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, Volume: 16( 1) DOI: 10.37532/0974-7435.2020.16(1).200

Yield Potential and Stability of Irrigated Spring Bread Wheat Genotypes in Central Rift Valley of Ethiopia

Mihratu Amanuel Kitil
Ethiopian Institute of Agricultural Research, Werer Agricultural Research Center, Ethiopia

Received: December 10, 2019; Accepted: February 03, 2020; Published: February 17, 2020

Citation: Kitil MA, Sarbessa TB, Biru HM , et al. Yield Potential and Stability of Irrigated Spring Bread Wheat Genotypes in Central Rift Valley of Ethiopia. Biotechnol Ind J. 2020;16(1):200.


The available potential resources under arid and semi-arid lowland irrigated areas of the Ethiopia could be more exploited by irrigated wheat technology generation on progresses and production to fill the gap of national wheat demand. Bread whet genotypes evaluated in different locations of Amibara district in Afar Region and Fentale district of Oromia Region for three consecutive years 2015/16-2017/18 were considered in study. The 25 bread wheat genotypes were evaluated in triple lattice with three replications on 9m2 plot area. The study were targeted to identify and select high yielding potential and stable candidate varieties for release and also further breeding purposes. The analysis of variances of bread wheat genotypes evaluated revealed highly significant difference (P≤0.01) among genotypes for all traits and the genotypes by environment interactions. The overall mean performance of genotypes evaluated across different environments the two genotypes (HEILO//MILAN/MUNIA/3/KIRITATI/2*TRCH) 3877 kg/ha and (MUU/FRNC LN//FRANCO LIN #1) with 3655 kg/ha were better out yielded with 12% and 5% than check respectively. The third promising genotype (GLADIUS/2* BAVIS) is most stable genotype and it is better in early maturing (12%), 2nd best plant height (13%) next to MUU/FRNCLN// FRANCOLIN #1, and it has the maximum thousand kernel weight (8%) and related quality traits comparing to check. The out yielded genotypes and performed well in their important traits were selected as candidate varieties and submitted for variety releasing committee and out of which the HEILO//MILAN/MUNIA/3/KIRITATI/2*TRCH and GLADIUS/2*BAVIS were officially released. Therefore from the current results it has been observed better yield potential than the check variety and showing stability among the studied genotypes and this could be exploited in future large scale seed production and breeding purposes.


Environment; Genotypes; Stability; Yield


Wheat is one of the major cereals grown for use as food and industrial raw materials in Ethiopia. It is an important staple food in the diets of many Ethiopians, providing an estimated 12% of the daily per capita caloric intake for the country’s over 90 million population [1]. It is the important staple crop in Ethiopia and ranked 4th in the area (13.38%) and grain production (15.17%) of total grain crops which has resulted in an increase in production mainly by smallholder farmers using rain-fed based production system [2]. Ethiopia is still importing about 1.6 ml tons of wheat which estimated to 25% in deficit to fulfill domestic wheat demand by foreign currency [3]. Several Bread wheat (Triticum aestivum L.) varieties have been released for rain fed production targeted for different midland and highland area agro-ecologies. Although there is a potential for irrigated wheat production in the lowlands, the capacity to produce at a commercial scale is at its very initial stage in the country. Main wheat production constraints are biotic and abiotic stresses across rain-fed and irrigated environments which accentuated by the increasing incidence of climate change heat and drought [4]. So the climate change effect abiotic and biotic stress tolerant high yielding variety development is vital in continuous as per Tadesse et al., [4]. Irrigated Lowland area wheat production has limitations in the high yielding and stability of released wheat varieties and their seed system. It is very important to increase the irrigated lowland wheat varieties as a choice for variety development as well as for production and also for irrigable areas with better seed supply. The Irrigated wheat Research and development works done in the last decade achieved better in continuous variety development and pre-scaling up which utilized by policymakers and get attention for irrigated wheat production and diversification in lowland areas of Ethiopia. The progress and promising irrigated wheat Research results to be sustainable in technology generation to supply the required varieties and related packages to feed the irrigated wheat development works and diversification throughout the Ethiopian lowland areas. The high yielding and stable varieties are very crucial to attain the required production gain. Hence, evaluation of the extent and performance of available high yielding genotypes present under lowland areas are essential for effective crop production in an extensive way for local consumption. Thus, the aim of the study is to identify high yielding and stable genotypes in different environments for various development works then to release and access related merits for further breeding activities.

