Journal of Plant Production Estimation of Genetic Variability Using Line X Tester Technic in Yellow Maize and Stability Analysis for Superior Hybrids Using Different Stability Procedures

Abstract

Fifteen inbred lines were crossed to three testers of maize to estimate combining ability effects for maturity and yield traits. The produce 45 crosses, S.C. 168 and T.W.C. Giza 368 were evaluated across two years at the Farm of Faculty of Agriculture, Moshtohor, Benha University in RCBD with 3 replicates. Mean squares due to year (Y) genotypes (G), crosses (C), testers (T), inbred lines (L), line x tester (LxT) and interaction variance for C, L, T and LxT with (S) were significant (P>0.05) for most studied traits. Non-additive gene action (δ 2 SCA) is more pervading in determining inheritance of the most traits. The non-additive type of gene action is fluctuated by year changed more than additive. The inbred lines M. 645a (L4), M. 653 (L5), and M. 674 (L11) showed desirable ĝi for early maturity and grain yield plant-1. The crosses M.221xM.653, M.221xM.655b, M.221xM.657, M.221xM.671, M.221xM.674 and M.221xM.677 exhibited out-yielded SC 168 reached 9.96%, 11.35%, 12.53%, 8.32%, 11.80% and 4.80%, respectively across years. TWC (SC M 200xM418)xM.653 and (SC M200xM418)xM.674 showed superiority than TWC 368 being 9.11% and 3.78%, respectively. The eight superior hybrids along with SC168, SC hytech 2066, TWC 368 and TWC 352 were evaluated in 2019 year at various environments using RCBD with 3 replicates to identify suitable adapted maize hybrids. The main effects of genotypes, environments and their GxE interaction were highly significant (P<0.01). Hybrids M. 221 x M. 674, M. 221 x M. 655b, SC hytech 2066 and SC 168 were the most crosses stable phenotypically and genetically across environments.

Full text

J. of Plant Production, Mansoura Univ., Vol. 11 (9):847-854, 2020
Journal of Plant Production
Journal homepage: www.jpp.mans.edu.eg
Available online at: www. jpp.journals.ekb.eg
* Corresponding author.
E-mail address: ahmed.alhossary@fagr.bu.edu.eg
DOI:
Estimation of Genetic Variability Using Line X Tester Technic in Yellow
Maize and Stability Analysis for Superior Hybrids Using Different Stability
Procedures
El-Hosary, A. A. A.
*
Department of Agronomy, Faculty of Agriculture, Benha University, Egypt
Cross Mark
ABSTRACT
Fifteen inbred lines were crossed to three testers of maize to estimate combining ability effects for
maturity and yield traits. The produce 45 crosses, S.C. 168 and T.W.C. Giza 368 were evaluated across two years
at the Farm of Faculty of Agriculture, Moshtohor, Benha University in RCBD with 3 replicates. Mean squares
due to year (Y) genotypes (G), crosses (C), testers (T), inbred lines (L), line x tester (LxT) and interaction variance
for C, L, T and LxT with (S) were significant (P0.05) for most studied traits. Non- additive gene action (δ2SCA)
is more pervading in determining inheritance of the most traits. The non-additive type of gene action is fluctuated
by year changed more than additive. The inbred lines M. 645a (L4), M. 653 (L5), and M. 674 (L11) showed
desirable ĝi for early maturity and grain yield plant-1. The crosses M.221xM.653, M.221xM.655b,
M.221xM.657, M.221xM.671, M.221xM.674 and M.221xM.677 exhibited out-yielded SC 168 reached 9.96%,
11.35%, 12.53%, 8.32%, 11.80% and 4.80%, respectively across years. TWC (SC M 200xM418)xM.653 and
(SC M200xM418)xM.674 showed superiority than TWC 368 being 9.11% and 3.78%, respectively. The eight
superior hybrids along with SC168, SC hytech 2066, TWC 368 and TWC 352 were evaluated in 2019 year at
various environments using RCBD with 3 replicates to identify suitable adapted maize hybrids. The main effects
of genotypes, environments and their GxE interaction were highly significant (P<0.01). Hybrids M. 221 x M.
674, M. 221 x M. 655b, SC hytech 2066 and SC 168 were the most crosses stable phenotypically and genetically
across environments.
Keywords: Combining ability, GCA, Inbred lines, SCA, Testers and Yellow Maize.
INTRODUCTION
Successful development of improved corn hybrids is
depending upon precise evaluation of genotypes under selection.
Inbred lines performance per se does not extend an entirely
suitable measure of their value in the line x tester crosses. Thus,
development of simple but effective method of evaluating new
inbred lines has been a major dilemma in the development of new
hybrids. Line x tester analysis has become a standard procedure
for evaluating both types of combining ability (GCA and SCA)
of parental inbred lines to be used in cross combinations.
However, there has been much controversy over the choice of
appropriate tester.
The line x tester procedure with using different tester's
base (narrow and broad) is the most prevalent method for the
evaluating process. A wished tester described as give ultimate
output on the predictable performance from the tested lines.
Also, it combines the more simplicity utilization when used in
other crosses or grown in various environments. No unique
tester is able to completely fulfill these purposes.
There were unsolved problem that, chose the kind base
of testers used in line x tester schema for assess inbred lines is still
confused. Therefore, the choice of desirable tester is a serious
decision. Utilization of low yielding variety carrying recessive
factors for traits of economic interest should be used as a tester
parent. But, the masking dominat desirable allels effect in such
testers is making them ineffective. While, use of high yielding
single crosses or elite inbred lines is useful for produce new three
way crosses and single crosses, respectively. Also, assess of the
top crosses gave a better idea SCA of the inbred lines. Matzinger
(1953) reported that a narrow tester's genetic base participate
more to line x tester interaction than does a large bases one. On
the other hand, Grogan and Zuber (1957) illustrated that some
double crosses like single crosses in effective for measuring
GCA. El-Hosary (2014) estimated the relative value of various
testers and found the small bases teeter like inbred line or single
cross is more important in evaluating inbred line than open
pollinated population. Sprague (1939) mentions that early testing
for efficient test of inbred lines depend on bases of testers needed.
The essential final stage in most applied plant breeding
programs is the evaluation of promising hybrids over diversified
environments (years and locations). Grain yield plant-1 of crosses
as quantitative inherited trait, often differ from environment to
other one thus, a significant hybrid x environment (GxE)
interaction will detected. Understanding the interaction of those
factors and how they affect grain yield plant-1 is crucial for
maintaining new high yield and stable crosses. A hybrid with high
mean is considered stable if it has low fluctuations under various
environments. Many investigators reported the importance of
GxE interaction in stability analysis of maize i.e., Sowmya et al.
(2018), Arunkumar, et al. (2020) and El-Hosary (2020).
Various statistical methods (parametric and non-
parametric) are proposed to measure stability by modeling the
GxE interaction. However, the widely used methods are those
based on regression models, variance components and
multivariate analysis. The popular stability forms of regression

