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† Corresponding author 
© 2015 Conscientia Beam. All Rights Reserved. 

GENOTYPE X ENVIRONMENT INTERACTION AND STABILITY ANALYSIS 

FOR YIELD AND YIELD RELATED TRAITS OF DESI-TYPE CHICKPEA 

(CICER ARIETINUM L.) IN ETHIOPIA 

 

Getachew Tilahun1† --- Firew Mekbib2 --- Asnake Fikre3 --- Million Eshete4 
1Amhara Regional Agricultural Research Institute, Gonder Agricultural Research Center, Ethiopia 

2Plant Science Department, Haramaya University, Dire Dawa, Ethiopia 

3Crop research Director, EIAR, Addis Ababa, Ethiopia. 

4Ethiopian Institute of Agriculture Research, Debre Zeit Agriculture Research Center, Ethiopia 

    

ABSTRACT 

Chickpea is the major pulses grown in Ethiopia, mainly by subsistence farmers usually under rain-fed 

conditions. However, its production is constrained due to genotype instability, environmental variability and 

interaction of genotype with environment. This research was carried out to examine the magnitude of 

environmental effect on yield of chickpea genotypes and to investigate the stability and adaptability of the 

genotypes under different agro-ecological conditions. 17 genotypes each of were evaluated in RCBD with 

four replications in five environments. Various stability indices were used to assess stability and genotype by 

environment performances. The combined ANOVA for yield and yield related traits revealed highly 

significant (P≤0.01) differences for genotypes, environments and their interaction. The significant 

interaction showed that the genotypes respond differently across the various environments. At Akaki, Chefe 

Donsa, Debre Zeit, Dembia and Haramaya the top performing genotype were DZ-2012-CK-0040 (2229 

kg/ha), DZ-2012-CK-0027 (3966 kg/ha), DZ-2012-CK-0040 (4060 kg/ha), DZ-2012-CK-0032 

(1394 kg/ha) and Natoli (3247 kg/ha) respectively. The first two PCs explained 84.3% of the variance of 

original variables for the genotypes. There were remarkable inconsistencies with the univariate stability 

parameters to select stable genotypes. However, multivariate approach, the AMMI model was better for 

partitioning the G x E into the causes of variation. Based on ASV value, DZ-2012-CK-0035 was most 

stable genotype. As per AMMI biplot, Minjar and local variety were the most widely adapted genotypes. 

Dembia and Haramaya are the most discriminative environments. Environments Debre Zeit and Chefe 

Donsa were the favorable environment. Genotypes, DZ-2012-CK-0040, DZ-2012-CK-0036 and DZ-

2012-CK-0040, DZ-2012-CK-0032 and variety Natoli were recommended as specifically adapted to sites 

Akaki, Chefe Donsa, Debre Zeit, Dembia and Haramaya respectively.  

Keywords: AMMI, ASV, Clustering, Desi-type, Phonologic traits, Multivariate, Univariate statistics. 

Current Research in Agricultural Sciences 
2015 Vol. 2, No. 3, pp. 100-113 
ISSN(e): 2312-6418 
ISSN(p): 2313-3716 
DOI: 10.18488/journal.68/2015.2.3/68.3.100.113 
© 2015 Conscientia Beam. All Rights Reserved. 

 
 
 
 
 
 

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101 
© 2015 Conscientia Beam. All Rights Reserved. 

1. INTRODUCTION 

Chickpea is the third leading legume grain in the world and in Ethiopia as well. Its range of 

cultivation extends from the Mediterranean basin to the Indian sub-continent and south ward of 

Ethiopia and eastern Africa highlands [1]. About 92% of the area and 89% of production of the 

grain are concentrated in the semi-arid tropical countries [1]. In Ethiopia, it accounts for about 

one third of the area and production of pulses following faba bean(Vicia faba L.) and haricot bean 

(Phaseolus vulgaris L.) [2]. 

Desi-type chickpeas (Cicer arietinum L.) with colored and thick seed coat with small and 

angular in shape having an average 1-2 seeds per pod. The plants are short with small leaflets and 

purplish flowers, and contain anthocyanin. Desi-type chickpea seeds germinate at an optimum 

temperature (28-33°C) and moisture level 10 % in about 5-6 days [3]. The flowers are generally 

pink and the plants show various degrees of anthocyanin pigmentation. The Desi-types account 

for 80-85% of chickpea global production area [3]. The crop grows mainly concentrated in two 

into major administrative regional stats namely Amhara and Oromiya and it accounts 94% the 

total production in the country with altitude range of 1400-2300 masl, and annual rainfall of 700-

2000 mm [4]. 

