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DIALLEL CROSS ANALYSIS FOR EARLINESS, YIELD, ITS COMPONENTS AND RESISTANCE TO LATE WILT IN MAIZE

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A half diallel set of crosses involved eight yellow maize inbred lines were evaluated in normal and artificial infection by late wilt environments at the Agricultural Research and Experiment Center, Faculty of Agriculture, Benha University, Egypt. To estimate combining ability, improve productivity of maize and resistant to late wilt in Egypt. Mean squares of environments, genotypes and its fractions as well as general and specific combining abilities (GCA and SCA) reached the significance level of probability for all traits. High GCA/SCA ratios exceeded than unity were obtained for days to 50% silking and resistance to late wilt% in artificial infection environment and across environments. For remain cases, non-additive type of gene action seemed to be more prevalent. Ten crosses in both and across experiments, gave significant superiority over SC 168. The useful superiority over SC 168 ranged from 10.02 to 33.59 %.Two crosses P 1 xP 2 and P 2 xP 3 in both and across experiments had significant superiority over the best check hybrid Hytech 2055 by 14.68 and 15.49% in the combined analysis. The parental inbred line P 2 exhibited the most accurate general combiner for earliness and grain yield plant-1. The cross P 2 xP 3 was contain most desirable inter and intra-allelic interactions for most traits.
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International Journal of Agricultural
Science and Research (IJASR)
ISSN(P): 2250-0057; ISSN(E): 2321-0087
Vol. 5, Issue 6, Dec 2015, 199-210
© TJPRC Pvt. Ltd.
DIALLEL CROSS ANALYSIS FOR EARLINESS, YIELD, ITS COMPONENTS AND
RESISTANCE TO LATE WILT IN MAIZE
EL-HOSARY A. A. A1 & I. A. I. EL-FIKI2
1Department of Agronomy, Faculty of Agriculture, Benha University, Egypt
2Department of Plant Pathology, Faculty of Agriculture, Benha University, Egypt
ABSTRACT
A half diallel set of crosses involved eight yellow maize inbred lines were evaluated in normal and artificial
infection by late wilt environments at the Agricultural Research and Experiment Center, Faculty of Agriculture, Benha
University, Egypt. To estimate combining ability, improve productivity of maize and resistant to late wilt in Egypt. Mean
squares of environments, genotypes and its fractions as well as general and specific combining abilities (GCA and SCA)
reached the significance level of probability for all traits. High GCA/SCA ratios exceeded than unity were obtained for
days to 50% silking and resistance to late wilt% in artificial infection environment and across environments. For remain
cases, non-additive type of gene action seemed to be more prevalent. Ten crosses in both and across experiments, gave
significant superiority over SC 168. The useful superiority over SC 168 ranged from 10.02 to 33.59 %.Two crosses P1xP2
and P2xP3 in both and across experiments had significant superiority over the best check hybrid Hytech 2055 by 14.68
and 15.49% in the combined analysis. The parental inbred line P2 exhibited the most accurate general combiner for
earliness and grain yield plant-1. The cross P2xP3 was contain most desirable inter and intra-allelic interactions for most
traits.
KEYWORDS: Combining Ability, Diallel Analysis, Yellow Maize, Resistant to Late Wilt
Received: Nov 05, 2015; Accepted: Nov 14, 2015; Published: Nov 19, 2015; Paper Id.: IJASRDEC201527
INTRODUCTION
Great efforts are devoted to increase maize productivity with a high resistance to disease and pests.
Several diseases attack maize fields. One of the most destructive diseases in maize growing areas in lower and
Upper Egypt is late wilt. It is caused by fungi called Cephalosporium maydis. The degree of lose may be up to
80% in fields. Late wilt disease is wide spread and serious. Therefore, breeding new resistance hybrids is practical,
inexpensive and effective for controlling this disease.
Several methods are available to study the inheritance yield productivity and disease resistance. One of
the common use in this respect is the diallel cross methodology for its power and versatility. Different approaches
to the diallel analysis for estimating certain genetic parameters in terms of gene models have been developed.