El-Hosary, A. A. A.
848
statistics was proposed by Eberhart and Russell (1966) and Tai
(1971). According to the regression procedure, the stability is
extrapolates two parameters being slope regression line and
the deviation from regression.
The ultimate goal of this study were to give an insight
in the choice of desirable tester for evaluating inbred lines and
determined superior inbred lines of maize, estimate GCA and
SCA of the testers and inbred line and identify superior hybrid
with high yield potentials and stability across various.
MATERIALS AND METHODS
The parental materials in this concern consisted of three
various testers (males) i.e.: open-pollination population (Sakha
pop.), a promising high yield single cross M 200 x M 418, and an
elite of combining abilities inbred line M 221 as well as new 15
yellow inbred lines (females) in S7 i.e. (Moshtohor) M. 601 (L1),
M. 603c (L2), M. 642 (L3), M. 645a (L4), M. 653 (L5), M. 655b
(L6), M. 657 (L7), M. 658A (L8), M. 671 (L9), M. 673 (L10),
M. 674 (L11), M. 675a (L12), M. 677 (L13), M. 678 (L14) and
M. 682r (L15). The fifteen females were crossed with the three
testers in line x tester program at the 2016 summer season to
produce 45 crosses combinations. Across two years of 2017 and
2018, the 45 test crosses and 2 various check hybrids single cross
168 (SC 168) and three way cross 368 (TW 368) were arranged
in a randomized complete block design (RCBD) with three
replications to determine the best parent and combinations.
The sowing dates were 6th June and 16th June in 2017
and 2018 seasons, respectively at farm of the Faculty of
Agriculture, Moshtohor, Benha University. Each entry
consisted of one 6-m long ridge with a 25 x 70 cm plant
density. Agriculture practices of maize growing were followed
according to the last recommendations.
Statistics were taken on a random sample of 15 guarded
plants in each plot; days to maturity (day), plant height (cm), ear
height (cm), number of rows ear-1, number of kernels row-1, 100-
kernel weight (g) and grain yield plant-1(g) (adjusted to 15.5%
moisture content). ANOVA in each and across the two seasons
was made. Further, combined analysis was not performed until
after testing the homogeneity of errors in two years. Combining
ability analysis was computed according the procedure
developed by Kempthorne (1957). All parents except SK Pop
were planted in 1st August 2018 to recombine the elite hybrids
which superior relative to check hybrids in the previous
experiment and to obtain a sufficient amount of grains. The elite
hybrids along with four check hybrids (SC168, SC hytech 2066,
TW 368 and Tw 352) were assessed in eight trials i.e. four
governorate 1) El-Dakahlya (Mansoura) – 2) El-Menofya (Tala)
– 3) Baneswif (Sids) - 4) El-Qaluobya (Moshtohor) under
different planting date in each location of season 2019 (Table 1).
The first planting date was 23, 22, 25 and 22 May and the second
one was 13, 12, 15 and 15 Jun for the mention trails, respectively.
In each trial the eight promising crosses (6 SC and 2
TWC) along with four check hybrids were evaluated in a
RCBS with three replicates. The planting dates were illustrated
in each environment in table 1.
Table 1. Planting dates at each location of season 2019.
Locations
First planting date
Second plant date
El-Mansoura (El-Dakahlya)
23/5/2019
13/6/2019
Tala (El-Menofya)
22/5/2019
12/6/2019
Sids (Baneswif)
25/5/2019
15/6/2019
Moshtohor (EL-Qaluobya)
22 /5 / 2019
12/ 6/ 2019
Each plot consisted of four ridges of 4 m length and 70
cm width. Hills were spaced at 25 cm apart with two grains per
hill on one side of the ridge. Dry method of planting was used
in this concern. The seedlings were minimized to one seedling
hill-1. The cultural practices were allowed as usual for ordinary
maize fields in these locations. The grain yield plant-1 was
recorded as an average of 20 graded plants from the two
middle rows of each plot. Analysis of variance of RCBD as
outlined by Gomez and Gomez (1984) was conducted for each
environment. Bartelett test (1937) was performed prior to the
combined analysis to test the homogeneity of error terms
indicating the homogeneity of variances. The regression
approach comprised two stability methods that were described
by Eberhart and Russell (1966) and Tai (1971)
RESULTS AND DISCUSSION
Table 2 showed that significant (P 0.01) mean
squares due years (Y), genotype (G) and GxY interaction were
detected for all studied traits, indicating change in years has
obvious effects on the studied traits. Furthermore, genotypes
performance influences significantly by change in years and
the possibility of selecting genotypes that stable across years
and exclude the unstable one. Also, Table (3) crosses and its
partitioning of crosses mean squares into inbred lines (L),
testers (T) and line x tester (LxT) were significant for all
studied traits of each year and across the them except T for no
of rows ear-1, and LxT for 100-kernel weight in the first year,
revealing a wide range of variability among parental tester
(males), inbred lines (females), and that the lines performed
differently according to the tester which they crossed.
Table 2. Mean squares for the studied traits at both and across years of 2017 and 2018 this analysis involved line x tester
crosses and two check hybrids.
S.O.V.
df
days to maturity
(day)
plant height
(cm)
Ear height
(cm)
No of rows
ear-1
no of kernels
row-1
100 kernel
weight (g)
grain yield
plant-1 (g)
First year of 2017
Rep
2
1.16
94.47*
21.24
0.009
0.49
1.97
57.89
Genotypes
46
13.38**
1161.546**
1272.52**
2.043**
24.11**
19.99**
3176.37**
Error
92
0.620
34.26
12.11
0.080
0.75
3.24
20.94
Second year of 2018
Rep
2
2.65
0.03
0.13
0.002
2.32
16.64**
42.15
Genotypes
46
16.50**
753.77**
1025.02**
2.01**
25.94**
19.16**
2929.50**
Error
92
0.96
28.30
22..52
0.047
0.83
2.67
15.45
Combined across years
year (Y)
1
59.29**
346.79*
7338.79**
0.67**
1938.54**
2005.33**
177901**
Rep/Y
4
1.90
47.25
10.68
0.005**
1.40
9.31
50.02
Genotypes
46
24.63**
1700.15**
1602.79**
2.36**
42.56**
30.22**
5158.5**
Genotype x Y
46
5.24**
215.17**
494.75**
1.69**
7.49**
8.93**
947.36**
Error
184
0.79
31.28
17.32
0.06
0.79
2.96
18.19
* and ** indicate significance at 0.05 and 0.01 levels of probability, respectively.