Environmental factors such as soil moisture, sowing time, fertility, and temperature and day 

length have strong influence during various stages of plant growth [5]. The environment is 

changing day-by-day and this implies that it is necessary to evaluate crop genotypes at different 

environments to assess their performances. The performance of a genotype is not always the same 

in different environments as it is influenced by environmental factors. To assess yield stability 

among varieties, multi-location trials with appropriate stability analysis method is required. In 

Ethiopia, there is no sufficient information on the genotype by environment interaction effects on 

yield and yield related traits. Therefore the current research was undertaken To examine the 

magnitude of environmental effect on yield and yield related traits of Desi-type chickpea 

genotypes,to study the nature and extent of G x E Interaction on seed yield of Desi -chickpea 

genotypes and to investigate the stability and adaptability of the varieties under different agro-

ecological condition. 

 

2. MATERIALS AND METHODS 

The experiment was conducted during the 2012/13 main cropping season at five 

environments representing various chickpea agro-ecologies of Ethiopia. The sites were Akaki, 

Chefe Donsa Debre Zeit, Dembia and Haramaya. Fourteen pipelines and three released Desi-type 

chickpea genotypes were included in the study. The plant materials were obtained from Debre 

Zeit Agricultural Research Center. Planting of the genotypes was done in early mid August up to 

first week of September using Randomized Complete Block Design (RCBD) with four replications 

at each site under rain fed conditions. Each genotype was planted in six rows of 4 m row length 

and at 1.2 m width. A spacing of 30 cm between rows and 10 cm between plants were used on a 

plot size of 4.8 m2. Fertilizer was not applied. Weeding and other management practice were done 

as required for each site. Data were recorded on days to 50% flowering, 90% physiological 



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maturity, plant height, the number of pods per plant, the number of seeds per plant, the number of 

seeds per pod, 100-seed weight, biomass yield, grain yield, and harvest index. Data were 

computed by using SAS 9.1.3 for analysis of variance, Genstat13th for biplot graph and 

Agrobase20 for stability analysis. 

 
Table-1. Some characteristic features of the test sites 

 
 Source: Debre Zeit Agricultural Research Center (2012) 

 

Table-2.List of Desi-type chickpea genotypes included in the experiment 

Entry no Entry name Entry no Entry name Entry no Entry name 

1 DZ-2012-CK-0027 8 DZ-2012-CK-0027 15 Natoli  

2 DZ-2012-CK-0027 9 DZ-2012-CK-0027 16 Minjar  
3 DZ-2012-CK-0027 10 DZ-2012-CK-0027 17 Local check 
4 DZ-2012-CK-0027 11 DZ-2012-CK-0027   
5 DZ-2012-CK-0027 12 DZ-2012-CK-0027   
6 DZ-2012-CK-0027 13 DZ-2012-CK-0027   
7 DZ-2012-CK-0027 14 DZ-2012-CK-0027   

 

3. RESULTS AND DISCUSSION 

The combined analysis of variance revealed significant (P≤0.01) differences for environments, 

genotypes and genotype by environment interaction in desi-type chickpea genotype. Except seed 

per pod, the variations were significant for all the characters studied viz. days to flowering, days 

to maturity, grain yield, number pod per plant, plant height, 100 seed weight , above ground dry 

biomass yield and harvest index when tested against pooled error variance. 

Yield and its components are poly genic traits and are strongly influenced by environment in 

chickpea. Highly significant variation was observed for grain yield in desi-type chickpea 

genotypes (Table 3). The mean squares due to G X E interactions were also highly significant 

exhibiting the differential response of genotype in various environments. Similar results were 

obtained by Khan, et al. [6], Khan, et al. [7] and Bains, et al. [8] in chickpea. 

Bartlett’s test showed that homogenous error variance for the grain yields these allowing 

proceeding further for pooled analysis of variance across environments. Indicating differences in 

environments and the presence of genetic variability among genotypes. The highly significant 

difference among the genotypes showed that they may carry genes with different additive effects. 

Variations for genotypes performances across environments were also reported by Malik, et al. 

[9],  Bozoglu and Gulumser [10]. 

 



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Table-3. Mean sum of squares of yield and other traits from combined ANOVA of 17 desi type chickpea genotypes grown 

across five environments 

 

 

Table 4. Mean grain yield (kg/ha) 17 Desi-type chickpea genotypes grown at five environments 

Genotype Akaki Chefe 
Donsa 

Debre 
Zeit 

Dembia Haramaya Mean 
yield 

DZ-2012-CK-0027 2073 3966 2908 939 2273 2053 
DZ-2012-CK-0028 1304 2374 2958 823 1710 1620 
DZ-2012-CK-0029 1540 3575 2741 836 1523 1636 
DZ-2012-CK-0030 1444 3488 3031 970 2028 1783 
DZ-2012-CK-0031 1596 3501 3569 667 1502 1792 

DZ-2012-CK-0032 1483 3446 2810 1394 1147 1663 
DZ-2012-CK-0033 1785 2943 3398 745 1208 1784 
DZ-2012-CK-0034 1556 3641 3208 833 1870 1805 
DZ-2012-CK-0035 1556 2928 2997 667 1655 1686 
DZ-2012-CK-0036 1821 3237 3717 1183 1991 2106 