Materials and Methods

1. Experimental material, sites, and Agronomic practice

The experiments were conducted in Awash River basins at Amibara district Werer Agricultural Research Centre (WARC) under the Ethiopian Institute of Agricultural Research (EIAR). The WARC is located at 740 m a.s.l (9º16’8”N, 40º09’41” É). In Oromia regional state the trials were done at Saru-weeba Fentale district. The 25 bread wheat Genotypes in a triple lattice with three replications were planted under irrigated lowland area on 3 m × 3 m=9 m2 plot area. The trials were planted at the relatively cool season of the middle awash from mid-October to November per consecutive years.

The fertilizers (UREA=100N Kg/ha, DAP=50 P2O5 kg/ha) were applied based on previous practice in the irrigable areas. UREA Fertilizer application was on split basis; 1/2 at 25-30 days after planting and 1/2 at booting stage and DAP applied all at planting. All experimental plots irrigated uniformly using furrow irrigation methods in 10 days interval until the wheat crop reached physiological maturity. Other management practices performed as per previous recommendations. Data were recorded for Days to 50% heading, Days to 75% Maturity, Spike length, Spikelet number per spike, Plant height (cm), Number of kernel per spike, Thousand kernel weight (g) and Grain yield (kg ha-1).

2. Statistical analysis of data

The recorded all yield components and average yield across locations data was subjected to Analysis of Variance (ANOVA) and Varieties by environment interaction (GGE) biplot analysis using appropriate software GenStat statistical package18th Edition [5]. A comparison of treatment means was done using Fischer’s Least Significant Difference (LSD) test at 5% probability levels. The combined analysis of variance was carried out to estimate the effects of the environment (E), Genotypes (G) and Genotype by Environment interaction.

Results and Discussion

1. Analysis of variance

The Analysis of variances across the location from 25 bread wheat genotypes evaluated revealed that highly significant (p ≤ 0.01) difference among genotypes for all traits and the genotypes by environment interaction was a highly significant difference (p ≤ 0.01) for all traits (TABLE 1). This indicated that the measured traits of bread wheat genotypes were highly influenced by environmental factors. Significant genotype ‘X’ environment interaction found for all traits studied would mean that evaluation of bread wheat genotype on several environments would give a more accurate estimate of different traits. These results agreed with the study that indicated that bread wheat genotypes responded deferentially to environments with significant genotype ‘X’ environment interaction [6].

Source of Variation Mean square of Traits
G 24 114** 72.4** 125** 8*** 16*** 174** 1551795** 133**
G × En 125 30** 107** 366** 3.1** 4.7** 83** 1258917** 27**
Residual 200 8 15 34 2.1 3.2 31 753892 15

TABLE 1. Analysis of Variance (ANOVA) of irrigated wheat genotypes.