J. of Plant Production, Mansoura Univ., Vol. 11 (9), September, 2020
849
Table 3. Mean squares and combining ability analysis of line x tester for the studied traits at both and across years of
2017 and 2018.
S.O.V.
df
days to maturity
(day)
plant height
(cm)
Ear height
(cm)
No of rows
ear-1
no of kernels
row-1
100 kernel
weight (g)
grain yield
plant-1 (g)
First year of 2017
Rep
2
1.21
90.38
20.52
0.01
0.47
1.88
61.61
Crosses (c )
44
13.52**
1214.35**
1330.25**
2.14**
25.20**
20.90**
3300.31**
Line (L)
14
20.33*
2206.53**
1526.40**
2.18
45.10**
23.55**
3205.65**
Tester (T)
2
20.59*
8792.68**
12805.20**
1.99
184.03**
252.02**
39855.01**
L x T
28
9.61**
176.94**
412.54**
2.13**
3.90**
3.06
736.59**
Error
88
0.63
35.82
12.66
0.08
0.78
3.39
21.8
δ2GCA
0.05
13.21
11.68
0.04
0.27
0.23
32.64
δ2SCA
2.99
47.04
133.29
0.68
1.04
-0.11
238.26
Second year of 2018
Rep
2
2.67
0.02
0.07
0.02
2.23
15.87**
67.75**
Crosses (c )
44
14.96**
787.95**
1049.46**
2.1**
27.12**
20.03**
2832.84**
Line (L)
14
27.15**
1234.91**
1161.49
1.32*
31.97**
25.54**
1058.09*
Tester (T)
2
24.90**
5903.76**
3743.18*
27.91**
233.11**
166.57**
47208.03**
L x T
28
8.16**
199.06**
801.03**
0.64**
9.98**
6.80**
550.56**
Error
88
0.99
29.59
17.66
0.05
0.86
2.79
12.66
δ2GCA
0.09
7.5
3.16
0.02
0.22
0.17
29.06
δ2SCA
2.39
56.49
261.13
0.2
3.04
1.34
179.3
Combined across years
Year (Y)
1
71.56**
325.95**
6910.07**
0.66**
1854.26**
1923.86**
183366.69**
Rep/Y
4
1.94
45.2
10.3
0.05
1.35
8.87*
64.68**
Crosses (c )
44
23.47**
1777.36**
1683.72**
2.46**
44.49**
31.59**
5274.00**
Line (L)
14
42.69**
3030.62**
1894.49**
1.63**
67.77**
31.87**
3062.85**
Tester (T)
2
45.38**
14551.78**
13066.35**
20.57**
415.04**
393.17**
84833.17**
L x T
28
12.29**
238.26**
765.29**
1.58**
6.38**
5.63**
696.77**
CxY
44
5.01**
224.94**
695.99**
1.77**
7.82**
9.33**
859.15**
LxY
14
4.79**
410.82**
793.39**
1.87**
9.30**
17.23**
1200.89**
TxY
2
0.1
144.66*
3482.03**
9.33**
2.1
25.42**
2229.87**
LxTxY
28
5.48**
137.73**
448.29**
1.18**
7.49**
4.24
590.38**
Error
176
0.81
32.71
15.16
0.07
0.82
3.09
17.23
δ2GCA
0.64
155.8
93.07
0.09
4.39
3.51
780.12
δ2SCA
1.14
16.75
52.83
0.07
-0.18
0.23
17.73
δ2GCAxY
0.34
137.53
92.2
0.11
3.87
3.63
775.17
δ2SCA xY
1.55
35.01
144.38
0.37
2.22
0.38
191.05
* and ** indicate significance at 0.05 and 0.01 levels of probability, respectively.
Significant interaction between CxY, LxY, TxY and
LxTxY were obtained for all traits except for TxS for No of
kernels row-1 and LxTxY for 100-kerenl weight,
representative that testers, lines and crosses influenced from
year to another. Also, these results designate significant the
both types of combining ability (GCA for parent and SCA for
crosses) and an indication to the predominance of dominance
in controlling traits under study at both years and the weak
effects of additive gene action. These results are in harmony
with those obtained by EL-Hosary and EL-Gammal (2013),
Bayoumi (2018), El-Hosary (2020) and Ismail et al (2020).
However, Amer and El-Shenawy (2007) reported that
significant interactions (P 0.01) between treatments, lines
(L) and testers (t) for earliness and grain yield plant-1. El-
Morshidy et al. (2003) reported that lines were stable much
more by change in environment than tester.
The estimates of variances due to GCA, SCA and
their interactions with years (Table 3) showed that δ2SCA
played the major role in determining the inheritance of all
studied traits except 100-kernel weight at the first year and the
combined across year, revealing that the largest part of the
total genetic variability associated with these traits was a
result of non- additive gene action. These results for most
studied traits support the findings Ahmed et al (2017), who
reported that δ2SCA was useful in the inheritance of grain yield
plant-1 and other agronomic traits.
The magnitude of the interaction of δ2GCA x year was
higher than that of δ2SCA x year for plant height, no of kernels
row-1, 100-kerenl weight and grain yield plant-1.
Consequently, additive gene effects seemed greatly affected
by environment. Vice versa, remain traits (maturity date, ear
height and No of rows ear-1) showed δ2SCA x year (Y) was
generally higher than for δ2GCA x Y. This finding showed that
non-additive type of gene action were more changed than
additive and additive x additive types of gene action by
seasonal change. This is in harmony with the findings of
several investigators who reported that δ2SCA is more sensitive
to environmental changes than δ2GCA (El-Hosary 2020 and
Ismail et al (2020).
General combining ability effects (ĝi) calculated for
each tester and lines (combined over two years) are presented
in Table 4. High positive values would be of interest under all
traits in question except that of days to maturity where high
negative values would be useful from the breeder's point of
view. The effects of ĝi for males (testers) showed that the
inbred line M 221 behaved as a good combiner for all traits
except, plant and ear heights. Earliness and high yielding if
found in maize, would expand the opportunity for intensive
cropping. Therefore, the male parent M 221 could be an
excellent parent in breeding programs towards releasing early
and high yield potentiality of hybrid maize. On the other
hand, the parental tester Sakha pop. expressed a highly
significant negative results for days to maturity, plant and ear
heights. The male parents SC (M200xM418) had undesirable