DZ-2012-CK-0037 1367 3150 3408 1117 1424 1737 
DZ-2012-CK-0038 1693 3245 3367 766 1352 1774 
DZ-2012-CK0039 1793 3347 3415 771 1538 1861 
DZ-2012-CK-0040 2229 3622 4060 956 1641 2223 

Natoli (SC) 1703 3655 3485 743 3247 2176 
Minjar (SC) 1367 2945 3876 1010 1756 1875 

Local check 1796 2837 2366 1329 1033 1664 
Means 1653 3288 3250. 928. 1670 1838 
CV(%) 16 11 12 20 20 16 

LSD (5%) 91 123 133 64 115 45 

 

The environment’s mean yield varied from 928 to 3288 kg/ha (Table 4). Maximum mean 

grain yield was obtained from Chefe Donsa and Debre Zeit; while, the minimum was from 

Dembia. Genotypes means across the environments indicated that the maximum mean grain yield 

was obtained from DZ-2012-CK-0039 (2223 kg/ha) while Natoli (2176 kg/ha) was ranked second 

and DZ-2012-CK-0036 (2106 kg/ha) third and the minimum from genotype DZ-2012-CK-0028 

(1620 kg/ha). Genotypes DZ-2012-CK-0040 (2229 kg/ha), DZ-2012-CK-0027 (2073 kg/ha) and 

DZ-2012-CK-0036 (1821kg/ha) were ranked first, second and third at environment Akaki based 

on mean grain yield. At Chefe Donsa genotype DZ-2012-CK-0027 (3966 kg/ha), Natoli (3655 

kg/ha) and DZ-2012-CK-0034 (3641kg/ha) ranked first, second and third respectively. At Debre 

Zeit genotype DZ-2012-CK-0040 (4060 kg/ha), Minjar (3876 kg/ha) DZ-2012-CK-0036 (3717 

kg/ha) performed first, second and third respectively. At Dembia genotype DZ-2012-CK-

0032(1394 kg/ha), local variety (1329 kg/ha) and DZ-2012-CK-0036 (1183 kg/ha) ranked first, 

second and third respectively. At Dembia, the performances of the genotypes were generally poor 

as compared to Akaki, Chefe Donsa, Debre Zeit, and Haramaya, because at Dembia there was 



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moisture stress during planting and vegetative stage. At Haramaya genotypes Natoli (3247 

kg/ha) DZ-2012-CK-0040 (2273) and DZ-2012-CK-0030 (2028 kg/ha) were found first, second 

and third respectively. The majority of the genotypes were best performing at Debre Zeit. G X E 

interaction causes differences in yield rank of genotype in different environments hence it is 

important for chickpea breeders to enhance selection efficiency and development of specifically 

adapted genotypes for different environments. 

 

3.1. Performance of Desi-Type Chickpea Genotypes for Yield Related Traits 

The mean square values due to genotypes, environments and genotype by environment 

interactions from the combined ANOVA were highly significantly for the traits: days to 

flowering, days to maturity, plant height, pods per plant, hundred seed weight, above ground dry 

biomass and harvest index. However, all of these were not significant for number of seeds per pod. 

Days to flowering and maturity (days): Days to flowering and to maturity were 

significantly affected not only by genotypes but also G X E interaction, reflecting genetic 

variability in experimental material as well as differential response across environments (Table 3). 

Averaged over all genotype, early flowering and maturity were observed at Debre Zeit (42 

and 102 respectively) and late flowering and maturity occurred at Akaki (52 and 130 days 

respectively) (Table 5). The probable reason is due to high temperature and early cessation of rain 

at Debre Zeit and, relatively long rain season and low temperature at Akaki. In all research sites, 

mean value of days to flowering and days to maturity ranged from 42 days (Debre Zeit) to 52 

days (Dembia) and 102 days (Debre Zeit) to 130 days (Haramaya), respectively (Table 6). 

Number of pods per plant: Number of pods per plant is an important selection criterion for 

the development of high yielding genotypes and it is strongly influenced by environment in 

chickpea [9]. Marked variation for number of pods per plant was observed in the performance of 

genotypes over the five environments (Table 3) and this indicated sensitiveness of number of pods 

for environmental variations. The highest mean number of pods per plant was recorded by 

genotypes local variety (57) followed by DZ-2012-CK-0036 (52) and DZ-2012-CK-0035 (42) 

(Table 5). Number of pods per plant was highest at Haramaya (50) and lowest at Akaki (31) 

(Table 6).The highest pod per plant was as result of extended vegetative and reproductive growth 

stages. These results are consistent with the findings of  Malik, et al. [9] in Kabuli type 

chickpeas.  