2. Mean performance of genotypes

The mean performance of yield in specific environments (year and location) were described in TABLE 2 that clearly showing the performance genotypes across environments. The two candidates HEILO//MILAN/MUNIA/3/KIRITATI/2*TRCH and MUU/FRNCLN//FRANCOLIN #1 were among the superior genotypes almost in all environments and similarly the third candidate GLADIUS/2*BAVIS is average yielder in addition to its extra earliness except for the first environment (TABLES 2 and 3). The combined mean performance of the evaluated genotypes different traits across different environment were illustrated in TABLE 3. From all the genotypes evaluated in different environments the two genotypes (HEILO//MILAN/MUNIA/3/KIRITATI/2*TRCH) with a mean yield of 3877 kg/ha followed by (MUU/FRNCLN//FRANCOLIN #1) the second most genotype with 3655 kg/ha mean performance out yielded by 12% and 5% than the standard check respectively. The third promising genotype (GLADIUS/2*BAVIS) is characterized by its extra early maturing (12%), it is second-best in plant height (13%) next to MUU/FRNCLN//FRANCOLIN #1, the best in its thousand kernel weight (8%) and related quality traits mean performance than check (TABLE 3). For the yield-related traits, spike length and number of spikelets per spike BAJ #1/KIS KADEE#1 and PFAU/MILAN/5/CHEN/AEGILOPSSQUARROSA(TAUS)//BCN/3/VEE#7/BOW/4/PAST OR/6/2*BAVIS#1 genotypes have the best mean performance followed by HEILO//MILAN/MU NIA/3/KIRITATI/2*TRCH (TABLE 3). The high yielding genotypes and their promising yield-related traits help to use them in large scale production and also further breeding similar to the findings of Punia SS [7]. In addition to high yielding, genotypes that are characterized by an early maturity could be promising because these adaptation mechanisms are associated with an escape strategy for stress conditions. These studies were very important in arid areas with respect to the existing stresses for a different purpose which is supported by M. Afzal Arain et al. results [8].

S. No. Genotypes 2015-16 Werer 2015-16 Fentale 2015-16 WARC 2015-16 FWCF 2015-16
2016-17 WARC 2017-18 WARC Mean Yield
1 KIRITATI//HUW234+LR34/PRINIA/3/BAJ #1 3161 2503 3797 3067 3718 2596 2549 3064
2 BAJ #1/KISKADEE #1 2893 2708 3713 2951 2787 3605 2926 3145
3 QUAIU//2*BRBT1*2/KIRITATI 2984 1991 3545 2642 3839 2584 3020 2929
4 ND643/2*WBLL1//2*KACHU 2896 2382 3908 2230 4542 3783 3155 3243
5 BAVIS//ATTILA*2/PBW65 3691 2045 3849 2107 3972 4312 3088 3331
6 BAJ #1/KISKADEE #1 2824 2646 3385 3804 4153 3640 3056 3287
7 GLADIUS/2*BAVIS 1424 3088 3272 3286 3527 3003 2813 2706
8 Gaambo 3318 2395 4143 3777 3161 4066 3117 3469
9 HEILO//MILAN/MUNIA/3/KIRITATI/2*TRCH 3958 3168 3812 4512 4089 4526 3297 3877
10 WHEAR/VIVITSI//WHEAR/3/FRNCLN 2844 3087 4328 3377 2788 3594 3020 3329
11 MUU/FRNCLN//FRANCOLIN #1 2716 3274 4574 4072 4062 3651 3217 3655
12 DANPHE #1//ND643/2*WBLL1/3/DANPHE 2146 2263 4082 2723 3334 3419 2517 2916
13 PFAU/MILAN/5/CHEN/AEGILOPS SQUARROSA (TAUS)//BCN/3/VEE#7/BOW/4/PASTOR/6/2*BAVIS #1 2735 3469 4408 3160 2133 2896 3325 3222
14 BAVIS/4/MILAN/KAUZ//DHARWAR DRY/3/BAV92 1888 3300 4095 3112 4828 4113 3043 3455
15 MUTUS//ND643/2*WBLL1 1810 2736 4357 1871 3677 3129 3113 3039
16 KIRITATI//HUW234+LR34/PRINIA/3/FRANCOLIN #1 2516 1739 3611 2646 3589 3644 3540 2952
17 VEE/MJI//2*TUI/3/PASTOR/4/BERKUT/5/BAVIS 1692 2866 3318 3125 4369 4486 3209 3233
18 WHEAR/KUKUNA/3/C80.1/3*BATAVIA//2*WBLL1/5/PRL/2*PASTOR/4/CHOIX/STAR/3/HE1/3*CNO79//2*SERI 2186 3194 2287 3377 1420 3946 2740 2876
19 DANPHE #1*2/CHYAK 2879 2973 3478 3684 2036 3945 3169 3280
20 MINO/898.97/4/PFAU/SERI.1B//AMAD/3/KRONSTAD F2004 2783 2716 2500 2912 2143 3547 2605 2838
21 WHEAR/KUKUNA/3/C80.1/3*BATAVIA//2*WBLL1*2/4/ND643/2*WBLL1 2995 2233 2818 2826 1626 3506 2707 2751
22 TACUPETO F2001*2/BRAMBLING//KIRITATI/2*TRCH 2664 2771 3081 1838 2358 3541 2995 2849
23 PRL/2*PASTOR//WHEAR/SOKOLL 2275 1696 2571 1963 3461 3657 3045 2600
24 DANPHE #1*2/CHYAK 3223 2894 3114 2359 3722 3866 3286 3205
25 W15.92/4/PASTOR//HXL7573/2*BAU/3/WBLL1/5/MUU 3116 2434 3543 1704 4553 3798 3285 3181
Mean 2705 2656 3584 2748 3485 3634 3029 3137
CV% 30.6 27 26 29.25 25.06 17.3 19.4 32.7
LSD 1368 1471 1563 43.33 1922 1163 1191 673

