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Agriculture and Food Sciences Research 
Vol. 7, No. 2, 113-124, 2020 

ISSN(E) 2411-6653/ ISSN(P) 2518-0193 
DOI: 10.20448/journal.512.2020.72.113.124 

© 2020 by the authors; licensee Asian Online Journal Publishing Group 

    
 

 
 
 
Combining Ability Analysis of Maize Inbred Lines in Ethiopia 

 
Abenezer Abebe Tefera1 
Legesse Wolde Beyene2 
Wosene Gebreselassie Abtew3 

  
( Corresponding Author)  

1,2Department of Crop Science, Ethiopian Institute of Agricultural Research, Holetta Agricultural Research 
Center, Holeta, Ethiopia. 

 
3Department of Horticulture and Plant Science, Jimma University, College of Agriculture and Veterinary 
Medicine, Jimma, Ethiopia. 

 
  

 
Abstract 

The study was initiated to estimate combining ability of maize inbred lines and crosses using line 
by tester analysis. Fifty entries consists 48 F1 single crosses developed from 24 inbred lines and 2 
testers using line x tester design and two commercial check hybrids used in the study. The 
experiment was conducted using alpha lattice design with two replications. Analysis of variance 
revealed existence of significant genetic variation among genotypes for all studied traits except 
for plant aspect (PA). Location x entry interaction for most of the traits was not significant which 
suggests hybrid performance was consistent across tested locations. Line x tester analysis of 
variance showed that mean squares due to GCA of lines were significant (p< 0.01 or p< 0.05) for 
all studied traits. Mean squares of tester GCA and SCA were significant for most of studied traits. 
This indicates that both additive and non-additive gene effects had contributed for the variation of 
the crosses. However, higher proportional contribution of additive gene action for all studied 
traits was obtained. Several lines and crosses were identified as good general and specific 
combiners for yield and yield related traits. Lines L23, L11, L15 and crosses L2xT1, L3xT1, 
L8xT1, L11xT1, L23xT1 and L13xT2 were found to be good general and specific combiners, 
respectively. In conclusion, the stated inbred lines with desirable gca effects and cross 
combinations with desirable sca effects for grain yield and yield related traits could be used as 
useful genetic material. 

 
        Keywords: Combining ability, General combining ability, Specific combining ability, Inbred lines, Line by tester, Maize. 

 
Citation | Abenezer Abebe Tefera; Legesse Wolde Beyene; Wosene 
Gebreselassie Abtew (2020). Combining Ability Analysis of Maize 
Inbred Lines in Ethiopia. Agriculture and Food Sciences Research, 
7(2): 113-124. 
History:  
Received: 30 April 2020 
Revised: 10 June 2020 
Accepted: 13 July 2020 
Published: 28 July 2020 
Licensed: This work is licensed under a Creative Commons 

Attribution 3.0 License  
Publisher:  Asian Online Journal Publishing Group 
 

Acknowledgement: All authors contributed to the conception and design of 
the study. 
Funding: This study received no specific financial support. 
Competing Interests: The authors declare that they have no conflict of 
interests. 
Transparency: The authors confirm that the manuscript is an honest, 
accurate, and transparent account of the study was reported; that no vital 
features of the study have been omitted; and that any discrepancies from the 
study as planned have been explained. 
Ethical: This study follows all ethical practices during writing.   

 

 

Contents 
1. Introduction .................................................................................................................................................................................... 114 
2. Materials and Method ................................................................................................................................................................... 114 
3. Results and Discussion ................................................................................................................................................................. 116 
4. Conclusion ....................................................................................................................................................................................... 121 
References ............................................................................................................................................................................................ 121 
 

 
 
 

 

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Contribution of this paper to the literature 
The study was initiated to estimate combining ability of maize inbred lines and crosses using line by 
tester analysis. 

 
1. Introduction 

Maize (Zea mays L.) is a diploid (2n = 20) crop belongs to the family of grasses Poaceae and tribes Maydeae and 
naturally it is cross pollinated crop. The crop is grown over a wide range of environmental conditions. Maize has 
great world-wide importance as human food, industrial raw material and animal feed. Because of its high yield 
potential and wider adaptation, maize is one of the strategic crops for the achievement of food security. Prasanna, et 
al. [1] noted that the crop is a vital source of calorie, protein, and some important vitamins and minerals to billions of 
people world-wide, particularly in Africa, South America and Asia. Approximately 88% of maize produced in Ethiopia 
is consumed as food, both as green and dry grain. The per capita consumption is 50 kg per annum [2].  

Maize is cultivated globally as one of most important cereal crops and ranks third next to wheat and rice. The 
total world production of maize is 1,068.79 MT, with the United States producing 384.78 MT, China 219.55 MT, 
Brazil 97.00 MT, European Union 60.71 MT, South Africa 16.40 MT and Ethiopia harvesting 6.35 MT of the total 
production of maize Foreign Agricultural Service (FAS) [3]. Central Statistical Agency (CSA) [4] reported that in 
Ethiopia by 2016/17 main cropping season out of the total grain crop area (12,574,107.33 hectare), 81.27% was under 
cereals of which maize share as large area as 16.98%, after tef (24%). Regarding total annual production, cereals 
contributed 87.42% (253,847,239.63 quintals) in which maize ranked first 27.02% (78,471,746.57 quintals) [4]. Over 
5.8 million hectares of potential suitable land was identified for the highland maize hybrids in the country [5]. The 
crop is increasingly grown to the highlands of Ethiopia where it has been a minor crop in the past. Zeng, et al. [6] 
pointed out that increased productivity and production of maize has significant positive impact on poverty reduction 
in sub-Saharan African countries including Ethiopia. 

Considering its importance, wide adaptation, total production and productivity, maize is one of the high priority 
crops to feed the increasing population of the country. However, national average yield in Ethiopia is still as low as 
3.675t ha-1[4] compared to that of the developed world 10.96t ha-1[3] and this warrants the increasing maize 
productivity as high national priority issue. For such yield gap, a number of production constraints are responsible. 
The shortages of high yielding varieties or potential parent materials and the effect of biotic and abiotic stresses are 
the major constraints limiting maize production and productivity [2]. This implies the need for developing high 
yielding maize varieties from suitable parents and crosses which will perform well under stress and non-stress 
conditions. 

Identification of suitable inbred lines and superior cross combinations require knowledge of combining ability. 
Information from combining ability (GCA and SCA) analysis can show the type of gene action involved in controlling 
quantitative characters thereby assisting breeders in selecting suitable parent materials and crosses [7]. Parental 
lines selection can be performed by particular mating designs such as line x tester, North Carolina (NC) designs I, II 
and III, and diallel. Line x tester analysis as suggested by Kempthorne [8]is useful in deciding the relative ability of 
female and male lines to produce desirable hybrid combinations [9]. Lines x tester programs have been applied to 
provide a systematic approach for the detection of suitable parents and crosses for investigated characters [10]. 

Combining ability has been studied in Ethiopia for different sets of new maize inbred lines [9, 11]. However, it is 
always mandatory for any breeding program to generate such information for any new batch of inbred lines 
developed or received outside of the program. In line with this, highland maize breeding program at Ambo 
Agricultural Research Center (AARC) in collaboration with CIMMYT recently developed inbred lines and crosses 
whose genetic information has not been studied. Hence, the study was conducted to evaluate the combing ability of 
inbred lines and their testcrosses. 
 

2. Materials and Method 
Description of Study Site: The experiment was conducted at Ambo and Holeta Agricultural Research Centers of 

the Ethiopian Institute of Agricultural Research (EIAR) during the main cropping season of 2017. Holeta 
Agricultural research center (HARC) is located at 09o04’12”N latitude and 38o29’45”E longitudes and an elevation of 
2400 m.a.s.l. The center receives an average rainfall of 1102 mm per annum. The maximum and minimum 
temperatures of this site are 6oC and 22oC, respectively. The center has nitosols and vertisols soil types with pH of 6.0 
[12]. 