Plant height: Significant effects were observed not only for genotypes but also for genotype 

environment interaction, reflecting genetic variability in experimental material as well as 

differences in genotype performances over location the (Table 3). The relative performance of 

genotypes for plant height was markedly inconsistent over the environments which is in line with 

finding of Malik, et al. [9] and Iliadis [11] in chickpea who found high magnitude of G X E 

interaction. Plant height was highest at Debre Zeit (40 cm) and lowest at Akaki (30 cm) (Table 

5).the shortest was DZ-2012-ck-0036 (32 cm) and the longest was DZ-2012-ck-0031 (39 cm) 

(Table 6).  



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100-grain weight: Statistically, highly significant variance was observed for genotypes, 

genotype and environment (Table 3). In addition, the relative performance of the genotypes was 

quite inconsistent across the environments. Significant pooled deviation for 100-grain weight 

suggested that these genotypes differ considerably with respect to their suitability for this trait. 

The results obtained are in conformity with the findings of  Singh and Singh [12] in chickpea and 

Sanghi and Kandalkar [13] in fodder cow pea. Hundred seed weight was highest at Akaki (25 g) 

and lowest at Chefe Donsa (22 g) (Table 5). Hundred seed weight varied from 13 g for farmers or 

local variety to 31 g for DZ-2012-CK-0031 (Table 6). 

Above ground dry biomass. Statistically, highly significant variance was observed for 

genotypes, environments and G X E interaction (Table 3). Averaged over all genotypes above 

ground dry biomass was highest at Debre Zeit (1469 g) and lowest at Akaki (765 g) (Table 5).On 

the other hand, where averaged over all environments above ground dry biomass ranged from 

920 g for local check and 1320 g for Natoli (Table 6).  

Harvest index. Statistically, highly significant variance was observed for genotype and 

genotypes, environments and G X E interaction (Table 3). Over all genotypes harvest index was 

highest at Chefe Donsa (57%) and least at Dembia (28%) (Table 5). Pooled over all environments, 

harvest index ranged from 41.1% for DZ-2012-ck-0028 to 49.5% for DZ-2012-CK-0036 (Table 6). 

High harvest index is very important for increasing yield potential in crops because it is sensitive 

to environmental variations. However, a high vegetative growth is not always a symptom for 

high chickpea yield. 

 

3.2. Stability Analysis 

3.2.1. Wricke’s Ecovalence Analysis 

Wricke [14]; Wricke [15] defined the concept of ecovalence as the contribution of each genotype 

to the GEI sum of squares. 

Genotypes with the lowest eco valence contributed the least to the G X E interaction and are 

therefore, more stable. Accordingly, DZ-2012-CK-0035, DZ-2012-CK-0034, DZ-2012-CK-0036, 

DZ-2012-CK-0028, DZ-2012-CK-0039, DZ-2012-CK-0029 and DZ-2012-CK-0038 were the most 

stable genotypes. In that order these ranked 13th, 7th, 3th, 17th, 6th, 16th, and 11th for grain yield. 

Whereas  most unstable genotypes were Natoli, DZ-2012-CK-0032, DZ-2012-CK-0040, DZ-

2012-CK-0027, DZ-2012-CK-0037, DZ-2012-CK-0030, DZ-2012-CK-0033, DZ-2012-CK-0031, 

Minjar and the local variety. These ranked 2nd 15th, 1st, 4th, 12th, 10th, 9th, 8th, 5th and 14th for grain 

yield, respectively.  

The results indicated that high yielders have higher ecovalence and vice versa, and because of 

this genotypes recommendation for general adaptability would be difficult (Table 7). According to 

Asrat, et al. [16] genotypes with high ecovalence mean and large estimated value are suitable for 

high input environments. 

 

 

 



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Table-5.Mean values yield related traits of desi-type chickpea genotype tested at five environments in Ethiopia 

Environment  DF DM PPP SPP PHT HSW BM HI YLD 

Akaki 52 130 31 1.05 30.2 25.3 765.4 52.9 1653.3 
Chefe Donsa 48 129 38 1.04 35.9 22.1 1408 57 3287.9 
Debre Zeit  42 102 49 1.01 40.1 24.6 1469.1 53.3 3250 
Dembia  52 109 38 1.01 37.2 22.7 1329.4 28 928.3 
Haramaya  43 130 50 1.01 35.8 24 886.7 47.1 1699.5 

Means  50 121 40 1.08 34.7 24.4 1043.2 44.9 1837.7 
CV (%) 3.8 1.8 15.5 1.02 7.8 8.8 15.4 11.6 16.1 
SE± 0.30 0.69 0.74 0.01 0.28 0.27 22.2 0.79 11.60 
LSD (5%) 1.16 1.26 3.85 0.06 1.67 1.34 100.4 3.24 44.5 

 

Where: YLD= grain yield, DF= days to flower, DM=days to mature, PPP= pod per plant, SPP=seed per pod, PHT=plant height, BM= 
biomass yield, HI= harvest index, HSW= hundred seed weight 

 
Table-6. Means for yield related traits of 17 Desi-type chickpea genotypes grown at five environments 