Total genetic variation is portioned into the effects of general (GCA) and specific (SCA) combining ability. In this
context, GCA is the average performance of an inbred line in hybrid combinations and as such it is primarily
recognized as a measure of additive gene action. SCA indicates non-additive gene action and it desirable those
instances in which certain hybrid combinations perform relatively desirable than would be expected on the mean
performance of inbred lines involved (Sprague and Tatum 1942).
The objective of the present investigation is to evaluate eight maize inbred lines and their F1 hybrid
Original Article
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200 El Hosary A. A. A & I. A. I. El-Fiki
according to general and specific combining ability for earliness, grain yield, its components and resistance to late wilt
disease.
MATERIALS AND METHODS
Eight yellow maize inbred lines i.e. M-201(P1), M-202(P2), M-203(P3), M-204 (P4), M-241(P5), M-224(P6), M-
228(P7) and M-524(P8) were sown in two different sowing dates (2nd and 12th May 2013) in order to make half diallel
crosses by hand pollination giving a total of 28 hybrids.
In the 2013 season, two experiments were carried out. The first was a normal trial and the second involved
artificial infection with late wilt disease. The inculum was prepared by growing the fungus (Cephalosporium maydis)
isolates in sterilized milk bottles containing wet cracked grain sorghum kept at room temperature for 45 days. The
infection in the field was made according to Shafshak et al. (1986). Each experiment contained 28 crosses and their
parents along with single crosses SC 168 and Hytech 2055 (check hybrids) were grown in a randomized complete block
design with three replications at the Agricultural Research and Experiment Center, Faculty of Agriculture, Benha
University, Egypt. The sowing of the two experiments was on 6th June 2014. Each plot consisted of two ridges, 70-cm
between ridges. The long of ridge was 6-m. Three kernels per hill were sown in one side of the ridge with 25-cm spacing
between hills. Normal cultural practices were followed for maize growing in the area.
The traits studied were: days to 50% silking, plant height, resistance to late wilt disease% (percent of resistant
plants in each plot following 105 days from sowing) according to Sabet et al. (1961), number of kernels row-1, number of
rows ear-1, 100-kernel weight and grain yield plant-1 adjusted to 15.5% grain moisture. Fifteen guarded plants from each
plot were randomly taken as samples tested for the previous traits except days to 50% silking where; the mean basis of plot
was used.
Statistical analysis was done according to Steel and Torri (1980). Relative superiority of grain yield was
estimated for each cross as the percentage deviation of F1 mean performance from check variety SC Hytech 2055 average
value. Genetic analysis was done as described by Griffing (1956) for method 2 model 1. The combined analysis across the
two experiments was carried out according to (Gomez and Gomez, 1984) whenever, homogeneity of error variance was
found.
RESULTS AND DISCUSSIONS
The results obtained from parental inbred lines and their F1's for all traits studied in each and across, the two
experiments were first subjected to an ordinary analysis of variance as presented in Table 1. The mean squares due to
environments were significant for all studied traits except for days to 50% silking and No. of rows ear-1. These results are
indicated that the plants generally remained symptomless until flowering stage. Also, the number of rows ear-1 was formed
in the ear before the flowering agrees with the findings of Mostafa et al. (1996), Vivek et al. (2010) and El-Gonemy
(2015). Genotype mean squares were highly significant for all traits studied. Its fractions i.e. parents, crosses and parent vs
crosses reached significant levels in most cases.