Ambo Agricultural Research Center (AARC) is located at 8o57’ N l and 37º 51ꞌ E and the elevation is 2225 m.a.s.l. 
The site receives an average rainfall of 1115mm. The maximum and minimum temperatures of this site are 11.7oC 
and 25.4oC, respectively. The soil type of Ambo is clay (heavy vertisols) with a pH of 7.8 [13]. 
 

2.1. Experimental Materials 
The experiment consisted of 50 maize entries which include 48 testcrosses and two hybrid checks (AMH853 

Kolba and AMH851-Jibat). The testcrosses (48) were generated from crossing of 24 inbred lines (female parents) with 
two testers (male parents) in line x tester mating design during 2015/2016 cropping season at Ambo Agricultural 
Research Center. The inbred lines were developed at Ambo Agricultural Research Center from CYMMYT materials 
using ear-to-row selection and subsequent selfing until they attain homozygosity. The testers used for the formation 
of the testcrosses were FS59 (Tester 1) and FS67 (Tester 2) Table 1. The first tester was from heterotic group “B”, 
while the second was from heterotic group “A”. The checks used in the study were AMH851 (Jibat) and AMH853 
(Kolba) which are three-way cross hybrid varieties released by Ambo Agricultural Research Center, highland maize 
breeding program in 2011 and 2015, respectively. They take about 178 days for grain mature at Ambo and similar 
environments. Besides, hybrid checks are high yielding, tolerant/resistance to major maize disease in the country and 
well adapted to the altitude ranging from 1800-2600m in the highland sub-humid agro-ecological conditions of the 
country [14]. 

 
 



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Table-1.List and pedigree of parents and hybrid checks used for the study. 

SN Line Code Pedigree Origin 

1 L1 (CML442*/OFP4)-B-4-2-2-B-B-B-# AMB16N42-29/AMB16N42-144 
2 L2 (CML495*/OFP14)-7-1-5-1-1-B-B-# AMB16N42-107/AMB16N42-144 

3 L3 (CML442*/OFP4)-B-17-1-1-B-B-B-# AMB16N42-32/AMB16N42-144 

4 L4 (CML495*/OFP6)-B-27-1-1-B-# AMB16N42-142/AMB16N42-144 

5 L5 (CML539*/OFP14)-2-1-1-2-2-B-B-# AMB16N42-16/AMB16N42-144 

6 L6 (CML442*/OFP4)-B-17-5-1-B-B-B-# AMB16N42-36/AMB16N42-144 

7 L7 (CML395*/OFP105)-1-1-1-1-1-B-B-# AMB16N42-38/AMB16N42-144 

8 L8 (CML395*/OFP105)-1-2-3-1-1-B-B-# AMB16N42-39/AMB16N42-144 

9 L9 CML539*/OFP1)-B-11-2-2-B-B-B-# AMB16N42-20/AMB16N42-144 

10 L10 (CML444*/OFP23)-6-3-1-1-1-B-B-# AMB16N42-44/AMB16N42-144 

11 L11 (LPSC7-F96-1-2-1-1-B-B-B*/OFP9)-3-2-1-1-1-
B-B-# 

AMB16N42-2/AMB16N42-144 

12 L12 (CML444*/OFP14)-3-2-4-1-2-B-B-# AMB16N42-47/AMB16N42-144 

13 L13 (CML444*/OFP4)-B-4-1-1-B-B-B-# AMB16N42-50/AMB16N42-144 

14 L14 (CML444*/OFP4)-B-6-1-1-B-B-B-# AMB16N42-51/AMB16N42-144 

15 L15 (CML537*/OFP106)-6-1-3-1-2-B-B-# AMB16N42-53/AMB16N42-144 

16 L16 (CML537*/OFP106)-7-1-2-1-2-B-B-# AMB16N42-56/AMB16N42-144 

17 L17 (CML491*/OFP4)-B-10-1-2-B-B-B-# AMB16N42-88/AMB16N42-144 

18 L18 CML546-# AMB16N42-61/AMB16N42-144 

19 L19 ([SYN-USAB2/SYN-ELIB2]-12-1-1-1-B*4-B-
B-B*/OFP105)-4-2-1-1-2-B-B-# 

AMB16N42-62/AMB16N42-144 

20 L20 ([CML312/[TUxPSEQ]C1F2/P49-SR]F2-
45-3-2-1-BB//INTA-F2-192-2-1-1-1-BBBB]-
1-5-1-1-1-BBB-B-B-B*/OFP106)-1-2-2-2-1-B-
B-# 

AMB16N42-75/AMB16N42-144 

21 L21 ([CML444/CML395//DTPWC8F31-1-1-2-2-
BB]-4-2-2-1-2-BB-B-B-B*/OFP105)-1-4-3-3-2-
B-B-# 

AMB16N42-65/AMB16N42-144 

22 L22 ([CML444/CML395//DTPWC8F31-1-1-2-2-
BB]-4-2-2-1-2-BB-B-B-B*/OFP105)-2-1-1-2-1-
B-B-# 

AMB16N42-66/AMB16N42-144 

23 L23 (LPSC7-F71-1-2-1-2-B-B-B*/OFP2)-B-1-3-2-
B-B-B-# 

AMB16N42-8/AMB16N42-144 

24 L24 [CML444/CML395//DTPWC8F31-1-1-2-2-
BB]-4-2-2-2-1-B*7-B-# 

AMB16N42-69/AMB16N42-144 

  Tester  

25 T1 FS59 Heterotic group 

26 T2 FS67 Heterotic group  

  Checks   

27  JIBAT  3-way hybrids 

28  KOLBA 3-way hybrids 

             

2.2. Experimental Design and Procedure 
The experimental materials along with two hybrid checks were grown during the 2016/2017 main cropping 

season using alpha lattice design [15] with two replications, 10 incomplete blocks and 5 plots per the incomplete 
blocks at both locations. Each entry was planted in a single row plot of 5.25m length with a spacing of 75cm between 
rows and 25cm between plants. Seeds were planted with two seeds per hill and later thinned to one plant at four leaf 
stage. 
 

2.3. Data Collection and Analysis 
Data were collected days to 50% anthesis (AD), days to 50% silking (SD), anthesis-silking interval (ASI), ear 

aspect (EA), plant aspect (PA), grain yield (GY), number of ear per plant (EPP) and thousand kernel weight 
(TKW) on plot basis. On plant basis data were collected on plant height (PH), ear height (EH), ear length (EL), ear 
diameter (ED), number of kernel rows per ear (KRPE) and number of kernels per row (KPR). Plant aspect and ear 
aspect were measured in 1 to 5 scales. 

The data obtained for different traits from field measurements were organized and analyzed using SAS 
statistical package [16]. Analysis of variance across location was conducted with PROC GLM procedure by 
considering location, replication and blocks as random and entry/genotype as fixed factors with statement of 
RONDOM and TEST option. The significance of mean squares for entries, crosses, and location in combined analysis 
were tested against the mean squares for their corresponding interaction with location as error term, while their 
interaction with location were tested against their corresponding pooled error. Based on general analysis of variance, 
traits that showed significant differences among the entries were further analyzed according to line x tester analysis 
[8] using analysis of genetic designs with R (AGD-R) version 3.0 procedures for individual and combined data [17].  
 

2.4. Estimation of  Combining Ability Effects 
Genotypic means of individual locations were used for the determination of GCA and SCA. The GCA effects of 

lines (L) and testers (T), the SCA effect of LxT, and their interactions with the environment were determined 
following the method stated by Kempthorne [8] assuming the following model.  