Genotype DF DM PPP SPP PHT HSW BM HI 

DZ-2012-CK-0027 48 122 38 1 36 29 1145 44 

DZ-2012-CK-0028 58 119 38 1 36 21 975 41 
DZ-2012-CK-0029 50 113 40 1 37 27 950 45 

DZ-2012-CK-0030 46 122 29 1 35 29 970 47 
DZ-2012-CK-0031 50 120 35 1 39 31 1030 45 
DZ-2012-CK-0032 47 115 35 1 33 24 960 48 
DZ-2012-CK-0033 50 122 40 1 35 23 1010 42 
DZ-2012-CK-0034 46 120 33 1 32 28 1170 43 

DZ-2012-CK-0035 49 120 41 1 33 22 945 43 
DZ-2012-CK-0036 48 124 52 1 32 23 1015 50 
DZ-2012-CK-0037 51 122 42 1 35 22 1095 46 
DZ-2012-CK-0038 46 121 41 1 34 24 1060 45 
DZ-2012-CK0039 48 118 40 1 35 24 1030 45 
DZ-2012-CK-0040 49 124 41 1 34 27 1170 46 

Natoli (SC) 54 123 36 1 35 28 1320 42 
Minjar (SC) 48 119 38 1 35 20 970 47 
Local check 47 118 57 2 34 13 920 46 
Means 50 121 40 1 35 24 1043 45 
CV (%) 4 2 16 10 8 9 15 12 

SE± 0.3 0.7 0.7 0.01 0.3 0.3 22 1 
LSD 1 1 4 0.1 2 1 100 3 

 

Where: YLD= grain yield, DF= days to flower, DM= days to mature, PPP= pod per plant, SPP= seed per pod, PHT=plant height, 
BM= biomass yield, HI= harvest index, HSW=hundred seed weight; SC=standard Check. 

 

3.3.2. Eberhart-Russell’s Joint Regression Stability Analysis 

Eberhart and Russell [17] joint regression model for stability of some agronomical and 

physiological data provide the estimate of the desired stability parameters. 

The GE (linear) interaction was not significant, indicating that the stability parameter ‘bi’ 

estimated by linear response to change in environment was the same for all genotypes or 

genotypes have the same slope (Table 8). This confirms that GE was not a linear function of 

environments indices. The variations among the genotypes and for G X E interactions were 

significant. It means that genotypes exhibited different performance in different environments, 

which is due to their different genetic makeup or the variation due to the environments or both. 



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Mean sum of squares due to pooled deviation from regression was significant (P≤0.01) for grain 

yield indicating the importance of the non- linear GE.  

 

Table-7. Wrickes ecovalence value for 17 desi-type chickpea genotypes at five environments 

             Wi =wrickes ecovalence, SC= standared check 

 
Table-8. Analysis of variance for linear regressions of desi-type chickpea genotypes means on 
environmental index according to Eberhart and Russell’s joint regression model 

Source of variation Df  SS  MS  

Total  339 3437279  
Genotype  16 166591 10412* 
Env + in Gen + Env 68 3270687 48098 

Env. in linear 1 2859358 2859358** 
Gen x Env.(linear) 16 140037 8752 
Pooled deviation 34 271293 5319** 
Residual  240 445758 1748 

 

*, ** -significant at P ≤0.05 and 0.01; Grand mean = 441.04; R-squared = 0.91%; C.V. = 18.96% 
The stability parameters according to the model of Eberhart and Russell are given on Table 9. The most stable 
genotypes with the lowest S2di values were DZ-2012-CK-0028, DZ-2012-CK-0038, DZ-2012-CK-0039, DZ-
2012-CK-0034 in decreasing order. 

 

The most unstable genotypes with the highest S2di values were Natoli, local and DZ-2012-

CK-0028. So, these genotypes would best fit for specific adaptation in favorable environments. If 

themean yield ( x ), regression coefficient value (bi) and the deviation from theregression (S2di) are 

considered together, then the most stable genotype would be DZ-2012-CK-0034 with a mean 

yield x = 1805 kg /ha ranked first, bi = 1.01 close to 1 and the S2di = 735 ranked fourth. On the 

other hand, genotypes DZ-2012-CK-0027, DZ-2012-CK-0028, DZ-2012-CK-0029, DZ-2012-CK-

0030, DZ-2012-CK-0032, DZ-2012-CK-0035 and local had regression coefficient values (bi) less 

than one (i.e. above average stability and significant deviation from regression). So these 

genotypes were specifically adapted to poor environments. Genotype DZ-2012-CK-0031, DZ-

Genotypes Wi Rank Mean seed yield 
(Kg/ha) 

Rank 

DZ-2012-CK-0027 32724 5 2053 4 
DZ-2012-CK-0028 6038 14 1620 17 

DZ-2012-CK-0029 7232 12 1636 16 
DZ-2012-CK-0030 13365 9 1783 10 
DZ-2012-CK-0031 10795 10 1792 8 
DZ-2012-CK-0032 36057 3 1663 15 
DZ-2012-CK-0033 18199 7 1784 9 