TABLE 2. Mean performance of yield (kg/ha) of wheat trial in lowland irrigated areas over different environments.

Trt Genotypes DH DAM PLH SL NSPS NKPS Yld_kg/ha TKW
1 KIRITATI//HUW234+LR34/PRINIA/3/BAJ #1 53b-e 85bc 72abc 8fgh 14c-f 36d-g 3064b-e 35d-j
2 BAJ #1/KISKADEE #1 54cde 86c 75abc 10a 16ab 37d-g 3145b-e 38bcd
3 QUAIU//2*BRBT1*2/KIRITATI 53b-e 84bc 77bc 9a-d 15abc 43b-g 2929cde 35d-i
4 ND643/2*WBLL1//2*KACHU 53b-e 85bc 72abc 8.1d-g 15abc 37d-g 3243a-e 30m
5 BAVIS//ATTILA*2/PBW65 54cde 86c 73abc 8.1d-g 13.3fg 34fg 3331a-d 34f-k
6 BAJ #1/KISKADEE #1 54cde 86c 72abc 9.4ab 14c-f 34fg 3287a-d 31lm
7 GLADIUS/2*BAVIS 41a 76a 69ab 7h 12g 32g 2706de 42a
8 Gaambo 55de 86c 79c 9.3abc 16ab 38d-g 3469abc 39bc
54cde 86c 76abc 9.4ab 16ab 41c-g 3877a 40ab
  10   WHEAR/VIVITSI//WHEAR/3/FRNCLN 54cde 87c 72abc 8.7a-f   15abc 39c-g 3329a-d 35d-i
11 MUU/FRNCLN//FRANCOLIN #1 53bcd 86c 68a 8.2d-g 14c-f 34fg 3655ab 37b-f
12 DANPHE #1//ND643/2*WBLL1/3/DANPHE 54cde 85bc 79c 8.4b-g 14.7b-e 38d-g 2916cde 35d-i
13 PFAU/MILAN/5/CHEN/AEGILOPS SQUARROSA (TAUS)//bcN/3/VEE#7/BOW/4/PASTOR/6/2*BAVIS #1 52bcd 87c 75abc 8.1d-g 16.2a 39c-g 3222a-e 36ch
14 BAVIS/4/MILAN/KAUZ//DHARWAR DRY/3/BAV92 52bcd 85bc 75abc 8.8a-e 14c-f 35efg 3455abc 35d-i
15 MUTUS//ND643/2*WBLL1 52bcd 85bc 71abc 8.4b-g 14.8bcd 36d-g 3039b-e 34f-k
16 KIRITATI//HUW234+LR34/PRINIA/3/FRANCOLIN #1 54cde 85bc 70ab 8.3d-g 14c-f 37d-g 2952cde 33i-m
17 VEE/MJI//2*TUI/3/PASTOR/4/BERKUT/5/BAVIS 51bc 85bc 73abc 7.7fgh 13.7def 35efg 3233a-e 36b-g
18 WHEAR/KUKUNA/3/C80.1/3*BATAVIA//2*WBLL1/5/PRL/2*PAST OR/4/CHOIX/STAR/3/HE1/3*CNO79//2*SERI 52bcd 85bc 72abc 7.6gh 13.5ef 47a-d 2876cde 33i-m
19 DANPHE #1*2/CHYAK 52bcd 84bc 72abc 8.09efg 14.8bcd 55ab 3280a-e 34e-j
20 MINO/898.97/4/PFAU/SERI.1B//AMAD/3/KRONSTAD F2004 53bcd 87c 73abc 7.6fgh 13.97c-f 51abc 2838cde 32j-m
21 WHEAR/KUKUNA/3/C80.1/3*BATAVIA//2*WBLL1*2/4/ND643/2 *WBLL1 51b 84bc 73abc 8.09efg 14.5b-f 46b-e 2751de 34g-l
22 TACUPETO F2001*2/BRAMBLING//KIRITATI/2*TRCH 56e 86c 73abc 8.2d-g 14.3c-f 44b-f 2849cde 37b-e
23 PRL/2*PASTOR//WHEAR/SOKOLL 52bcd 85bc 71abc 7.5gh 14.2c-f 50abc 2600e 31klm
24 DANPHE #1*2/CHYAK 51b 81ab 71abc 8.3c-g 16ab 59a 3205a-e 33h-m
25 W15.92/4/PASTOR//HXL7573/2*BAU/3/WBLL1/5/MUU 53 86bc 74abc 7.7fgh 14c-f 54ab 3181b-e 36d-i
Mean 53 85 73 8 15 41 3137 35
CV 7.3 8.3 17.5 19.3 13.7 44.6 32.7 13
LSD 2.8 5.1 8.4 1.04 1.3 12 673.3 3