Yijke= µ + Le + R (L) ke +Vij+ (LV) ije +Ԑijke Where, Yijke = observed value from each experimental unit; µ = 
grand mean; Le = location effect; Rke = replication effect within each location Vij = F1 hybrid effect = gi+gj+sij, 
where, gi = general combining ability of ith lines; gj = general combining ability of jth tester; sij = specific combining 

ability of ijthF1 hybrids; (LV) ije = interaction effect of ijth F1 hybrid and eth location Ԑijke = residual effect. 
The Significance of GCA and SCA effects were performed computing the standard error for lines, testers and 

crosses and then tested against t-test by taking the degree of freedom of pooled error mean square [18, 19]. The 
proportional contributions of lines (GCAL), testers (GCAT), and their interaction (SCA LxT) to the sum square of 
crosses were calculated as the ratio between sum of squares of each component and the cross sum of squares as given 
[19]. 
 



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3. Results and Discussion 
The analysis of variance and general and specific combining ability effects were computed and the results are 

discussed below.  
 

3.1. Analysis of Variance 
The analysis of variances for yield and yield related traits for individual and combined location are presented in 

Appendix 1, 2 and Table 2. Significant differences were detected between the two locations for all of the studied traits 
except for ear length, indicating that the two locations differed in the environmental conditions to cause variation 
which agreed with the finding of Aly and Khalil [20]. Entry difference were significant (p<0.01 or p<0.05) for all 
traits except for plant aspect Table 2. Entries differed in their performance from one location to another for variable 
like grain yield, plant and ear height, ear diameter and 1000 kernels as entry x location interaction was significant. 
Beyene, et al. [21] and Murtadha, et al. [22] also reported significant entry x location interaction effect for some 
yield and its components in maize and indicated presence of wide variability with regard to tested entry and 
locations. The result showed the location played significant role in the variation of these traits. If significant genotype 
x location interaction mean squares existed, different genes involved in controlling the traits show the inconsistency of 
the genes over locations [23]. The interaction of entry with location suggests further evaluation of the genotypes 
across more number of locations to minimize environmental effect from computation genetic variance. 
 

Table-2. Analysis of variance for yield and yield related traits of 48 testcross and two hybrid checks evaluated at Holeta and Ambo, 2017. 

3.2. Combining Ability Analysis 
Significant differences (p<0.01, or p<0.05) were observed among the crosses for all traits except for anthesis-

silking interval at Holetta and for number of kernels per row at Ambo Appendix 3 and 4. At Ambo, GCA mean 
squares due to lines were significant (p<0.01, or p<0.05) for most of the studied traits except for ear position and ear 
aspect, while tester GCA mean squares were significant (p<0.01, or p<0.05) for days to 50% silking, anthesis- silking 
interval, plant and ear height, ear aspect and 1000 kernels weight Appendix 3. Similarly, SCA mean squares for line x 
tester were significant for grain yield, ear height, ear position and ear aspect. At Holetta, GCA mean squares of lines 
and testers were significant (p<0.01, p<0.05) for all traits except for ear length, anthesis silking interval and number 
of kernels per row and GCA of tester for days to 50% anthesis, number of kernels per row and 1000 kernels weight. 
The mean squares of SCA line x testers were also significant (p<0.01, or p<0.05) for seven traits and non-significant 
for other seven studied traits Appendix 4. This indicates both additive and non-additive gene actions with different 
level from location to location were involved in the inheritance of these traits. The observed differences in the level of 
significance of GCA and SCA mean squares with changing locations were an indication of environmental effect on the 
preponderance of additive and non-additive gene action. Zare, et al. [24] reported the different level of GCA and SCA 
mean square for different testing environment. In contrast, Haddadi, et al. [25] found no environmental effect on the 
preponderance of additive and non-additive gene action. The significance of mean squares due to lines and testers 
indicated inbred lines variation among the lines and tester in their performance. Meanwhile, significant line x tester 
interaction suggests that inbred lines performed differently according to the testers to which they were crossed. 

Combined analysis of line x tester showed highly significant (p<0.01) difference among cross for all studied traits 
Table 3a and 3b. Cross x location interaction were significant (p<0.01, or p<0.05) for most traits except for days to 
50% anthesis, anthesis silking interval and ear position. This indicates the presence of wide genetic variations among 
the studied materials. These findings are in agreement with those reported by Aly and Hassan [26]; Aly and Khalil 
[20] and Mousa [27]. The mean squares of GCA lines and testers and SCA were significant (p<0.01, or p<0.05) for 
all traits except GCA of testers for days to 50% anthesis, number of ear per plant and ears aspect, and SCA for 
anthesis silking interval, number of ears per plant, number of kernel rows per ear and ear diameter, which confirms to 
the finding of Mohammad, et al. [28] and Dar, et al. [29]. Significant GCA and SCA mean squares indicate that both 
additive and non-additive gene effects were involved for the variation of crosses through all studied traits. However, 
higher GCA proportional contribution and GCA/SCA ratio greater than unit indicated predominance of additive 
gene action for all studied traits. This indicates that variations among crosses through all the studied traits were 
mainly due to additive gene effect which was in accordance with the finding of Amare, et al. [30]. Adebayo and 
Menkir [31];Satyanvesh [32];Tolera, et al. [11] have earlier reported that additive gene actions were more 
important than non-additive gene actions for inheritance of grain yield and yield related traits. However, Aminu, et al. 
[33] and Arsode, et al. [34] reported that non-additive gene action was predominated in the inheritance of these 
traits. Based on current findings, the inheritance of all traits was governed by additive gene effect, suggesting 
selection would be effective in improving yield and yield related traits. 

Trait L, df=1 Re(L)df=2 B(L*R) 
df=36 

Ent 
df=49 

Ent*L 
df=49 

Error 
df=62 

Mean±SE(m) CV% R2 

GY 8.38* 0.03 1.29 4.41* 2.63** 1.1 7.53± 0.52 13.9 0.86 
AD 14162.4** 24.23** 2.96 13.33** 2.77 3.18 104.52±0.89 1.71 0.99 
SD 18489.6** 19.34** 2.60 15.66** 2.51 3.31 105.15±0.91 1.73 0.99 
ASI 0.63** 0.001 0.005 0.007* 0.005 0.004 1.2± 0.03 

 
5.52 0.86 

PH 574.6** 779.0** 161.6 1631.89** 237.4* 139.1 251.07±5.9 4.70 0.93 
EH 5724.5** 398.33** 45.04 943.11** 85.85* 54.64 136.66±3.7 5.41 0.95 

EPO 0.07** 0.0002 0.001 0.004** 0.0007 0.002 0.54±0.02 7.33 0.79 
EPP 1.49** 0.007 0.03 0.13** 0.05 0.03 1.70±0.09 10.18 0.86 
EA 0.78* 0.91** 0.13 0.43** 0.19 0.13 3.12±0.18 11.56 0.84 
PA 2.88** 0.75* 0.15 0.20 0.14 0.20 3.30±0.22 13.69 0.70 
EL 1.69 8.82** 0.98 3.61** 1.21 0.81 15.47±0.45 5.82 0.88 
ED 1.62** 0.004 0.03 0.10** 0.03** 0.03 4.32±0.09 3.84 0.86 

KRPE 10.76** 0.58 0.63* 1.21** 0.47 0.37 12.86±0.3 4.74 0.86 
KPR 19.22* 25.22** 7.43* 8.51** 6.50 4.22 32.3±1.03 6.37 0.83 
TKW 193827.8** 27.26 743.1 3102.2** 1603.9* 947.3 305.0±15.39 10.09 0.90 



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GCA line x location interaction was significant (p<0.01, or p<0.05) for traits such as grain yield, ear height, 
number of ears per plant, ear length and number of kernels row/ear, while GCA tester x location interaction effect 
showed significant for all studied traits except for days to 50% anthesis and silking, ear position and ear length Table 
3aand 3b. These suggest that the lines and testers were depended on the location in which they were grown and 
limited number of testing location would be insufficient. Comparable results were reported Aly [35]; Fan, et al. [36] 
and Noelle, et al. [37] for the materials they studied. On the contrary, non-significant GCA x location interaction 
mean squares were reported by Alemeshet [38]. Significant GCA x location interaction implies that the trend of 
variation of GCA of lines and testers were different across location and selection for good combining lines would be 
effective if based on hybrid performance across a range of environment. This also suggests the need for selecting 
inbred lines at specific locations. However, mean squares of SCA x location interaction were non-significant for all 
investigated traits which were in agreement with the finding of Dagne, et al. [39]; Adebayo and Menkir [31] and 
Fan, et al. [36]. But, Tulu, et al. [40] for grain yield and ear per plant, Noelle, et al. [37] for days to 50% silking and 
ear aspect and Mosa, et al. [41] for ear length, number of rows per ear and number of kernels per row found 
significant SCA x location interaction. 
 