Appreciable genotypes by environment interaction were detected for all traits except for No. of rows ear-1 and
100-kernel weight indicating that the genotypes behaved rather differently from normal environment to late wilt infection
environment. For the exceptional traits, insignificant genotype by environment was detected revealing that the genotypes
were suspected to environmental changes by nearly similar magnitudes. Insignificant interactions between parental inbred
Impact Factor (JCC): 4.7987 NAAS Rating: 3.53
Diallel Cross Analysis for Earliness, Yield, Its Components and Resistance to Late Wilt in Maize
201
lines and environments were detected in all traits except plant height. This may reveal the high repeatability of the parental
inbred lines under different environments. Significant interaction between F1 hybrids and environment were detected for
days to 50% silking, No of kernels row-1, late wilt resistance% and grain yield plant-1, indicating that these crosses behave
differently from environment to another. Insignificant interactions occurred between parent vs hybrids and environment for
all studied traits except for grain yield plant-1 revealing that average of heterosis over all crosses was influence by
environmental changes.
Mean Performance and Superiority
The mean performances of tested the eight inbred lines and the 28 hybrids across environments for all traits as
well as grain yield plant-1 and resistance to late wilt % in normal and infection environment and across them and
superiority over both checks (SC 168 and Hytech 2055) are presented in Tables (2 a and b). For days to 50% silking date,
the inbred line No. 2 gave the earliest parents. However, inbred line P7 gave the lateness one. Days to 50% silking for
crosses, ranged from 57.42 for cross P4xP8 to 63.92 for cross P3xP6 while all crosses were earliest than both check hybrids.
For plant height (cm), means ranged from 248.75 for cross P4xP6 to 290.54 for cross P3xP5. The results indicate that most
crosses were shorter than the two check hybrids, for No of rows ear-1, means ranged from 8.9 for P2 to 14.55 for P6, while,
ranged from 11.93 for cross P5xP6 to 15.47 for cross P 1xP6. Most crosses gave higher No. of rows ear-1 compared with the
two check hybrids. The parental inbred lines P7 gave the lowest number of kernels row-1. However, the parent inbred line
P1 gave the highest one for this trait. The two crosses P1xP2 and P1xP3 gave the highest number of kernels row-1 and
significant differences from two check hybrids. However cross P4xP5 gave the lowest ones, but without significant
difference from check hybrids. The inbred lines P1 and P5 recorded heavier 100-kernel weight. On the other hand, the
parental inbred line P7 gave the lowest one for this trait. For the 100-kerenel weight (g) means of crosses ranged from 31.0
for P1xP6 to 45.67 for cross P2xP3. For resistance to late wilt disease, means ranged from 76.67 for cross P6xP8 to 100.00
for P1, P5, P2xP4, P2xP6, P3xP8, P5xP6, P5xP7 and P5xP8 at normal condition, Means ranged from 58.33 for P3 to 100% for
P1, P5, P1xP5, P2xP4, P2xP6, P5xP7 at infection trial. However, means ranged from 68.33 for P 3 to 100% for P1, P5, P1xP5,
P2xP4, P2xP6 and P5xP7 in the combined analysis.
For grain yield plant-1, the two crosses P1xP2 and P2xP3 in both experiments as well as the combined analysis had
significant superiority over the best check hybrid Hytech 2055 by 14.68 and 15.49% in the combined analysis.
The ten crosses of P1xP2, P1xP3, P1xP5, P2xP3, P2xP5, P3xP8, P4xP6, P4xP7, P4xP8 and P5xP7, in both and across
experiments and the combined analysis, gave significant superiority over SC 168 by 33.59, 23.63, 17.62, 34.54, 14.25,
16.23, 11.66, 16.32 and 10.02%, respectively. In addition, the crosses P1xP5 and P5xP7 gave the highest grain yield with
resistance to late wilt. Hence, it could be concluded that these crosses offer possibility for improving grain yield in maize .
These crosses may be released as commercial hybrids after further testing and evaluation. The previous crosses exhibited
significant increase of two or more of traits contributing to grain yield plant-1. The fluctuation of hybrids from normal and
infection environments was detected for most traits.