DZ-2012-CK-0034 3063 16 1805 7 
DZ-2012-CK-0035 2338 17 1686 13 
DZ-2012-CK-0036 3385 15 2106 3 
DZ-2012-CK-0037 14406 8 1737 12 
DZ-2012-CK-0038 8231 11 1774 11 
DZ-2012-CK0039 6479 13 1861 6 

DZ-2012-CK-0040 33034 4 2223 1 
Natoli (SC) 110185 1 2176 2 
Minjar (SC) 31917 6 1875 5 
Local check  73873 2 1664 14 



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2012-CK-0033, DZ-2012-CK-0034, DZ-2012-CK-0036, DZ-2012-CK-0037, DZ-2012-CK-0038, 

DZ-2012-CK-0039, DZ-2012-CK-0040, Natoli, and Minjar had regression coefficients (bi) greater 

than one (i.e. below average stability and significant deviation from regression). Hence, these 

genotypes were specifically adapted to favorable environments. Similar results were obtained in 

common bean genotype tested [18] in different parts of Ethiopia and Ferreira, et al. [19] in 

Brazil. 

 
Table-9. Mean seed yield, regression coefficients (bi), coefficients of determination (r2i) and deviation 
from regression (S2di) 

Genotypes bi r2i S2di Seed Yield 
(kg/ha)  

Rank  

DZ-2012-CK-0027 0.74 1.01 5629 2053 4 
DZ-2012-CK-0028 0.93 1.00 13 1620 17 

DZ-2012-CK-0029 0.80 0.99 1535 1636 16 
DZ-2012-CK-0030 0.89 1.00 2028 1783 10 
DZ-2012-CK-0031 1.24 0.99 1405 1792 8 
DZ-2012-CK-0032 0.68 1.01 4775 1663 15 
DZ-2012-CK-0033 1.13 1.01 3318 1784 9 
DZ-2012-CK-0034 1.01 0.99 735 1805 7 

DZ-2012-CK-0035 0.97 0.99 1015 1686 13 
DZ-2012-CK-0036 1.11 0.99 1302 2106 3 
DZ-2012-CK-0037 1.06 1.00 2803 1737 12 
DZ-2012-CK-0038 1.11 1.00 232 1774 11 
DZ-2012-CK0039 1.11 0.99 357 1861 6 

DZ-2012-CK-0040 1.31 1.01 3811 2223 1 
Natoli (st.ck) 1.09 1.12 34519 2176 2 
Minjar (st.ck) 1.30 1.01 3516 1875 5 
local check 0.45 1.02 6418 1664 14 

 

               bi- regression coefficients, r2i-coefficients of determination, S2di-Deviation from regression. 

 
Table-10. AMMI analysis of variance for grain yield (kg/ha) of the 17 desi -type genotypes tested across five 
environments 
Source Df Sum of squares Mean of squares % Explained 

Total 339 22006783 64917  
Environment (E) 4 17449755 4362439** 79.3% 
Genotype (G) 16 804949 50309** 3.7% 
G × E 64 1844379 28818** 8.4% 
IPCA1 19 779080 41004** 42.2% 

IPCA2 17 603319 35489** 32.7% 

IPCA3 15 318905 21260** 17.3% 
IPCA Residuals 13 143075 11006 7.8% 

 

          **=significant at the P≤ 0.01 probability level 

 

3.3.3. AMMI Analysis and Biplot Representation of 17 Desi-Type Chickpea Genotypes 

The main effects of E and G accounted for 79.3 % and only 3.7% respectively, and G X E 

interaction accounted for 8.4% of the total variation in GE data for grain yield (Table 10). The 

high percentage of the environment is an indication that environment is the major factor that 

influence yield performance of chickpea in Ethiopia. The variation due to GE is more than double 

than the variation due to genotypes as main effect. Tarakanovas and Ruzgus [20], reported 

significant G X E interaction for grain yield and stressed the usefulness of AMMI analysis for 



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selection of promising genotypes for specific environments or environmental conditions. The first 

two principal components (PC1 and PC2) which were used to create a two-dimensional biplot, 

explained 42.24% and 32.72% of AMMI sum of squares, respectively (Table 10). The first two 

IPCA captures more than 74.96% of the total interaction main effect. The large sum of squares for 

environments showed  that the environments were diverse, with large differences among 

environmental means causing most of the variation in grain yield, which is in synchronization 

with the findings of  Yan and Tinker [21] in chickpea. This result also indicated the great 

influence the test environments have had on the yield performance of Desi-type genotypes in 

Ethiopia. 