Table-3a. Analysis of variance and heritability for yield and yield related traits of 48 testcrosses and two commercial hybrid 
checks evaluated at Ambo and Holeta, 2017. 

Source df GY t/ha AD day SD day ASI day PH cm EH cm EPO % 

Loc 1 7.76* 12661** 17787** 193** 351.72 5184 ** 0.067** 
Rep(Loc) 2 0.06 23.07** 18.89** 0.32 403.86 357.6 ** 0.000 

Cross 47 5.20** 13.92** 18.23** 3.03* 1952.07** 1208.2 ** 0.005** 

Line(GCA) 23 5.92** 21.48** 25.75** 2.30* 1019.01** 772.4** 0.006** 
Tester(GCA) 1 22.07** 10.45 105.02** 47.51** 59791.93** 33769 ** 0.033** 
Line xTester 23 3.75** 6.50* 6.94** 1.82 370.08** 228** 0.002 
Cross x Loc 47 2.57** 3.90 4.38* 1.90 221.59* 96.49* 0.001 
Line x Loc 23 2.81** 4.08 4.60 1.39 205.39 93.50 * 0.001 

Tester x Loc 1 20.90** 0.31 14.08* 17.06** 2665.16** 1307** 0.001 
L x T x Loc 23 1.54 3.87 3.75 1.75 131.55 46.84 0.001 
GCA/SCA  1.83 3.38 4.37 2.40 9.78 9.82 4.67 

Error 58 1.07 3.14 3.16 1.65 129.31 52.26 0.001 
Pro. Cont (%) 

L  55.66 75.55 69.11 37.20 25.55 31.29 67.33 
T  9.02 1.60 12.25 33.38 65.17 59.47 15.04 

LxT  35.32 22.85 18.64 29.42 9.28 9.24 17.63 
h2

b  28.19 68.26 71.21 34.45 84.65 88.76 80 

Table-3b.Analysis of variance and heritability for yield and yield related traits of 48 testcrosses and two commercial hybrid checks 
evaluated at Ambo and Holeta, 2017. 

Source df EPP no EA scale EL cm ED cm KRPE no KPR no TKW gm 

Loc 1 1.35** 1.01** 1.88** 1.08** 4.20** 5.83 186083** 
Rep(Loc) 2 0.006 0.67* 6.69** 0.01 0.18 7.21 14.33 

Cross 47 0.147** 0.51** 4.74** 0.11** 1.30** 9.43** 3885.10** 
Line(GCA) 23 0.229** 0.80** 7.36** 0.18** 1.53** 11.68** 5356.10** 

Tester(GCA) 1 0.193* 0.05 0.88 0.34** 11.79** 10.46 34114.7** 
Cross x Loc 47 0.050* 0.21* 1.33* 0.04* 0.57* 6.31* 1909.8** 
Line x Loc 23 0.055* 0.18 1.55* 0.04 0.62* 6.84 1256.1 

Tester x loc 1 0.188* 1.94* 2.59 0.65** 1.87* 1.90 26660.1** 
LxT x Loc 23 0.039 0.17 1.05 0.02 0.47 5.96 1486.45 
GCA/SCA  3.45 3.28 3.23 5.09 3.37 1.70 6.21 

Error 58 0.031 0.13 0.85 0.02 0.36 3.96 820.01 
Pro.cont (%) 

L  74.55 76.39 76.027 77.16 57.76 60.65 67.46 

T  2.99 0.22 0.003 6.42 19.32 2.36 18.68 

LxT  22.45 23.39 23.64 16.42 22.89 37.04 13.86 

h2
b  58.43 50.85 65.33 53.85 48.34 26.49 39.72 

 

3.3. General Combining Ability Effect 
Estimates of gca effects of 24 inbred lines and two testers for combined data of yield and yield related traits are 

presented in Table 4aand 4b. Out of 24 lines, three of them had positive and highly significant gca effects and six lines 
exhibited negative and significant (p<0.01, or p<0.05) gca effects for grain yield. Line L23 showed maximum gca effect 
(1.64t ha-1) followed by L11 (1.50t ha-1), whereas L13 revealed lowest gca effect (-1.57t ha-1) followed by L3 (-1.31t ha-

1). This depicts the presence of best and poorest general combiners in the group of the studied inbred lines. L23, L11 
and L15 found to be good general combiners suggesting their ability to transmit additive genes in desirable direction 
for grain yield. L3, L7, L13, L21, L18 and L19 found to be poor general combiners as they had tendency to reduce 
grain yield. Among the testers, FS59 revealed significantly positive gca effect. Several researchers Girma, et al. [9]; 
Natol [42] reported both positive and negative significant gca effects for maize grain yield in different set of 
materials. High GCA effects are attributed to additive or additive x additive gene effects which denote the fixable 
genetic components of variance [43]. The inbred lines with good general combining ability can make complementary 
single cross which can be used as seed parent for three-way or double cross hybrid development. 

For days to 50% anthesis and silking, gca effects of inbred lines ranged from -2.81 to 2.70 and -2.89 to 3.49 Table 
4a, respectively. L3, L7, L10, L13, L14 and L22 showed positive gca effects, while lines L1, L4, L5, L9 and L18 had 
negative gca effects for both traits. Lines gca effect for anthesis- silking interval ranged from -1.41 (L12) to 1.06 (L3) 



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and tester gca effects for anthesis-silking interval were -0.5 (T2) to 0.5 (T1). Despite the importance of negative gca 
effects for anthesis-silking interval, only L12 was found to be good general combiner. Negative and significant line 
gca affects for days to 50% anthesis and silking, and anthesis silking interval suggests the possibility of exploiting 
favorable genes for earliness to maturity and narrower anthesis silking interval in future breeding work. Similarly, 
Sundararajan and Kumar [44] and Demissew [13] suggested the importance of the negative gca effects for days to 
50% anthesis and silking to develop early maturing varieties. 

For plant and ear height, L1, L5, L10, L12, and L14 revealed positive and significant lines gca effect, while L2, L8, 
L13, L18 and L22 showed negative and significant gca effects. Inbred lines with negative gca effects are good general 
combiners for plant and ear height. Girma, et al. [9] concluded that shorter plant height with lower ear placement is 
desirable. Inbred lines with negative gca effect had tendency to reduce plant and ear height, hence genotypes with 
shorter plant height with lower ear placement can be good for lodging resistance. Ji, et al. [45] also noted that 
cultivars with high ear positions are prone to root and stalk lodging and suggested that negative significant lines gca 
effects are desirable shorter stature and lower ear placement. 