El-Hosary, A. A. A.
850
ĝi effects for all traits. Therefore, both male parents were of
greatest interest and should be used as testers for evaluating
the new inbred lines for these traits. The parental females
(inbred lines) M. 645a (L4), M. 653 (L5), M. 658A (L8), M.
671 (L9), M. 673 (L10), M. 674 (L11) and M. 678 (L14)
showed significant negative effects for ĝi days to maturity;
M. 603c (L2), M. 673 (L10), M. 675a (L12), M. 677 (L13)
and M. 678 (L14) for plant and ear heights, M. 601 (L1), M.
645a (L4), M. 658A (L8), M. 674 (L11) for No of rows ear-1,
M. 653 (L5), M. 655b (L6), M. 657 (L7), M. 671 (L9), M. 674
(L11), M. 682r (L15) for No. of kernel row-1, M. 642 (L3), M.
653 (L5) for 100-kernel weight, M. 645a (L4), M. 653 (L5),
M. 655b (L6), M. 657 (L7), M.674 (L11) for grain yield plant-
1 had significant positive ĝi effect.
Table 4. General combining ability effects for testers and inbred lines for all studied traits in the combined analysis.
Parent
Days to maturity
(days)
plant height
(cm)
ear height
(cm)
No of
Rows ear-1
No of kernel
row-1
100-kernel
weight (g)
Grain yield
plant-1 (g)
Tester
M. 221 (T1)
-0.56**
12.10**
11.61**
0.49**
2.16**
2.21**
31.73**
M 200 x M 418 (T2)
-0.24**
1.14
0.84*
-0.02
-0.02
-0.26
-2.17**
Sakha pop. (T3)
0.80**
-13.25**
-12.45**
-0.47**
-2.14**
-1.95**
-29.56**
LSD (gi) 5%
0.16
1.18
0.7
0.05
0.16
0.36
0.74
1%
0.21
1.55
0.92
0.06
0.21
0.48
0.98
kLSD (gi-gj) 5%
0.26
1.67
1.14
0.08
0.27
0.51
1.21
1%
0.35
2.2
1.5
0.1
0.35
0.67
1.59
Line
M. 601 (L1)
3.48**
-10.82**
-0.29
0.72**
-1.64**
-2.37**
-11.91**
M. 603c (L2)
2.81**
-22.09**
-12.65**
0.00
-2.41**
-0.41
-10.84**
M. 642 (L3)
0.98**
18.54**
12.41**
-0.1
-3.05**
1.57**
-9.90**
M. 645a (L4)
-1.58**
14.68**
9.05**
0.38**
-0.37
0.65
5.74**
M. 653 (L5)
-1.47**
10.77**
7.46**
-0.27**
2.04**
2.57**
19.27**
M. 655b (L6)
1.03**
4.31**
-0.14
0.01
1.26**
1.01*
11.46**
M. 657 (L7)
-0.3
13.41**
4.31**
0.03
1.33**
-0.01
7.59**
M. 658A (L8)
-1.63**
4.22**
10.61**
0.21**
-0.52*
0.58
2.52*
M. 671 (L9)
-1.13**
15.87**
19.29**
0.07
3.72**
-1.15**
11.93**
M. 673 (L10)
-0.91**
-12.95**
-9.04**
-0.34**
-0.47*
-0.21
-9.32**
M. 674 (L11)
-0.97**
0.67
-5.49**
0.17**
2.61**
0.72
20.65**
M. 675a (L12)
-0.19
-9.09**
-14.45**
-0.28**
-2.22**
-2.44**
-26.76**
M. 677 (L13)
-0.13
-13.37**
-12.01**
-0.24**
-0.82**
-0.26
-6.78**
M. 678 (L14)
-0.58**
-13.38**
-7.07**
0.09
-0.11
-0.4
-1.16
M. 682r (L15)
0.59**
-0.78
-1.98*
-0.44**
0.65**
0.16
-2.48*
LSD (gi) 5%
0.42
2.64
1.8
0.12
0.42
0.81
1.92
LSD (gi) 1%
0.55
3.47
2.36
0.16
0.55
1.07
2.52
LSD (gi-gj) 5%
0.59
3.74
2.54
0.17
0.59
1.15
2.71
LSD (gi-gj) 1%
0.77
4.91
3.34
0.22
0.78
1.51
3.56
* and ** indicate significance at 0.05 and 0.01 levels of probability, respectively.
Specific combining ability effects (SCA) of 45 line x
tester cross are presented in Table 5. The greatest inter-and
intra-allelic interaction as deduced from SCA effects were
observed in crosses: M. 221 x M 671, M. 221 x M 674, M. 221
x M 678, M. 221 x M 682r , M SC x M603c, M SC x M653,
M SC x M657, Sakha Pop. x 642, , Sakha Pop. x 645a and ,
sakha Pop. x 658A for early maturity; M 221 With each of M
645a, M671, M 677; M SC with each of M 603c and M 657
for plant and ear heights; M 221 with each of M 601, M655b,
M 657, M 682r; Sakha Pop. with each of M 673, M 674 and
M 675a for No of rows ear-1; M 221 With each of M 642,
M653, M 673; M SC with each of M 642, Sakha po. X M
675a, M 678 and M 682r for the number of kernels row-1; M
221 with each of M 657, M677; Sc x M 678 for the 100-kernel
weight; and M 221 with each of M 601, M 655b, M657 and
M 677; SC (M 200xM418) and each of M 642, M 653, M 677,
M678, M 682r; and Sakha Pop. with each of M 603c, M 645a,
M 673, M 672a and M 678 for grain yield plant-1. These test-
crosses might be of interest in breeding programs as most of
them involved at least one good combiner for the concerned
traits. These test crosses could be of interest to obtain synthetic
varieties or produced inbred lines.
It could be concluded that testers of broad genetic base
are more efficient than those of the narrow genetic base for
evaluation of GCA inbred lines of maize. Among the material
evaluated, the line M 642a, 653, 658, 671 and M 674 gave the
highest GCA effects for early maturity with high yielding
ability, and that the top crosses M 221 x M 653, SC x M653
and Shakha with each of M645a and M 658A appeared
efficient and promising in improving early maturity and grain
yield. Also, these hybrids used in breeding program to produce
new inbred lines.
Mean performance and relative superiority% relative to
check hybrids
Table 6 showed that the mean performance of 45 test
crosses and two checks (SC 168 and TWC 368) for days to
maturity and grain yield plant-1. Also, the percent of out-
yielded of test crosses relative to mention check varieties. For
days to maturity, results showed that twelve, sixteen and
twenty six test crosses exhibited the lowest mean values for
days to maturity and the deviation between these crosses and
earlier check SC 168 were significant. However, the crosses M
221xM674, M221xM682r, MSC x M653, MSC x 657, Sakha
Pop. X M645a and Sakha Pop. X M658A were earlier than the
two check hybrids in both and across years. Early maturity
crosses in maize is convenient for escaping destructive injuries
caused by borer like Sesamia cretica, Chilo simplex and
Pyrausta nubilialis. Similar results were reported by El-
Hosary and El-Fiki (2015) and Ismail (2019 a & b).