The mean squares associated with general and specific combining abilities were highly significant in all studied
traits (Table 1). To get an idea about the produced performance of single-cross progeny in each case, the relative size of
general to specific combining ability mean squares may be helpful. High ratios which largely exceeded the unity were
obtained for days to 50% silking in both and across environments and resistance to late wilt% in artificial infection
environment as well as the combined analysis. This indicates that the largest part of the total genetic variability was
www.tjprc.org editor@tjprc.org
202 El Hosary A. A. A & I. A. I. El-Fiki
associated with those traits giving additive and additive by additive gene action. For remain cases, non-additive type of
gene action seemed to be more prevalent. The genetic variance reported by El-Rouby et al. (1973), El-Hosry, (1989) and
El-Hosary et al. (2006) to be mostly due to additive type of gene action for earliness. The non-additive genetic variance
was reported by Singh and Roy (2007), Osman et al. (2012), Zare et al.( 2011), Gouda et al. (2013), Abdel-Moneam et
al.( 2014), El-Ghonemy (2015) and Kamara (2015) to be most prevalent for grain yield and most of its components.
However other researcher Derera et al. (2008), Vivek et al. (2010), Sibiya et al. (2011), Ibrahim (2012) , El-Hosary and
Elgammaal (2013) and El-Hosary (2014) found that the additive play the major role in inheritance of grain yield. Akbar
et al. (2008) and Hefny (2010) reported that both additive and non-additive effects were equal in expression of genetic
variability for the yield and its components traits in maize.
Significant GCA and SCA by environments mean squares were obtained for all studied traits except No. of rows
ear-1 and100-kernel weight, indicating that the magnitude of GCA and SCA varied from one environment to another. These
findings agree to a large extent with those obtained from the ordinary analysis of variance.
Tables (3a and 3b) illustrate the estimates of
i
g
ˆ
effects for individual parental inbred lines at the combined across
environment. High positive values would be of interest under all studied traits except days to 50% silking and plant height
where negative one would be useful from the breeder point of view for earliness and lodging resistance. General
combining ability effects computed herein were significantly different from zero in all traits. Significant negative
i
g
ˆ
effects were detected by parental inbred lines P1, P4 and P8 for days to 50 % silking and P1, P4, P7 and P8 for plant height.
Meanwhile, the significant positive
i
g
ˆ
effects were detected by parental inbred lines P1, P3, P6 and P8 for No of rows ear-1;
P1, P2 and P6 for No of kernel row-1; P2, P3, P5 and P8 for 100- kernel weight; P1 and P5 for resistant to late wilt and P1, P2,
P3 and P6 for grain yield plant-1.
The aforementioned inbred line which had high
i
g
ˆ
effects for grain yield plant-1, also, possessed one or more of
the traits contributing to grain yield. It is of interest for plant breeders to ask whether the GCA for parental inbred lines
agrees with its own performance or where some parents are more potent when crossed than would be expected from their
own performance. The results show positive correlation coefficient between the parental performance and the
corresponding
i
g
ˆ
effects obtained for all studied traits. Therefore, it could be concluded that the high performing hybrids
could be reached except that crossing is carried out between parental inbred lines characterized by high mean
performances. For grain yield plant-1, plant height and 100-kernel weight the insignificant correlation coefficients between
i
g
ˆ
effects and mean performance was detected. This disagreement suggests that hybrids characterized by these traits
could be expected by crossing between inbred lines with a low performance for these characters. Also, it could be
concluded that the GCA variance had been with dominance with effects to a certain degree (Jinks 1955). The parental
inbred line P2 exhibited the most accurate general combiner for earliness and grain yield plant-1.