TABLE 3. Combined analysis of bread wheat genotypes mean performance across different locations (Amibara district at Afar region and Fentale district at Oromia region) 2015-16 to 2018-19.

3. GGbiplot analysis

The GGbiplot analysis showed that overall performance of the Genotypes across different environments (locations/years) and cumulative mean performance as per Anputhas et al. [9] and Yan W et al. [10]. Genotypes assigned on treatment 9 (HEILO//MILAN/MUNIA/3/KIRIT ATI/2*TRCH) and 11 (MUU/FRNCLN//FRAN COLIN #1) out yielded in overall mean and more stable on environments except for environment-5. Early maturing Genotype assigned on treatment 7 (GLADIUS/2*BAVIS) is the most stable genotype in its yield on overall environments (FIG. 1).


FIG. 1. GGbiplot analysis of the genotypes across different locations and years.


The variability among genotypes for different traits was well recognized and stability of promising genotypes in yield also well discriminated. Based on the study results three candidate varieties for yield potential and different agronomic merits were identified. Generally, the outperformed candidate varieties were potential yielder across all the six environments exception to the fifth environment and the best stable, early maturing and superior quality. The two candidate varieties; HEILO//MILAN/MUNIA/3/KIRITATI/2*TRCH and GLADIUS/2*BAVIS were officially released for production under irrigated lowland agro-ecology. The out yielded genotypes were promising in their most traits that could be utilized for further breeding purposes. More locations and area-based better package utilization could express more the potential which requires attention in future to broaden the study.


We sincerely acknowledge EIAR, WARC, National wheat Research Program for technical and managerial supports, CIMMYT and AGP-II projects for their Germplasm, Technical and financial supports.

Conflict of Interest

The authors declare that they have no conflict of interest.


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