J. of Plant Production, Mansoura Univ., Vol. 11 (9), September, 2020
851
Table 5. Specific combining ability effects for test crosses over both years for all studied traits.
test crosses
Days to maturity
(days)
plant height
(cm)
ear height
(cm)
No of
Rows ear-1
No of kernel
row-1
100-kernel
weight (g)
Grain yield
plant-1 (g)
M. 221 x M. 601
-0.11
0.85
10.41**
0.62**
0.40
0.64
8.27**
M. 221 x M. 603c
-0.61
4.00
-5.29**
-0.01
0.68
-0.80
-0.84
M. 221 x M. 642
0.56
-3.81
7.24**
-0.60**
1.23**
-0.18
-6.68**
M. 221 x M. 645a
2.11**
-6.46**
-6.27*
-0.22*
-0.28
-0.18
-7.40**
M. 221. x M. 653
0.83*
-1.17
-13.12**
0.04
0.83*
-0.62
-0.94
M. 221 x M. 655b
-0.67
2.92
1.92
0.57**
-0.38
-0.22
9.81**
M. 221 x M. 657
0.83*
1.25
1.63
0.69**
0.14
1.64*
16.22**
M. 221. x M. 658A
1.00**
-1.06
0.45
-0.05
-1.07**
-0.56
-8.88**
M. 221 x M. 671
-0.83*
-11.77**
-7.32**
-0.04
-0.38
0.41
2.88
M. 221 x M. 673
0.28
-2.77
-3.46*
-0.36**
1.62**
-0.64
3.88*
M. 221 x M. 674
-1.00**
8.30**
7.02**
-0.36**
-0.33
0.48
1.58
M. 221 x M. 675a
0.56
4.05
-2.42
-0.10
-1.08**
-0.18
-10.20**
M. 221 x M. 677
0.17
-7.43**
-15.78**
-0.15
0.10
2.39**
14.07**
M. 221 x M. 678
-1.06**
2.91
10.44**
-0.32**
-0.10
-1.33
-14.39**
M. 221 x M. 682r
-2.06**
10.19**
14.54**
0.28**
-1.40**
-0.86
-7.38**
M. S.C. x M. 601
0.08
-2.25
-22.91**
-0.53**
0.66
-0.49
-6.05**
M. S.C. x M. 603c
-0.76*
-6.67**
-7.83**
-0.01
-0.97**
0.06
-5.49**
M. S.C. x M. 642
1.24**
-2.60
0.77
0.39**
0.96**
-0.22
9.19**
M. S.C. x M. 645a
1.13**
2.00
3.26*
-0.56**
-0.11
0.31
-6.11**
M. S.C.. x M. 653
-1.98**
0.67
11.72**
0.47**
-0.47
0.21
8.84**
M. S.C. x M. 655b
0.52
5.50*
7.76**
0.08
-0.23
0.33
1.18
M. S.C. x M. 657
-2.48**
-4.48
-5.13**
-0.21*
0.33
-0.77
-2.13
M. S.C. x M. 658A
0.52
-0.29
-6.43**
-0.15
0.51
0.03
1.02
M. S.C. x M. 671
-0.14
5.88*
6.99**
-0.04
0.46
-0.54
-1.22
M. S.C. x M. 673
-0.03
-1.74
-2.34
-0.23*
-1.36**
-0.10
-11.54**
M. S.C. x M. 674
0.19
-3.71
-5.71**
-0.23*
0.53
0.20
-2.86
M. S.C. x M. 675a
-0.42
1.53
14.63**
-0.23*
0.34
-0.81
-4.69**
M. S.C. x M. 677
-0.31
2.10
2.37
0.90**
0.62
-0.67
6.94**
M. S.C. x M. 678
0.63
3.61
2.83
0.19
-0.66
1.42*
5.46**
M. S.C. x M. 682r
1.80**
0.46
0.03
0.18
-0.60
1.04
7.44**
Sakha Pop. x M. 601
0.03
1.39
12.50
-0.09
-1.06**
-0.15
-2.22
Sakha Pop. x M. 603c
1.37**
2.67
13.11
0.03
0.29
0.75
6.33**
Sakha Pop. x M. 642
-1.80**
6.42
-8.01
0.21*
-2.19**
0.40
-2.51
Sakha Pop. x M. 645a
-3.24**
4.46
3.01
0.78**
0.39
-0.14
13.51**
Sakha Pop. x M. 653
1.14**
0.50
1.40
-0.51**
-0.37
0.41
-7.89**
Sakha Pop. x M. 655b
0.14
-8.42
-9.68
-0.66**
0.60
-0.11
-11.00**
Sakha Pop. x M. 657
1.64**
3.23
3.50
-0.49**
-0.48
-0.88
-14.09**
Sakha Pop. x M. 658A
-1.52**
1.35
5.98
0.20
0.56
0.54
7.86**
Sakha Pop.x M. 671
0.98**
5.89
0.33
0.09
-0.08
0.13
-1.65
Sakha Pop. x M. 673
-0.24
4.51
5.81
0.59**
-0.26
0.74
7.66**
Sakha Pop. x M. 674
0.81*
-4.59
-1.30
0.59**
-0.20
-0.68
1.28
Sakha Pop. x M. 675a
-0.13
-5.58
-12.21
0.33**
0.74*
0.99
14.89**
Sakha Pop. x M. 677
0.14
5.33
13.41
-0.74**
-0.72
-1.72*
-21.01**
Sakha Pop. x M. 678
0.42
-6.52
-13.26
0.13
0.76*
-0.09
8.93**
Sakha Pop.x M. 682r
0.26
-10.65
-14.57
-0.47**
2.00**
-0.18
-0.06
L.S.D. (Sij) 5%
0.72
4.58
3.12
0.21
0.73
1.41
3.32
L.S.D. (Sij) 1%
0.95
6.01
4.09
0.27
0.95
1.85
4.36
L.S.D. S(ij-ki) 5%
1.02
6.47
4.41
0.29
1.03
1.99
4.70
L.S.D. S(ij-ki) 1%
1.34
8.51
5.79
0.38
1.35
2.61
6.17
* and ** indicate significance at 0.05 and 0.01 levels of probability, respectively.
Concerning grain yield plant-1 for the studied test crosses
ranged from 140.67 (Sakha Pop. x M. 677) to 278.0 (M. 221 x
M. 674) in the first year, 100.44 (Sakha Pop. x M. 601) to 214.6
(M. 221. x M. 653) in the second years and 127.52 (Sakha Pop.
x M. 677) to 240.41 (M. 221 x M. 657) in the combined analysis.
The six SC between M L 221 and each of inbred lines M. 653,
M. 655b, M. 657, M. 671, M. 674 and M. 677 showed
significantly and out yielded than check hybrid SC 168 in the
combined analysis. Also, most TW crosses out yielded or
insignificant than check hybrid Twc 368. The fluctuation of
hybrids from years to another was detected for yield plant-1.
Hence, it could be concluded that these crosses offer possibility
for improving grain yield of maize. In the same time, for grain
yield plant-1, six single crosses i.e. M.221xM.653,
M.221xM.655b, M.221xM.657, M.221xM.671, M.221xM.674
and M.221xM.677 expressed significant and positive superiority
relative to SC 168 in the combined analysis reached 9.96%,
11.35%, 12.53%, 8.32%, 11.80% and 4.80%, respectively.
However, the two three way crosses i.e. S.C. (M200xM418) x
M.653 and S.C. (M200xM418) x M.674 recorded significant
positive superiority effective to TWC 368 being 9.11% and
3.78%, respectively. Hence, it could be concluded that these
crosses offer possibility for improving grain yield in maize.
Several investigators reported high heterosis for yield of maize;
i.e. Sadek, et al. (2002), Hefny, (2010) and Abd El-Aal, (2012).
Stability analysis for the eight promising hybrids and the
four check hybrids.
Analysis of variance (ANOVA)
The regular combined analysis of variance for grain
yield plant-1 of the 12 genotypes (G) evaluated across 8