The parental inbred lines combinations specific combining ability
ij
S
^
effects for all studied traits across
environments are presented in Tables (4 a-b). twenty two, zero, twenty, twenty, fifteen, nine and twenty two crosses give
desirable
ij
S
^
effects for days to 50% silking, plant height, no of rows ear-1, No of kernels row, 100- kernel weight, resistant
to late wilt% and grain yield plant-1, respectively. The most desirable inter and intra-allelic interactions were represented;
Impact Factor (JCC): 4.7987 NAAS Rating: 3.53
Diallel Cross Analysis for Earliness, Yield, Its Components and Resistance to Late Wilt in Maize
203
by P4xP7, P4xP8, P5xP6, P5xP8, P6xP7 and P7xP8 for days to 50% silking, P3xP8 and P5xP7 for No of rows ear-1, P1xP3 for
No of kernels row-1, P2xP3 for 100-kerenl weight, P2xP3, P2xP4, P2xP6 and P3xP6 for resistant to late wilt% and P1xP2 and
P2xP3 for grain yield plant-1. Such combinations may be of interest in breeding programs aimed at excellent hybrids since
they surpassed the best performing for these traits or produce new inbred lines as most combinations involved at least one
good combiner parent or produced synthetic varieties.
CONCLUSIONS
The previous results could be showed that the parental inbred line P1was the good general combiner for earliness,
resistant to late wilt and grain yield plant-1. The crosses P1xP2 and P2xP3 had high productivity and these crosses were
superior over the check hybrids. However, the cross P2xP3 was contain most desirable inter and intra-allelic interactions
for most traits.
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Impact Factor (JCC): 4.7987 NAAS Rating: 3.53
Diallel Cross Analysis for Earliness, Yield, Its Components and Resistance to Late Wilt in Maize
205
APPENDICES
Table 1: Mean of squares from ordinary analysis for studied traits in normal environment, artificial infection by
late wilt disease and across the previous environments.
SOV
Mean squares
Days to
50%
silking
Plant
height
No of
Rows ear-1
No of
kernels row-1
100-kernel
kernel weight
Resistant
to late wilt%
Grain
yield plant-1
Normal environment
Replication
4.97*
150.42*
0.79
0.56
1.00
25.93
38.03**
Genotype (G)
56.17**
4772.73**
9.33**
110.09**
54.42**
157.06**
7718.44
Parent (P)
43.41**
3757.87**
9.41**
108.43**
13.69**
178.57**
3798.95**
Crosses (F1)
10.80**
505.19**
2.88**
31.93**
28.82**
157.18**
2636.92**
P vs. F1
1370.48**
127100.42**
183.06**
2231.86**
1030.92**
3.24
172355.99**
Error
1.13
46.81
0.47
2.65
3.87
33.54
79.08
GCA
19.47**
215.26**
1.68**
21.73**
9.57**
41.09**
650.93**
SCA
18.54**
1934.82**
3.47**
40.44**
20.28**
55.17**
3053.28**
Error
0.38
15.60
0.16
0.88
1.29
11.18
26.36
GCA/SCA
1.05
0.11
0.48
0.54
0.47
0.74
0.21
Artificial infection environment by late wilt disease
Replication
5.58**
94.02
1.74*
3.56
17.07*
31.84
82.12
Genotype (G)
55.16**
5469.70**
10.43**
97.43**
58.75**
344.29**
8779.67**
Parent (P)
28.06**
955.85**
11.13**
78.14**
23.23**
536.36**
2833.69**
Crosses (F1)
18.71**
446.66**
2.59**
31.64**
30.34**
304.35**
2564.60**
P vs. F1