Significant gca effects of inbred lines ranged from -0.37 (L18) to 0.40 (L23) for number of ear per plant, -1.71 
(L13) to 2.06 (L15) for ear length, -0.24 (L7) to 0.27 (L10) for ear diameter, -0.83 (L17) to 0.73 (L20) for number of 
kernel rows per ear and -3.02 (L1) to 2.27 (L4) for number of kernels per rows Table 4b. L1, L9, L23 and L24 for 
number of ears per plant, L4, L7, L8, L10, L12, L14, L15 and L24 for ear length, L4, L10, L11, L12, L14, L20 and L21 
for ear diameter and L8, L10, L11, L14, L20 for number of kernel rows per ear and L4 and L15 for number of kernels 
per rows showed positive and significant gca effects. On the other hand, L4, L8, L13, L18, L20 and L21 for number of 
ears per plant, L1, L9, L11, L13 and L19 for ear length, L1, L7, L16, L17, L19, L22, L23 and L24 for ear diameter, L2, 
L5, L16, L17, L21 and L22 for number of kernel rows per ear and L1, L3 and L9 for number of kernels per row 
revealed negative and significant line gca effect. Ejigu, et al. [46] also reported certain inbred lines with good general 
combing ability and suggested the possibility of improving these traits through selection. The present study also 
identified inbred lines with good general combing ability which could be used for the improvement of traits of interest 
as these lines had potential to transfer favorable genes to their progenies. 

The range of lines gca effect for 1000 kernels weight varied from -45.84 (L7) to 77.36 (L21). Inbred lines L11, 
L14, L21 and L22 had positive and significant line gca effects, while L2, L7, L9, L13, L15 and L19 showed negative 
and significant line gca effects. Hence, L11, L14, L21 and L22 were good general combinersand had favorable allele 
frequency for developing varieties with heavy grain weight.  

Concerning testers, FS59 was a good general combiner for grain yield, ear diameter, number of kernels row per 
ear and 1000 kernels weight. Likewise, FS67 found to be good general combiner for days to 50% silking, anthesis-
silking interval, plant height, ear height and ear position. Generally, inbred lines and testers with good general 
combiners could be utilized in the improvement of traits of interest either during hybrid or synthetic variety 
development. 
 

Table-4a.Estimates of general combining ability (gca) effect of lines and testers for yield and yield related traits 
across two locations, 2017. 

Lines GY 
t/ha 

AD 
days 

SD 
days 

ASI 
days 

PH 
cm 

EH 
cm 

EPO 
ratio 

L1 0.45 -2.05** -2.26** -0.30 10.26* 7.72** 0.01 
L2 -0.30 -1.06 -1.01 0.13 -15.83** -11.77** -0.01 
L3 -1.31** 2.57** 3.49** 1.06* -5.15 -3.65 0.00 
L4 -0.08 -2.05** -1.64* 0.85 10.30* 2.10 -0.02 
L5 0.72 -2.81** -2.39** -0.08 27.22** 11.86** -0.01 
L6 -0.64 -0.68 -1.51* -0.83 -2.32 1.71 0.01 
L7 -0.86* 2.70** 2.99** 0.23 -5.81 4.72 0.04** 
L8 -0.07 -0.17 0.61 0.74 -10.37* -8.79** -0.02 
L9 0.39 -2.30** -2.89** -0.57 1.82 -9.02** -0.04** 
L10 0.68 1.57* 1.61* 0.05 13.92** 8.72** 0.00 
L11 1.50** 1.58* 1.24 -0.29 3.97 8.97** 0.03* 
L12 0.37 1.95** 0.61 -1.41** 9.59* 21.11** 0.06** 
L13 -1.57** 1.95** 2.11* 0.13 -14.11** -13.40** -0.02 
L14 0.31 2.32** 2.74** 0.47 13.19** 5.97* 0.00 
L15 1.26** 0.33 0.86 0.49 3.42 4.83 0.01 
L16 0.05 -0.68 -0.89 -0.24 6.50 11.37** 0.03* 
L17 -0.08 -1.18 -1.39* -0.26 7.62 6.10* 0.01 
L18 -0.78* -1.55* -1.64* -0.11 -16.52** -8.65** 0.00 

L19 -1.13** -0.31 -0.26 0.09 -20.87** -2.90 0.05** 
L20 0.22 -0.30 -0.14 0.35 -4.47 -1.27 0.00 
L21 -1.15** 0.20 -0.39 -0.64 5.51 5.22* 0.01 
L22 -0.16 1.57* 1.74** 0.28 -10.03* -12.52** -0.03* 
L23 1.64** -1.05 -1.14 -0.16 -4.89 -12.52** -0.04** 
L24 0.57 -0.56 -0.51 0.06 -2.17 -15.91** -0.06** 
SE 0.36 0.63 0.63 0.45 4.02 2.56 0.01 

Tester        
T1 0.34** 0.24 0.74** 0.51** 18.39** 13.28** 0.01** 
T2 -0.33** -0.24 -0.74* -0.51 ** -18.33** -13.28** -0.01** 
SE 0.11 0.26 0.18 0.13 1.16 0.74 0.004 

Note: **Significant (p<0.01), *significant (p<0.05), L=line, T=tester, SE= standard error, GY=grain yield, AD=anthesis days, 
SD=silking days, ASI=anthesissilking interval, PH=plant height, EH=ear height, EPO=ear position. 

 
 
 



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Table-4b. Estimates of general combining ability (gca) effect of lines and testers for yield and yield related traits 
across two locations, 2017.  

LINES EPP 
no 

EA 
scale 

EL 
cm 

ED 
cm 

KRPE 
no 

KPR 
no 

TKW 
gm 

L1 0.24** -0.26* -1.54** -0.13** -0.21 -3.02** -12.62 
L2 0.11 0.55** -0.58 -0.08 -0.44* 0.59 -24.07* 
L3 -0.05 0.06 -0.56 -0.11 0.38 -1.98** -4.06 
L4 -0.14* -0.38** 0.81* 0.16** 0.36 2.27** 4.85 
L5 0.06 -0.32* 0.29 0.02 -0.63** 0.38 1.95 
L6 0.05 -0.56** -0.41 0.09 0.35 -0.38 -8.94 
L7 -0.02 0.56** 1.05** -0.24** -0.07 0.51 -45.84** 
L8 -0.16* 0.00 0.98** 0.01 0.50* 0.91 18.04 
L9 0.16* 0.32* -1.64** 0.03 0.37 -2.14** -26.96** 
L10 -0.05 -0.44** 0.92** 0.27** 0.48* 1.02 7.06 
L11 0.05 0.62** -1.34** 0.19** 0.54* -0.30 31.41** 
L12 0.04 0.18 0.73* 0.11* -0.12 1.20 29.04** 
L13 -0.19** 0.06 -1.71** 0.10 -0.07 -0.75 -21.20* 
L14 0.02 -0.13 0.97** 0.11* 0.54* 0.57 -12.61 
L15 0.01 -0.32* 2.06** 0.06 0.39 2.10** -21.46* 
L16 0.05 0.25 -0.44 -0.11* -0.66** -0.48 -15.47 
L17 0.03 0.05 -0.08 -0.16** -0.83** -1.23 12.36 
L18 -0.37** -0.38** 0.19 0.10 -0.01 0.50 -3.44 
L19 -0.13 -0.01 -0.85* -0.21** 0.18 -0.02 -35.00** 
L20 -0.18** 0.06 0.42 0.20** 0.78** 0.73 14.49 
L21 -0.19** 0.06 0.04 0.13** -0.64** -1.06 77.36** 
L22 0.07 0.12 0.16 -0.22** -0.65** -0.83 22.73* 
L23 0.40** 0.00 -0.27 -0.15** -0.27 0.64 3.06 
L24 0.15* -0.12 0.82* -0.18** -0.31 1.19 9.30 
SE 0.06 0.13 0.32 0.05 0.21 0.70 10.12 

Tester        
T1 0.03 -0.02 0.06 0.04** 0.26** 0.25 -13.33** 
T2 -0.03 0.02 -0.06 -0.04** -0.26** -0.21 13.33** 
SE    0.02 0.06  2.92 

Note: **Significant (p<0.01), *significant (p<0.05), L=line, T=tester, SE= standard error, EPP=ear per plant EA=ear aspect 
EL=ear length ED=ear diameter, KRPE=kernel rows per ear, KPR=kernels per rows, TKW=thousand kernels weight. 