The AMMI I biplot for grain yield of 17 Desi-type genotypes at five environmental 

conditions is presented on Fig. 1. The main effects (genotypes and environments) accounted for 

82.99 %, and IPCA 1 accounted for 42.24% and IPCA2 accounted for 32.71% of the total variation 

in genotype by environment interaction. The three IPCAs together accounted for 92.24% of the 

total interaction, the remaining 7.76% being the residual or noise, which is not interpretable and 

thus discarded. Environments showed high variation in both main effects and interactions 

(IPCA1) (Fig. 1).Chefe Donsa and Debre Zeit were most favorable environments; Haramaya and 

Dembia were  least favorable environments as these two environments are far from the origin, 

while Akaki is the average environment. Environments are also classified into four main groups 

based on their IPCA1 scores, those of Haramaya and Chefe Donsa in quadrant I have large 

positive IPCA1 scores, which interact positively with genotypes that have positive IPCA1 scores 

and negatively those genotypes with negative IPCA1 scores. Debre Zeit in quadrant III has large 

negative IPCA1 scores, which interact positively with genotypes having negative IPCA1 scores 

and negatively with genotypes that have positive IPCA1 scores. Akaki and Dembia in quadrant 

IV have large negative IPCA1 scores, which interact positively with genotypes having negative 

IPCA1 scores and negatively with genotypes that have positive IPCA1 scores. The environments 

can be sub-grouped according to their average yield over the genotypes. 

The biplot analysis revealed that genotypes DZ-2012-CK-0029, DZ-2012-CK-0031, DZ-

2012-CK-0036, and Minjar exhibited IPCA scores close to zero and high mean yield; thus they 

are found to be stable. Variety Natoli and local are far from the origin, were sensitive to 

environmental interactive force, and are considered unstable. Genotypes DZ-2012-CK-0029, 

Minjar and DZ-2012-CK-0031 are close to the origin, were non-sensitive to environmental 

intercations and are stable. The biplot also revealed association between environment and 

genotypes. The local variety, DZ-2012-CK-0032, DZ-2012-CK-0033 is related to environment 

Akaki and Natoli are not associated to any particular environment. DZ-2012-CK-0027 and DZ-

2012-CK-0036 are related to Chefe Donsa and DZ-2012-CK-0040 is related to Debre Zeit. 

Genotypes DZ-2012-CK-0031was high yielder since its mean was greater than the grand mean; it 

had positive IPCA scores, thus adapted to Debre Zeit. Genotypes with negative IPCA score were 

not adapted to any of the environments. Among environments, Chefe Donsa and Haramaya are 

favorable environments as they exhibited the highest positive IPCA1 score, while Debr zeit, 

Akaki and Dembia are marginal environments showing the highest negative IPCA scores.  



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Genotypes DZ-2012-CK-0040, Natoli, DZ-2012-CK-0036 and DZ-2012-CK-0027 have 

higher average yields and adapted to favorable environments, while genotypes Minjar, DZ-2012-

CK-0039 and DZ-2012-CK-0034 were adapted to poor environments. DZ-2012-CK-0027, DZ-

2012-CK-0030, DZ-2012-CK-0034, DZ-2012-CK-0036, Minjar were adapted to Chefe Donsa 

while DZ-2012-CK-0032, DZ-2012-CK-0039, and DZ-2012-CK-0040 were adapted to Debrezeit. 

Genotypes DZ-2012-CK-0037, DZ-2012-CK-0038, DZ-2012-CK-0032, DZ-2012-CK-0033 and 

local variety were adapted to Akaki.  Genotypes DZ-2012-CK-0040, Natoli, DZ-2012-CK-0036, 

and DZ-2012-CK-0027 had higher average mean grain yield and had highest positive and 

negative IPCA1 scores which makes them unstable genotypes. Genotype DZ-2012-CK-0032and 

DZ-2012-CK-0033 had low yield and large IPCA1 scores which indicates that they unstable.  

  

 
Fig-1. AMMI biplot of IPCA1 vs. Main effects using yield data for Desi-type chickpea genotypes. 

Akk=akaki, dzt= Debre Zeit, hun= haramaya, dem= dembia and chf= Chefe Donsa; G1-G17 graph ID for the genotypes 

 

Table-11. Yield (kg/ha) and parametric stability statistics for grain yield on 17 genotypes grown in five 

environments 

Genotype IPCA1 IPCA2 ASV Rank  Yield  

DZ-2012-CK-0027 4.81 -8.06 9.74 14 2053 
DZ-2012-CK-0028 1.61 2.30 2.93 3 1620 
DZ-2012-CK-0029 0.02 -6.21 6.21 10 1636 
DZ-2012-CK-0030 3.91 -3.39 5.59 9 1783 
DZ-2012-CK-0031 0.66 3.23 3.32 4 1792 