El-Hosary, A. A. A.
852
environments (E) and their (GxE) interaction is presented in
Table (7). The results indicated that the main effects of
genotypes, environments and their GxE interaction were
highly significant (P < 0.01). On the other hand, the pooled
analysis showed that 28.83 % of the total sum of squares was
attributed to environment while the genotype and GxE
interaction effects explained 63.20 % and 7.96 %,
respectively (Table 7). The large sum of squares of
environment+ GxE interaction almost duplicated 5 times the
corresponding percent of genotype term indicating that there
were substantial differences among studied environments
which advocated the adequacy of running stability analysis. It
is axiomatic to say that the yield as a final outcome was the
most responsible for the environmental variation. Also, the
ratio of the sum of squares for genotype was nearly eight
times higher than the share of interaction effect indicating
wide genetic variation among tested genotypes. The
significant interaction effect gives another justification to
discuss the genotype stability. Sowmya et al. (2018),
Arunkumar, et al. (2020) and El-Hosary (2020) found
significant GxE interaction component indicating that the
maize genotypes fluctuated in their rank performance for seed
yield across the aimed environments.
Table 6. Test crosses mean performance and studied check varieties in both and across years for days to maturity and
grain yield plant-1 and relative superiority % for grain yield in the combined analysis.
Test cross
days to maturity
(day)
grain yield plant -1
(g)
% superior
for grain yield in Comb. (g)
Frist year
2017
Second
year 2018
Combined
Frist year
2017
Second year
2018
Combined
H% Relative to
S.C.168
H% Relative
to T.w.c. 368
M. 221 x M. 601
105.67
105.00
105.33
228.26
197.67
212.96
-0.31
10.23**
M. 221 x M. 603c
106.00
102.33
104.17
225.33
184.50
204.92
-4.08**
6.06**
M. 221 x M. 642
103.67
103.33
103.50
204.70
195.33
200.02
-6.37**
3.53**
M. 221 x M. 645a
101.33
103.67
102.50
229.79
200.09
214.94
0.61
11.25**
M. 221. x M. 653
103.00
99.67
101.33
255.24
214.60
234.92
9.96**
21.60**
M. 221 x M. 655b
103.33
101.33
102.33
271.00
204.76
237.88
11.35**
23.13**
M. 221 x M. 657
102.33
102.67
102.50
275.00
205.82
240.41
12.53**
24.43**
M. 221. x M. 658A
101.33
101.33
101.33
239.13
181.36
210.25
-1.59
8.82**
M. 221 x M. 671
101.33
98.67
100.00
259.30
203.51
231.41
8.32**
19.78**
M. 221 x M. 673
101.67
101.00
101.33
230.64
191.68
211.16
-1.16
9.30**
M. 221 x M. 674
99.67
100.33
100.00
278.00
199.67
238.83
11.80**
23.62**
M. 221 x M. 675a
101.33
103.33
102.33
189.57
169.71
179.64
-15.91**
-7.02**
M. 221 x M. 677
105.33
98.67
102.00
237.33
210.44
223.89
4.80**
15.88**
M. 221 x M. 678
101.67
99.00
100.33
217.67
184.44
201.05
-5.89**
4.06**
M. 221 x M. 682r
100.00
101.00
100.50
241.26
172.23
206.74
-3.23**
7.01**
M. S.C. x M. 601
106.00
105.67
105.83
192.05
137.44
164.75
-22.88**
-14.73**
M. S.C. x M. 603c
104.00
104.67
104.33
191.10
141.66
166.38
-22.12**
-13.88**
M. S.C. x M. 642
103.67
105.33
104.50
206.10
157.89
182.00
-14.81**
-5.80**
M. S.C. x M. 645a
103.33
100.33
101.83
223.31
141.37
182.34
-14.65**
-5.62**
M. S.C.. x M. 653
98.67
99.00
98.83
248.67
172.95
210.81
-1.32
9.11**
M. S.C. x M. 655b
104.00
103.67
103.83
228.24
162.46
195.35
-8.56**
1.11
M. S.C. x M. 657
100.00
99.00
99.50
242.67
133.67
188.17
-11.92**
-2.61*
M. S.C. x M. 658A
101.67
100.67
101.17
211.66
160.82
186.24
-12.82**
-3.60**
M. S.C. x M. 671
101.33
100.67
101.00
222.17
164.67
193.42
-9.46**
0.11
M. S.C. x M. 673
101.00
101.67
101.33
180.38
143.32
161.85
-24.24**
-16.23**
M. S.C. x M. 674
101.67
101.33
101.50
243.33
157.67
200.50
-6.15**
3.78**
M. S.C. x M. 675a
104.00
99.33
101.67
183.45
119.06
151.25
-29.20**
-21.71**
M. S.C. x M. 677
103.33
100.33
101.83
217.66
148.08
182.87
-14.40**
-5.35**
M. S.C. x M. 678
103.33
101.33
102.33
209.38
164.64
187.01
-12.46**
-3.20**
M. S.C. x M. 682r
106.00
103.33
104.67
215.67
159.67
187.67
-12.16**
-2.86*
Sakha Pop. x M. 601
106.67
107.00
106.83
181.93
100.44
141.18
-33.91**
-26.92**
Sakha Pop. x M. 603c
107.33
107.67
107.50
172.20
129.40
150.80
-29.41**
-21.95**
Sakha Pop. x M. 642
102.00
103.00
102.50
181.33
104.47
142.90
-33.11**
-26.04**
Sakha Pop. x M. 645a
98.67
98.33
98.50
215.29
133.84
174.56
-18.29**
-9.65**
Sakha Pop. x M. 653
103.67
102.33
103.00
178.67
154.70
166.68
-21.98**
-13.73**
Sakha Pop. x M. 655b
105.00
104.00
104.50
176.67
134.90
155.78
-27.08**
-19.37**
Sakha Pop. x M. 657
106.00
103.33
104.67
185.99
111.62
148.80
-30.35**
-22.98**
Sakha Pop. x M. 658A
100.67
99.67
100.17
176.95
154.43
165.69
-22.44**
-14.24**
Sakha Pop.x M. 671
105.00
101.33
103.17
190.35
140.83
165.59
-22.49**
-14.29**
Sakha Pop. x M. 673
102.33
102.00
102.17
169.13
138.18
153.65
-28.08**
-20.47**
Sakha Pop. x M. 674
104.00
102.33
103.17
229.15
125.33
177.24
-17.04**
-8.26**
Sakha Pop. x M. 675a
103.33
102.67
103.00
166.40
120.47
143.43
-32.86**
-25.76**
Sakha Pop. x M. 677
103.33
103.33
103.33
140.67
114.38
127.52
-40.31**
-33.99**
Sakha Pop. x M. 678
104.67
101.67
103.17
173.33
152.83
163.08
-23.66**
-15.59**
Sakha Pop.x M. 682r
104.33
104.00
104.17
155.91
149.63
152.77
-28.49**
-20.93**
SC 168
103.33
105.30
104.32
218.80
208.47
213.64
TWC 368
105.67
106.90
106.29
195.48
190.92
193.20
L. S. D 5%
1.27
1.59
1.01
7.42
6.37
4.86
L. S. D 1%
1.69
2.10
1.34
9.83
8.44
6.41
* and ** indicate significance at 0.05 and 0.01 levels of probability, respectively.