 

3.4. Specific Combining Ability Effect 
Estimates of specific combining ability (sca) effects for grain yield and yield related traits for all hybrids computed 

across locations are presented in Table 5aand 5b. Crosses L2 x T1 (1.03), L3 x T1 (1.04), L8 x T1 (1.10), L11 x T1 
(1.14), L13 x T2 (1.64) and L23 x T1 (1.64) are exhibited significant positive sca effects for grain yield. Crosses like L2 
x T2 (-1.03), L3 x T2 (-1.04), L8 x T2 (-1.10), L11 x T2 (-1.14), L13 x T1 (-1.64) and L23 x T2 (-1.64) found to be 
poor specific combiners which could be due to the presence of unfavorable gene combinations in the parents. The 
positive sca effects indicate lines were from opposite heterotic group, while negative sca affects refer lines were from 
the same heterotic group. For instance, cross L2 x T1 showed significant positive sca effect, but had lower grain yield 
than standard checks. The high positive and significant sca effects were manifested by crosses of low x low (L13 x T2 
and L3 x T2), low x high (L2 x T1 and L8 x T1) and high x high (L23 x T1, L11 x T1), indicating the presence of 
complementary gene action for grain yield. Inbred lines L3, L2, L13 and T2 had poor general combining ability, but 
resulted in hybrids with higher sca effects for grain yield. This signifies that inbred lines with poor general combining 
ability might produce better hybrids depending on the other parent with which it combines. 

The sca effects of days to 50% anthesis (AD) and silking (AD) ranged from -1.98 (L16 x T1) to 1.98 (L16 x T1) 
and -2.14 (L21 x T2) to 2.14 (L22 x T1), respectively. Crosses such as L13 x T2, L16 x T1 and L21 x T2 revealed 
negative and significant sca effects for days to 50% anthesis and silking, while L13 x T1, L16 x T2 and L21 x T1 
showed positive sca effects. Crosses with negative and significant sca effects for these traits are considered as good 
specific combiners, which indicate the earliness of the hybrids. On the other hand, crosses with positive and significant 
sca effects were found to be poor specific combiners, mainly for highland condition due to lateness. Inbred lines with 
negative and significant gca effects did not necessarily produced crosses with negative and significant sca effects. But, 
tester FS59 had negative and significant gca effect and interacted well with L21 and L13 in cross combination thereby 
resulted in crosses with negative and significant sca effects. The interactions involved in the crosses were poor x good 
general combiners (L13 x T1 and L21 x T1) and poor x poor (T16 x T2). 

Crosses L9 x T1, L16 x T2 and L21 x T1 had negative and significant sca effects for plant and ear height 
considered as good specific combinations. These crosses involved parents with general combiners of good x poor, 
poor x good and poor x poor gca effects. L13 x T2, L16 x T1 and L21 x T2 for plant height and L9 x T2, L10 x T1, 
L12 x T2, L16 x T2 and L21 x T1 for ear height showed positive and significant sca effects, indicating that these 
crosses were poor specific combination for these traits. Accordingly, good specific combination could be utilized in 
developing lodging resistance hybrids. Positive sca effects for plant and ear height indicates crosses had tendency to 
increase height in undesirable direction.  

Crosses L8 x T1 for number of ears per plant, L9 x T1, L10 x T2 and L14 x T1 for ear length and L11 x T2 for 
number of kernels per row had significant and positive sca effects. The crosses involved parent interaction of poor x 
poor, good x poor and good x poor based on their gca effects. L8 x T2 for number of ears per plant, L9 x T2, L10 x 
T1 and L14 x T2 for ear length and L11 x T1 for number of kernels per row showed significant and negative sca 
effects. The crosses exhibiting significant and positive sca effects are considered as good specific combiners. The 
crosses that showed significant and negative sca effects found to be poor specific combiners. Moreover, crosses with 
positive and significant sca effects had inbred lines with positive (L10 and L14) and negative (L9) gca effect.  



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Finally, based on the gca effects of parents, and sca effects hybrids for different traits, it is evident that high 
specific combinations involved, Inbred lines with high x high, high x low and low x low gca effects. The sca effects of 
crosses combinations exhibited no specific trends in cross combinations between parents having good and poor gca 
effects. This indicates high specific combiners were not only obtained from the combination of good x good general 
combiners, but also resulted from good x poor and poor x poor general combiners. The superiority of hybrids resulted 
from the crosses of high x low combiners could be due to interactions between positive alleles and negative alleles 
from good and poor combiners, respectively. The best performance of these combination may be caused by additive x 
additive (high x high), additive x dominance (high x low), or dominance x dominance (low x low) gene interactions 
Dey, et al. [47]; Talukder, et al. [48]. Zhang, et al. [49] suggested that hybrids with high sca effects from parents 
with low gca effects might be primarily due to non-additive gene action which includes dominance and epistasis. For 
some of the studied traits, high gca effect parents resulted into hybrids with low sca effect which might be due to the 
lack of complementary of gene action. On the other hand, lowgca effect parents produced hybrids with high sca effects 
which might be caused by complementation of gene actions. Generally, the crosses identified were best specific 
combiners for yield and yield related traits which can be used in the heterosis breeding. 
 

Table-5a.Estimates of specific combining abilities of line x tester for yield and yield related traits across two location, 2017. 

