel weight and grain yield per plot using sensitive balance.The collected data both from field and laboratory were subjected to statistical analysis using SAS 9 th edition software to conduct combined ANOVA.
Stability analysis of Additive main effect and multiplicative interact ion (AMMI) model: was used to determine the magnitudes of the main and interaction effects.The Genotype by Environment Interaction was partition into two principal components axis (IPCA1 and IPCA2).Stable genotypes across locations and over years were identified by analyzing the contributions of the variations into total sums of squares.Genotypes ranking was done using AMMI stability values (ASV) with the following formula proposed by Purchase (1997) (Figure 2): Where: IPCA1 -interaction principal component analysis axis1; IPCA2 -interaction principal component analysis axis 2

RESULTS AND DISCUSSIONS
The combined ANOVA is presented in Table 1.Combined Amanuel et al. 929 ANOVA indicated that the effect of year (Y) was significantly high (P <0.01) for all parameters studied except for number of spikelets per spike.Likewise, the effect of location was significantly high (P <0.01) for all parameters studied.The results of combined analysis of genotypes showed highly significant (P <0.01) differences among the genotypes for all parameters studied except total tillers/hill and numbers of spikelets/spike.Friedrich et al. (2017), Abdulkerim et al. (2016) and Mehari et al. (2015) found grain yield to be highly influenced by environment and genotype.Highly significant (p<0.01)G × Y interaction effects were observed for DM, PH, SL and GY but non-significant for the rests of the parameters (Table 1).
Moreover, highly significant (P<0.01)L x G interaction effects were observed for DM, SL and GY and significant (P<0.05) for NKPS but non-significant for the rest of the traits studied.The environment (E) and GEI effects accounted for 67.8 and 8.2% of total sum of squares (TSS), respectively (Mehari et al., 2015;Abdulkerim et al., 2015).
The results also showed that there were crossover interactions.The stability analysis showed that among the genotypes, Moontiji-3, Doukkala-4 and Saamid-3 were high yielder and stable over locations and years (Tables 1 and 2).Genetic resources have played a significant role in wheat improvement and will continue to do so, with the genetic variation affecting future improvements increase of wheat's yield potential (Skovmand et al., 2001).
The combined analysis of variances showed highly significant differences (P<0.01) for DH, DM, PH, ET, SL, NKPS, TKW and GY.The result clearly indicated the existence of sufficient genetic variability for most traits among the genotypes studied.The mean values of the genotypes ranged from 47 to 65 days for DH, 81 to 92 days for DM, 63.9 to 74.4 cm for PH, 5.6 to 6.7 for NTT, 5.4 to 6.6 for NET, 6.5 to 8.1 cm for SL, 13.3 to 14.5 for NSPS, 29 to 37.9 for NKPS, 29.4 to 36.3 g for TKW and 2323.00 to 3488.00 kg for GY (Table 2).The highest yielding genotypes were Moontiji-3 (3488.00kg/ha), Doukkala-4 (3258.00kg/ha) and Saamid-3 (3158.00kg/ha) with the maturity date of 82.2, 89.5 and 84.2 days, respectively.
In general, Moontiji-3 is an early maturing type, taller in plant height and possessed higher seed number per spike (Table 2) similar to that of Akbarzai et al. (2017) (Figures 3 and 4).The results of this study showed that the performances of genotypes evaluated were significantly influenced by the test environments (years and locations), which proved the presence of wide variations among the test environments where the genotypes were evaluated.The environmental effect accounted for 67.8% of total sum of squares (TSS) indicating the importance of testing the wheat genotypes across the different locations and over years similar to   the report of Friedrich et al. (2017) and Mehari et al. (2015), environmental effects caused 76% of the total variation for grain yield.Generally, the environmental effects relative to G effect higher in the present study may make the selection process more complex.This result agreed with the finding of Karimizadeh et al. (2012) and Hinsta et al. (2011).The GE accounted for 8.2% showing that the genotypes responded differently to the test environments (Table 3).The higher GE interaction effect (8.2%) relative to the G effect (3.6%) indicated that the genotypes exhibited both additive and crossover type of interaction.
Similar findings were reported by Ezatollah et al. (2012), Naheif (2013), Mehari et al. (2015) and Naser et al. (2012).This implies that multi-location trials are important to identify and select high yielding and stable varieties for wide as well as specific environments.The most important component is the genotypic and total variance by genotypic variation, and environmental variation (year, location and year by location) influences performance of evaluated genotypes (Friedrich et al., 2017).
The stability analysis over locations showed that among the genotypes studied, Moontiji-3, Doukkala-4 and Saamid-3 were high yielder and stable.Moontiji-3 is the second most adaptable and the most stable variety in addition to its highest yielding potential.Similarly, the second highest yielding variety, Doukkala-4 got the third and fourth promising adaptability across locations and stability over the years, respectively (Figures 3 and 4).This result was in line with the findings reported by Ezatollah et al. (2012) andNaheif (2013).These results revealed the possibility of selecting wide adaptable wheat varieties for all locations among the genotypes suitable for wide environments.
Generally, the results of this study showed that Monntiji-3 was the most adaptable varieties across locations and over the years.The results of stability analysis over the years showed that among the materials studied, Moontiji-3 was the most stable variety followed   by the standard check (Ga'ambo) and Doukala-4 (Figure 2).These may be due to less variation of major weather factors such as mean temperature, relative humidity, evapo-transpiration and soil temperature of the growing season over years (WARC weather unpublished data).
The combined ANOVA over years, across locations and among genotypes of the experiment showed highly significant differences for all the traits except number of spikelets/spike.The most traits indicated the presence of sufficient genetic variability among the tested materials and environmental variations.The highest overall mean yield was recorded from genotypes such as Moontiji-3 (3488 kg/ha), Doukkala-4 (3258 kg/ha) and Sammid-3(3158 kg/ha) with the mean maturity date of 82.2, 89.5 and 84.2 days, respectively.

CONCLUSIONS AND RECOMMENDATION
The results of the present study showed that the yield and yield stability of the genotypes evaluated were significantly affected by the test environments (years and locations).The higher environmental effect (67.8% of TSS) clearly showed that the genotypes were much more influenced by the environmental factors (soil type, soil fertility and temperatures, etc.).The effects of L x G interactions varied significantly showing that there was high genetic variability among the wheat genotypes studied.Thus, the results obtained from the present study necessitate wheat breeders to evaluate more and more genotypes across locations, and also for identifying and selecting wide as well as stable adaptable wheat varieties possessing the required grain yield and quality parameters.

Figure 2 .
Figure 2. Location map of the study area DH = Days to heading, DM = Days to maturity, PH = Plant height, SL = Spike length, NTT = Total tillers, NET = Effective tillers, NSPS = Number of Spikeletes per Spike, NKPS = Number of seeds per spike, TKW = Thousand kernel weight and GY = Grain yield.

Table 1 .
Combined ANOVA over years and location from 2011 to 2014.

Table 2 .
Mean performance of the genotypes under different location (2011 to 2014).

Table 3 .
AMMI analysis for tested genotypes over environments.