J. of Plant Production, Mansoura Univ., Vol. 11 (9), September, 2020
853
Results of joint regression analysis of variance as
suggested by Eberhart and Russell (1966) are also shown in
Table (7). The model partitioned the environment + (genotype x
environment) term into three parts; including environment
(linear), genotype x environment (GxE linear) and the part of
pooled deviation which expressed the unexplained deviation
from linear regression. The mean squares of GxE (linear)
component was highly significant indicating that at least one
regression coefficient (b values) significantly differed from unity
which meaning that some tested genotypes are linearly affected
by the aimed environments. Also, the highly significant effect of
pooled deviation component indicated that the tested genotypes
differed regarding their deviations from their respective average
linear response.
Table 7. Regular combined analysis of variance and
partitioning the proper source of variation for
grain yield plant-1 according to each of Eberhart
and Russell model.
Source of variation
df
Grain yield
plant-1 SS
Grain yield
plant-1 MS
Genotype
11
15456.94 (63.20%)
1405.18**
Environment+ G*E
84
8998.603 (36.79%)
107.13**
Environment
7
7050.977 (28.83%)
1007.28**
Genotype x Env.
77
1947.626 (7.96%)
25.29**
a) Env . (linear)
1
7050.977
7050.98**
b) V x Env. (linear)
11
189.2443
17.20**
c) pooled deviations
72
1758.382
24.42**
Genotypes
M. 221 x M. 657 (1)
6
209.1003
34.85**
M. 221 x M. 674 (2)
6
175.7746
29.30**
M. 221 x M. 655b (3)
6
164.0391
27.34**
M. 221. x M. 653 (4)
6
151.3271
25.22**
M. 221 x M. 671 (5)
6
146.3716
24.40**
M. 221 x M. 677 (6)
6
282.7828
47.13**
M. S.C.. x M. 653 (7)
6
153.2355
25.54**
M. S.C. x M. 674 (8)
6
89.0453
14.84**
SC hytech 2066 (9)
6
81.44573
13.57**
SC 168 (10)
6
39.52813
6.59**
TWC 368 (11)
6
12.8728
17.15**
TWC 352 (12
6
162.8587
27.14**
poled error
176
10.6113
0.06
* and ** indicate significant at 0.05 and 0.01 levels of probability, respectively.
The previous results appeared the magnitude of both
predictable (linear) and unpredictable (non-linear) interaction
components in explaining the stable breeding materials. The
obtained results are in agreement with those reported by Sowmya
et al. (2018), Arunkumar, et al. (2020) and El-Hosary (2020).
According to Eberhart and Russell model, regression
coefficients ranged from 0.67 to 1.24 indicating that genotypes
already had different responses to environmental changes. The
values of regression coefficient (b) did not significantly differ
from unity for all tested genotypes except for TWC 368 (11).
The values of deviation from regression (S2d) were
insignificantly different from zero for all genotypes except for
M. 221 x M. 657 (1), M. 221 x M. 674 (2), M. 221 x M. 655b
(3), M. 221 x M. 677 (6), SC hytech 2066 (9) and SC 168 (10).
It is evident that the values of b and S2d for the
aforementioned genotypes were not significantly different from
unity and zero, respectively. Moreover, their mean performances
exceeded or insignificant decrease the mean of all genotypes.
Therefore, these genotypes were considered phenotypically
stable according to Eberhart and Russell (1966) model. These
results are in accordance with those obtained by Sowmya et al.
(2018), Arunkumar, et al. (2020) and El-Hosary (2020).
With regard to genotypic stability as outlined by Tai
(1971), the estimates of α and λ are displayed in Table (8) and
graphically shown in Fig. (1). It is important to report that, the
most stable genotypes resulted using Tai model exactly
coincided with those obtained by Eberhart and Russell model.
The stability parameters according to Tai were not significantly
differed from zero for all genotypes at all the probability levels
except numbers 6 and 1. The λ statistics were significantly
differed from λ = 1 for all genotypes except genotypes 6 and 1.
These results indicate that maize genotypes 12, 7 and 5 showed
average degree of stability, while, genotype 3, 4, 9 and 10
showed below average degree of stability at 0.90 probability
levels for the grain yield plant-1. On the contrary, genotype 2, 11
and 8 showed above average degree of stability at 0.90
probability levels for the mention trait.
Table 8. Estimation of stability parameters of grain yield
plant-1.
Genotype
Grain yield plant-1
Mean (g)
bi
S2di
α
λ
M. 221 x M. 657 (1)
220.17
0.85
3.790
-0.15
2.59
M. 221 x M. 674 (2)
214.57
0.80
2.235
-0.21
2.18
M. 221 x M. 655b (3)
205.35
1.08
2.280
0.08
2.04
M. 221. x M. 653 (4)
198.7
1.11
5.161*
0.11
1.88
M. 221 x M. 671 (5)
202.69
1.04
4.335*
0.04
1.82
M. 221 x M. 677 (6)
208.43
1.24
3.070
0.24
3.50
M. S.C.. x M. 653 (7)
191.59
1.03
5.479*
0.03
1.90
M. S.C. x M. 674 (8)
174.8
0.85
4.781*
-0.15
1.10
SC hytech 2066 (9)
195.04
1.14
3.514
0.14
1.01
SC 168 (10)
202.27
1.17
2.528
0.18
0.49
TWC 368 (11)
191.08
0.67
7.085**
-0.33
1.27
TWC 352 (12)
181.79
1.02
2.083**
0.02
2.02
Average
198.87
LSD 5%
3.72
LSD 5%
4.94
Where, bi and S2d refer to regression coefficient and deviation from
regression, respectively; α and λ measure linear response to environmental
effects and deviation from linear response in terms of the magnitude of
error variance, respectively.
Fig. 1. Distribution of Tai’s stability statistics for grain
yield plant-1 of twelve genotypes across eight
environments
Notes: 1- M. 221 x M. 657, 2- M. 221 x M. 674, 3- M. 221 x M. 655b, 4- M.
221. x M. 653, 5- M. 221 x M. 671, 6- M. 221 x M. 677, 7- M. S.C.. x M. 653,
8- M. S.C. x M. 674, 9- SC hytech 2066, 10- SC 168, 11- TWC 368 and 12-
TWC 352.
It can be concluded that the hybrids M. 221 x M. 674
(2), M. 221 x M. 655b (3), SC hytech 2066 (9) and SC 168
1
2
3
4
5
6
7
8
9
10
11
12
0.95
0.90
0.80
0.95
0.90
0.80
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
-1 0 1 2 3 4
α
λ