S/N CODE GY 
t/ha 

AD 
days 

SD 
days 

PH 
cm 

EH 
cm 

EPP 
no 

1 L1xT1 -0.14 -0.11 0.01 -0.91 2.22 -0.03 
2 L1xT2 0.13 0.11 -0.01 0.85 -2.22 0.03 
3 L2xT1 1.03* 1.12 0.26 1.86 -4.52 -0.02 
4 L2xT2 -1.03* -1.12 -0.26 -1.93 4.52 0.02 
5 L3xT1 -1.04* -0.12 -0.24 -4.16 -2.41 -0.01 
6 L3xT2 1.04* 0.12 0.24 4.09 2.41 0.01 
7 L4xT1 -0.17 0.03 -0.11 -4.46 -0.63 0.09 
8 L4xT2 0.17 -0.03 0.11 4.40 0.63 -0.09 
9 L5xT1 0.30 0.39 -0.11 -3.85 0.34 -0.07 
10 L5xT2 -0.31 -0.39 0.11 3.78 -0.34 0.07 
11 L6xT1 0.56 0.02 -0.74 -3.13 -4.54 0.00 
12 L6xT2 -0.56 -0.02 0.74 3.06 4.54 0.00 
13 L7xT1 -0.58 -0.85 -0.24 2.10 -2.03 -0.13 
14 L7xT2 0.58 0.85 0.24 -2.17 2.02 0.13 
15 L8xT1 1.10* 0.01 0.14 7.63 2.97 0.26** 
16 L8xT2 -1.10* -0.01 -0.14 -7.70 -2.97 -0.26** 
17 L9xT1 0.18 -0.86 -0.11 -10.57** -9.27** 0.05 
18 L9xT2 -0.18 0.86 0.11 10.51** 9.27** -0.05 
19 L10xT1 -0.72 0.76 0.89 5.60 7.72* -0.03 
20 L10xT2 0.72 -0.76 -0.89 -5.66 -7.72* 0.03 
21 L11xT1 1.14** 0.00 0.51 4.01 2.48 0.01 
22 L11xT2 -1.14 0.00 -0.51 -4.07 -2.48 -0.01 
23 L12xT1 0.34 0.64 0.89 2.29 12.86** 0.03 
24 L12xT2 -0.34 -0.64 -0.89 -2.36 -12.86** -0.03 
25 L13xT1 -1.64** 1.88* 1.89* -11.57** -5.67 -0.04 
26 L13xT2 1.64** -1.88* -1.89* 11.51** 5.66 0.04 
27 L14xT1 0.55 -0.23 -0.49 4.36 3.48 0.08 
28 L14xT2 -0.55 0.23 0.49 -4.43 -3.48 -0.08 
29 L15xT1 -0.04 0.76 0.14 1.56 2.61 -0.06 
30 L15xT2 0.04 -0.76 -0.14 -1.63 -2.61 0.06 
31 L16xT1 0.94 -1.98* -2.11* 14.87** 9.61** -0.05 
32 L16xT2 -0.94 1.98* 2.11* -14.93** -9.61** 0.05 
33 L17xT1 -0.73 -0.27 -0.11 4.03 0.09 -0.15 
34 L17xT2 0.72 0.27 0.11 -4.09 -0.09 0.15 
35 L18xT1 0.53 -0.87 0.39 9.55 2.35 0.00 
36 L18xT2 -0.53 0.87 -0.39 -9.62 -2.35 0.00 
37 L19xT1 0.03 -0.86 -1.24 -5.79 -4.90 0.04 
38 L19xT2 -0.03 0.86 1.24 5.72 4.90 -0.04 
39 L20xT1 0.29 -0.88 -1.11 7.64 1.97 0.10 
40 L20xT2 -0.30 0.88 1.11 -7.70 -1.97 -0.10 
41 L21xT1 -0.56 1.62* 2.14* -12.70** -8.02* -0.11 
42 L21xT2 0.56 -1.62* -2.14* 12.63** 8.02* 0.11 
43 L22xT1 -0.17 1.03 0.76 3.72 -5.26 0.09 
44 L22xT2 0.17 -1.03 -0.76 -3.79 5.26 -0.09 
45 L23xT1 1.64** -0.37 -0.86 -4.70 0.96 0.06 
46 L23xT2 -1.64** 0.37 0.86 4.64 -0.97 -0.06 
47 L24xT1 -0.87 -0.87 -0.49 -8.17 -2.41 -0.08 
48 L24xT2 0.87 0.87 0.49 8.11 2.41 0.08 

SE(d)  0.52 0.89 0.89 5.69 3.23 0.09 
Note: **Significant (p<0.01), *significant (p<0.05), SE= standard error, GY=grain yield, AD=anthesis days, SD=silking days, PH=plant height, 
EH=ear height,  

 
 
 
 
 
 



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Table-5b.Estimates of specific combining abilities of line x tester for yield and yield related traits across two location, 2017. 

S/N CODE EA 
scale 

EL 
cm 

KPR 
no 

S/N CODE EA 
scale 

EL 
cm 

KPR 
no 

1 L1xT1 0.02 -0.45 0.73 25 L13xT1 -0.05 -0.42 0.60 
2 L1xT2 -0.01 0.45 0.73 26 L13xT2 0.05 0.42 -0.60 
3 L2xT1 -0.04 0.27 -0.21 27 L14xT1 -0.10 1.03* 1.54 
4 L2xT2 0.04 -0.27 0.21 28 L14xT2 0.10 -1.03* -1.54 
5 L3xT1 -0.05 0.26 0.16 29 L15xT1 -0.05 -0.80 0.52 
6 L3xT2 0.05 -0.26 -0.16 30 L15xT2 0.05 0.80 -0.52 
7 L4xT1 0.02 -0.13 0.08 31 L16xT1 -0.11 0.27 0.42 
8 L4xT2 -0.02 0.13 -0.8 32 L16xT2 0.11 -0.27 -0.42 
9 L5xT1 -0.42* -0.03 0.22 33 L17xT1 -0.04 0.75 0.91 
10 L5xT2 0.42* 0.03 -0.22 34 L17xT2 0.04 -0.75 -0.91 
11 L6xT1 0.08 0.09 0.13 35 L18xT1 0.02 0.14 1.08 
12 L6xT2 -0.08 -0.09 -0.13 36 L18xT2 -0.02 -0.14 -1.08 
13 L7xT1 0.08 0.18 -1.08 37 L19xT1 0.02 0.03 1.48 
14 L7xT2 -0.08 -0.18 1.08 38 L19xT2 -0.02 -0.03 -1.48 
15 L8xT1 -0.23 -0.03 -0.01 39 L20xT1 -0.29 -0.22 0.65 
16 L8xT2 0.23 0.03 -0.01 40 L20xT2 0.29 0.22 -0.65 
17 L9xT1 0.21 1.25** 1.76 41 L21xT1 0.08 -0.55 -1.04 
18 L9xT2 -0.21 -1.25** -1.76 42 L21xT2 -0.08 0.55 1.04 
19 L10xT1 0.08 -0.99* -0.96 43 L22xT1 -0.10 -0.08 -0.99 
20 L10xT2 -0.08 0.99* 0.96 44 L22xT2 0.10 0.08 0.999 
21 L11xT1 0.27 -0.84 -2.39* 45 L23xT1 0.02 0.10 -1.13 
22 L11xT2 -0.27 0.84 2.36* 46 L23xT2 -0.02 -0.10 1.13 
23 L12xT1 0.45* -0.24 -0.50 47 L24xT1 0.15 0.39 -0.69 
24 L12xT2 -0.45* 0.24 0.50 48 L24xT2 -0..15 -0.39 0.69 
SE      0.18 0.46 0.99  

Note: ** highly significant (p<0.01),*significant (p<0.05), EA=ear aspect, EL=ear length, ED=ear diameter, KRPE=kernel rows per ear, 
KPR=kernels per rows, TKW=thousand kernels weight. 

 

4. Conclusion 
Analysis of variance revealed the presence of significant variation among the genotypes for all studied traits 

except for plant aspect. Mean square of entry x location interaction for most of studied traits showed non-
significant, indicating that hybrid performance was consistent across locations. Nevertheless, genotype x location 
interaction was significant for some traits, suggesting further evaluation of selected genotypes over a number of 
locations. Mean squares of GCA and SCA were significant for most of studied traits, implying that both additive 
and non-additive gene action were involved in the control of the inheritance of these traits. However, the 
proportional contribution of GCA effect was higher and GCA/SCA ratio was greater than unit for all studied 
traits, suggesting that additive gene action was more important than non-additive gene action for these traits.  

Estimation of gca and sca effects identified lines and crosses with good general and specific combiners for 
studied traits respectively. Inbred lines L23, L11 and L15 for grain yield, L1, L9, L23 and L24 for number of ears 
per plant, L8, L14 and L15 for ear length, L8, L14 and L20 for number of kernels row per ear and L4 and L15 for 
number of kernels per row were the top good general combiners for the respective traits. Crosses such as L11xT1, 
L13xT2 and L23xT1 for grain yield, L6xT2 for number of ear per plant, L9xT1, L10xT2 and L14xT1 for ear 
length and L11xT2 for number of kernels per row revealed good specific combining ability. Finally, better 
performing testcrosses, inbred lines with desirable gca effects and cross combinations with desirable sca effects for 
grain yield and yield related traits could be used as source of useful genetic material for future maize breeding. 
 

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Appendix  
 

Appendix-1.Analysis of variance for grain yield and yield related traits of 50 maize genotypes evaluated at Ambo, 2017. 