DZ-2012-CK-0032 6.55 -6.32 9.76 15 1663 
DZ-2012-CK-0033 -4.40 3.99 6.39 10 1784 
DZ-2012-CK-0034 2.69 -1.89 3.59 5 1805 
DZ-2012-CK-0035 1.44 0.13 1.64 1 1686 
DZ-2012-CK-0036 0.17 3.80 3.81 7 2106 
DZ-2012-CK-0037 -2.99 2.34 4.12 8 1737 
DZ-2012-CK-0038 -2.65 2.12 3.68 6 1774 
DZ-2012-CK0039 -1.26 1.82 2.31 2 1861 
DZ-2012-CK-0040 -3.35 5.88 7.00 12 2223 
Natoli (SC) 15.29 0.01 17.37 17 2176 
Minjar(SC) 0.00 8.34 8.34 13 1875 

Local check -8.07 -8.10 12.23 16 1664 

              SC=Standard Check 

 



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3.3.4. AMMI Stability Value (ASV) 

According to the ASV ranking, the most stable genotypes were DZ-2012-CK-0035, DZ-

2012-CK-0039 and DZ-2012-CK-0028. DZ-2012-CK-0040 and Minjar were the first and second 

highest yielders based on the mean yield values (Table 11). However, DZ-2012-CK-0040 which 

was the highest for mean yield, ranked 12th for the ASV. The most unstable genotypes were 

Natoli, local, DZ-2012-CK-0032 and DZ-2012-CK-0027. These results are similar with most of 

the stability indices estimation. ASV was used similarly to identify the stability of common bean 

varieties in eastern Ethiopia by Nigussie [22]. 

 

3.4. Cluster Analysis of Genotypes  

Cluster analysis was performed to study the patterns of groupings of genotypes.  

Dendrograms (Fig. 2) were generated from SAS clustering method of hierarchical algorism 

method based on Euclidean distances using AMMI adjusted mean yields of genotypes. Clustering 

of genotypes at a cut-off value of zero produced five clusters. Cluster one consisted of seven 

genotypes (DZ-2012-CK-0030, DZ-2012-CK-0031, DZ-2012-CK-0033, DZ-2012-CK-0037, DZ-

2012-CK-0038, DZ-2012-CK-0039 and Minjar). Cluster two consisted of five genotypes (DZ-

2012-CK-0028, DZ-2012-CK-0029, DZ-2012-CK-0032, DZ-2012-CK-0035 and local). Cluster 

three consists of two genotype (DZ-2012-CK-0027 and DZ-2012-CK-0036) and in this group 

both genotypes were characterized as high yielder and clearly shown in the AMMI biplot. Cluster 

four consisted of two genotypes (DZ-2012-CK-0040 and Natoli) which were characterized as high 

yielders. The last clustering group consists of only one genotype which is DZ-2012-CK-0034. 

 

 
Fig-2. Dendrogram depicting the clustering of 17 Desi-type chickpea genotypes 

Note; DZ-2012-CK-0027=1, DZ-2012-CK-0028=2, DZ-2012-CK-0029=3, DZ-2012-CK-0030=4, DZ-2012-CK-0031=5, DZ-2012-CK-
0032=6 DZ-2012-CK-0033=7, DZ-2012-CK-0034=8, DZ-2012-CK-0035=9, DZ-2012-CK-0036=10, DZ-2012-CK-0037=11,DZ-2012-CK-
0038=12 DZ-2012-CK-0039=13, DZ-2012-CK-0040=14,natoli=15,Minjar=16 and local variety=17. 

 

4. CONCLUSIONS 

The combined analysis of variance revealed significant (P≤0.01) differences for environments, 

genotypes and genotype by environment interaction in Desi-type chickpea genotype. Except seed 

per pod, the variations were significant for all the characters studied  

In this study, univariate and multivariate stability parameters were used to select the most 

stable chickpea (Desi-type) genotypes for Ethiopia. The univariate stability parameters showed 

inconsistence to recommend the most stable genotypes. However, multivariate method, AMMI 



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model could be used to identify superior genotypes for specific adaptation and the AMMI model is 

one of most important package to investigate patterns, relationships and for predicting 

performance of genotype and environments. In this experiment Dembia and Haramaya are the 

most discriminative environments for Desi type chickpea genotypes and Debre Zeit and Chefe 

Donsa was the favorable environment and Akaki was moderately favorable environment for Desi-

type chickpea genotype. Genotypes, DZ-2012-CK-0040, DZ-2012-CK-0036 and DZ-2012-CK-

0040, DZ-2012-CK-0032 and variety Natoli were recommended as specifically adapted to sites 

Akaki, Chefe Donsa, Debre Zeit, Dembia and Haramaya respectively for Desi-type chickpea. As 

the experiment was tested on five environments, it is imperative to use the recommended 

genotype for the given environment. 

 

5. ACKNOWLEDGMENTS  

We would like to thank express our appreciation to TL-I Project for its financial support. We 

are also indebted for the assistances provided by the research and technical staff of the highland 

pulse improvement program of Debre Zeit Agricultural Research Center (DZARC) and Gonder 

Agricultural Research Center (GARC). 

 

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