El-Hosary, A. A. A.
854
(10) were the most crosses stable phenotypically and
genetically in this study.
REFERENCES
Abd El-Aal, A.M.M. (2012) Utilization of Line x tester model
for evaluating the performance of some new yellow
maize inbred line. Bull. Fac. Agric. Cairo Univ.
63:29-36.
Ahmed, S.; S. Begum; A. Islam; M. Ratna and R.
Karim (2017) Combining ability estimates in maize
(Zea Mays L.) through line x tester analysis. Bangladesh
J. of Agric. Res., 42(3): 425–436.
Amer, E.A. and A.A. El-Shenawy (2007) Combining ability
for new twenty yellow maize inbred lines. J. Agric.
Sci. 32(9):7053-7062.
Arunkumar, B.; E. Gangapp; S. Ramesh; L. D. Savithramma;
N. Nagaraju and R. Lokesha (2020) Stability analysis
of maize (Zea mays L.) hybrids for grain yield and its
attributing traits using Eberhart and Russel
model. Current J. of App. Sci. and Tech., 39(1): 52-63.
Bartelett, M. S. (1937) Some examples of statistical methods
of research in agricultural and applied biology. J. Roy.
Stat. Soc. Suppl., 4: 137-183.
Bayoumi, R. A.; S.M. Shoker; G.Y. Hamam; A.A.A. El-Hosary
(2018) Determination of combining ability for some new
yellow maize inbred lines using line x tester model.
Annals of Agric. Sci., Moshtohor. 56(2): 305-316.
Eberhart, S.A. and W.A. Russell (1966) Stability parameters
for comparing varieties. Crop Sci., 6: 36-40.
El-Hosary, A.A.A. (2020) Diallel analysis of some
quantitative traits in eight inbred lines of maize and
GGE biplot analysis for elite hybrids. J of Plant
Production, Mansoura Univ., Vol. 11 (3):275 - 283
El-Hosary, A.A.A. (2014) Relative values of three different
testers in evaluating combining ability of new maize
inbred lines. Intern. J. of Plant Breed. and Genetics.
5(2): 57-65.
EL-Hosary A.A.A. and A. A. El-Gammaal (2013). Utilization
of line x tester model for evaluating the combining
ability of some new white maize inbred lines. Egypt. J.
Plant Breed. 17(1):79-72.
El-Hosary, A.A.A. and I.A.I. El-Fiki (2015) Diallel cross
analysis for earliness, yield, its components and
resistance to late wilt in maize. Intern. J. of Agric. Sci.
and Res. (IJASR), 5(6): 199-210.
El-Morshidy, M.A.; E.A. Hassaballa; Sh.F. Abou-Elsaad and
M.A. Abd El-Moula (2003) Combining ability and
type of gene action in maize under favorable and water
stress environments. Proc. Plant Breed. Conf Giza
Egypt, 26: 55-57.
Gomez, K.N. and A.A. Gomez (1984) Statistical Procedures
for Agricultural Research. John.Wiley and Sons. Inc.,
New York, 2nd ed.
Grogan, C.O. and M.S. Zuber (1957) A comparative study of
top cross testers parents of maize. Agron. J. 49:68-72.
Hefny, M. (2010). Genetic control of flowering traits, yield
and its components in maize (Zea mays L.) at different
sowing dates. Asian J. Crop Sci., 2(4): 236-249.
Ismail, M.R.; A.A. El-Hosary; M.E.M. El-Badawy (2020)
Comparison among three different testers for the
evaluation of new maize inbred lines (Zea mays L.).
Maydica, 65(1):1-6.
Ismail, M.R.; A.A. El-Hosary; M.E.M. El-Badawy; T.A.E.
Abdallah (2019 a) Diallel analysis for yield and
component traits in maize (Zea mays) under infestation
and non-infestation with pink stem borer (Sesamia
cretica). Indian J. of Agric. Sci., 89 (11): 1953–1958.
Ismail, M.R.; A.A. El-Hosary; M.E.M. El-Badawy; T.A.E.
Abdallah (2019 b) Combining ability studies on
resistance to pink stem borer (Sesamia cretica) in new
yellow maize (Zea mays) hybrids. Electronic Journal
of Plant Breeding, 10 (4): 1376-1382.
Kempthorne O. (1957) An introduction to genetic statistics.
John-Wiley and Sons Inc. Landon, UK.
Matzinger, D.F. (1953). Comparison of three types of testers
for the evaluation of inbred lines of corn. Agron. J.
45:493-495.
Sadek, S.E.; M.S.M. Soliman; A.A.Barakat and K.I. Khalifa
(2002) Top-crosses analysis for selecting maize lines
in the early self generations. Minufiya J. Agric. Res.
27(2): 197-213.
Sowmya, H.H.; M.Y. Kamatar; G. Shanthakumar; S.M.
Brunda; T.V. Shadakshari; B.M.; S. Babu; R.S. Singh
(2018) Stability analysis of maize hybrids using
Eberhart and Russel Model. Intern. J. of Current Micr.
and App. Sci.,7 (2):3336-3343.
Sprague, G.F. (1939) An estimation of the number of top
crossed plants required for adequate representation of
corn variety. J. Am. Soc. Agron. 38:11-16.
Tai, G.C. (1971). Genotype stability analysis and its application
to potato regional trails. Crop Sci., 11: 184-190.
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x

M. 645a (L4)

M. 653 (L5)

M. 674 (L11)

M.221xM.653

M.221xM.655b

M.221xM.657

M.221xM.671

M.221xM.674

M.221xM.677


(SC M 200xM418)xM.653

(SCM200xM418)xM.674
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