Traits Rep(df=1) Blk(rep)df=18 Entry(df=49) Error df=31 Mean CV % 

GY 0.06 0.904 4.26** 1.19 7.74 14.08 
AD 16.0* 1.01 6.23* 3.38 96.10 1.91 

SD 13.69 2.75 9.63** 3.9 95.53 2.07 

ASI 0.0002 0.003 0.008** 0.002 1.1 4.24 

PH 501.76 224.06 776.49** 207.71 207.71 5.70 

EH 272.25* 32.20 399.64** 50.28 142.01 4.99 

EPO 0.00004 0.001 0.002 0.003 0.56 9.17 

EPP 0.01 0.027 0.094** 0.029 1.62 10.47 

EA 0.12 0.059 0.20** 0.095 3.056 7.66 

PA 0.49 0.16 0.19 0.18 3.42 12.52 

EL 8.82** 1.01 2.51** 1.09 15.37 6.78 

ED 0.004 0.04 0.07** 0.03 4.41 4.05 

KRPE 0.37 0.93** 0.56 0.35 12.63 4.68 

KPR 6.35 8.97 7.20** 5.68 32.56 7.32 

TKW 22.37 987.20 3282.45** 1024.25 336.13 7.52 
Note: **Significant (p<0.01),*significant (p<0.05), Rep=replication, Blk=block, CV=correlation variation. 

 
Appendix I2. Analysis of variance for grain yield and yield related traits of 50 maize genotypes evaluated at Holetta, 2017. 

Traits Rep(df=1) Blk(rep)df=18 Entry(df=49) Error df=31 mean CV% 

GY 0.006 1.67 3.12** 1.01 7.33 13.73 
AD 32.49 ** 4.91 11.19** 2.98 112.93 1.53 

SD 25.0** 2.43 10.23** 2.71 114.76 1.44 

ASI 0.001 0.006 0.004* 0.006 1.22 6.37 

PH 1056.25** 99.13 1136.63** 70.54 249.37 3.37 

EH 524.41** 57.88 650.52** 59.0 131.31 5.85 

EPO 0.0003 0.0004 0.002** 0.0005 0.52 4.35 

EPP 0.004 0.03 0.08** 0.04 1.79 10.5 

EA 1.69** 0.20 0.44** 0.21 3.18 14.33 

PA 1.0* 0.14 0.17 0.22 3.18 14.9 

EL 8.82** 0.95 2.53** 0.53 15.56 4.70 

ED 0.004 0.01 0.08** 0.02 4.23 3.59 

KRPE 0.79 0.34 1.17** 0.39 13.08 4.79 

KPR 44.08** 5.87* 7.92** 2.74 31.94 5.19 

TKW 32.15 498.92 1742.34* 870.39   

      Note:  **Significant (p<0.01),*significant (p<0.05), Rep=replication, Blk=block, CV=correlation variation. 
 

Appendix-3.Mean squares, and proportional  contribution of lines, tester and line x tester of yield and yield related 
traits 48 maize testcross at Ambo, 2017. 

Source DF GY AD SD ASI PH EH EPO 

Rep 1 0.03 15.84* 12.76 0.11** 408.38 260.04* 0.0013 

Cross 47 4.76** 6.49** 10.89** 2.81(0.009)** 902.75** 511.62** 0.0025** 

Line 23 6.23** 9.73** 13.11** 1.95(0.006) 687.48* 422.09** 0.003 

Tester 1 0.09 3.76 98.01** 59.32(0.18)** 19877.41** 10922.67** 0.0047 

Line x 
Tester 

23 3.48** 3.37 4.88 1.20(0.004) 293.04 148.49** 0.002* 

Error 29 1.01 2.57 3.61 0.77(0.002) 211.96 44.85 0.0008 

Proportion contribution 
(%) 

 
 

      

Line  64.12 73.36 58.91 34.07 37.27 40.37 58.44 

Tester  0.04 1.23 19.15 44.98 46.85 45.42 3.92 

Line x 
Testers 

 35.84 25.41 21.93 20.95 15.89 14.2 37.65 

 
 

 EA ED EL EPP KRPE KPR TKW 

Rep 1 0.09 0.01 6.48** 0.01 0.06 0.68 7.23 

Cross 47 0.22** 0.07** 2.66** 0.11** 0.65* 7.18 3590.20** 

Line 23 0.28 0.12** 4.48** 0.16** 0.73* 7.54 3535.40** 

Tester 1 0.67** 0.01 0.44 0 2.62** 9.01 57934.13** 

Line x 
Tester 

23 0.15* 0.02 0.93 0.06 0.27 6.73 1282.22 

Error 29 0.06 0.03 1.06 0.03 0.36 5.04 857.51 

Proportion contribution 
(%) 

 
 

      

Line  60.68 88.45 82.47 74.35 65.43 51.45 48.19 

Tester  6.36 0.33 0.36 0 10.19 2.67 34.33 

Line x 
Testers 

 32.97 11.22 17.18 25.65 24.38 45.88 17.48 

Note: **Significant (p<0.01), *significant (p<0.05), GY=grain yield, AD=anthesis days, SD=silking days, ASI=anthesissilking interval, 
PH=plant height, EH=ear height, EPO =ear position, EPP=ear per plant, EA=ear aspect, EL=ear length, ED=ear diameter, 
KRPE=kernel rows per ear, KPR=kernels per rows, TKW=thousand kernels weight. 

 



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Appendix-4.Mean squares, and proportional  contribution of lines, tester and line x tester of yield and yield related traits of 
48 maize testcross Holetta, 2017. 

Source DF GY AD SD ASI PH EH EPO 

Rep 1 0.05 15.66** 25.01** 0.55 247.00** 320.26** 0.0005 

Cross 47 3.05** 10.57** 11.73** 2.04 1226.24** 755.60** 0.0024* 

Line(GCA) 23 2.96** 15.71** 17.24** 1.67 587.61** 434.46** 0.0032** 

Tester(GCA) 1 37.79** 3.32 21.09** 3.43 39148.12** 22634.84** 0.0241** 

Line x Tester(SCA) 23 1.63 5.74 5.81* 2.34 216.10** 125.48* 0.0007 

Error 29 0.97 3.1 2.71 2.50 46.94 55.52 0.0005 

Proportional contribution (%) 
 
 

      

Line  47.5 72.75 71.93 40.11 23.45 28.14 64.69 

Tester  26.35 0.01 3.83 3.58 67.93 63.74 21.43 

Line x Testers  26.15 26.58 24.25 56.31 8.62 8.13 13.88 

  EA ED EL EPP KRPE KPR TKW 

Rep 1 1.17** 0 4.70** 0.001 0.54 10.54 23.21 

Cross 47 0.50* 0.09** 3.17** 0.09* 1.48** 8.45** 2074.04** 

Line(GCA) 23 0.70** 0.09** 4.09 0.11* 1.55** 11 3015.38* 

Tester(GCA) 1 1.27** 1.02** 3.56 0.38** 12.98** 1.27 229.4 

Line x Tester(GCA) 23 0.26 0.04* 2.23** 0.05 0.91* 6.22* 1212.9 

Error 29 0.2 0.02 0.6 0.04 0.36 2.81 745.02 

Proportional contribution (%)       

Line  69.15 51.46 63.17 62.95 51.22 63.69 71.15 

Tester  5.44 25.17 2.39 9.46 18.69 0.89 0.24 

Line x Testers  25.41 23.36 34.44 27.59 30.1 36 28.62 

Note: **Significant (p<0.01), *significant (p<0.05), GY=grain yield, AD=anthesis days, SD=silking days, ASI=anthesissilking interval, PH=plant height, EH=ear height, 
EPO =ear position, EPP=ear per plant, EA=ear aspect, EL=ear length, ED=ear diameter, KRPE=kernel rows per ear, KPR=kernels per rows,  TKW=thousand  kernels 
 weight. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 
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