1229.13**
172688.63**
217.00**
2008.83**
1074.47**
78.26
218208.26**
Error
0.72
94.49
0.38
1.55
3.53
31.27
75.67
GCA
21.39**
325.84**
1.89**
16.45**
10.09**
191.59**
425.35**
SCA
17.64**
2197.58**
3.87**
36.48**
21.96**
95.56**
3551.86**
Error
0.24
31.50
0.13
0.52
1.18
10.42
25.22
GCA/SCA
1.21
0.15
0.49
0.45
0.46
2.00
0.12
Combined across environment
Environment (E)
0.49
11022.45**
0.07
10.67**
13.73**
2660.02**
289.14**
Rep/E
5.28**
122.22
1.27*
2.06
9.04*
28.88
60.08
Genotype (G)
108.92**
9991.20**
19.53**
199.86**
110.95**
435.71**
16330.73**
Parent (P)
69.79**
3861.48**
20.44**
184.13**
33.57**
656.27**
6574.85**
Crosses (F1)
26.89**
911.69**
5.23**
54.38**
57.15**
392.57**
5049.55**
P vs. F1
2597.69**
298045.79**
399.33**
4237.75**
2105.17**
56.68
389213.82**
G x E
2.42**
251.23**
0.23
7.66**
2.23
65.64**
167.37**
P x E
1.68
852.24**
0.10
2.44
3.35
58.65
57.78
F1 x E
2.63**
40.15**
0.24
9.19**
2.02
68.96**
151.97**
P vs. F1 x E
1.92
1743.26**
0.72
2.93
0.23
24.83
1350.43**
Error
0.93
70.65
0.43
2.10
3.70
32.41
77.38
GCA
39.42**
450.75**
3.52**
35.81**
19.06**
197.48**
1036.69**
SCA
35.53**
4050.31**
7.26**
74.32**
41.46**
132.18**
6545.30**
GCA x E
1.43**
90.35**
0.05
2.37**
0.60
35.20**
39.59
SCA x E
0.65**
82.09**
0.08
2.60**
0.78
18.55*
59.84**
Error
0.31
23.55
0.14
0.70
1.23
10.80
25.79
GCA/SCA
1.11
0.11
0.48
0.48
0.46
1.49
0.16
* and ** indicate p< 0.05 and p< 0.01, respectively.
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206 El Hosary A. A. A & I. A. I. El-Fiki
Table 2a: Mean performance of all genotypes for earliness, plant height, no of rows ear-1, no of kernels row-1 and
100-kernel weight at the combined analysis across the studied environments and resistance of genotypes to
late wilt in both and across environments
Genotype
Days to
50%
Silking
Plant
Height
No of
Rows
No of
Kernels
Row
-1
100-
Kernel
Weight
Resistance to Late Wilt %
N.
Inf.
Comb.
Ear-1
P
1
72.00
156.25
11.45
35.85
34.50
100.00
100.00
100.00
P
2
63.71
210.33
8.90
27.13
30.17
93.33
88.33
90.83
P
3
65.83
203.17
9.48
18.63
30.50
78.33
58.33
68.33
P
4
66.58
207.21
11.03
30.28
29.83
96.67
90.00
93.33
P
5
72.42
144.33
10.37
26.05
34.33
100.00
100.00
100.00
P
6
70.83
186.46
14.55
35.00
29.83
96.67
91.67
94.17
P
7
72.63
165.63
11.53
25.28
28.33
96.67
91.67
94.17
P
8
68.38
165.04
9.00
28.13
28.67
85.00
80.67
82.83
P
1
xP
2
59.50
278.46
15.00
46.77
39.00
80.00
75.00
77.50
P
1
xP
3
62.08
265.21
14.42
47.04
39.00
93.33
91.67
92.50
P
1
xP
4
60.38
259.63
14.77
38.33
38.17
98.33
83.33
90.83
P
1
xP
5
62.42
289.75
15.25
39.92
39.33
100.00
100.00
100.00
P
1
xP
6
62.63
272.29
15.47
34.73
31.00
98.33
90.00
94.17
P
1
xP
7
63.58
269.67
12.73
36.23
33.50
96.67
91.67
94.17
P
1
xP
8
63.00
266.29
13.23
38.83
37.67
96.67
91.67
94.17
P
2
xP
3
58.21
276.75
14.80
41.62
45.67
98.33
90.00
94.17
P
2
xP
4
56.63
250.46
13.93
38.73
36.67
100.00
100.00
100.00
P
2
xP
5
61.50
290.08
14.62
41.17
38.67
83.33
73.33
78.33
P
2
xP
6
59.00
258.88
15.30
39.07
35.67
100.00
100.00
100.00
P
2
xP
7
57.71
254.79
14.82
35.53
37.17
93.33
86.67
90.00
P
2
xP
8
57.04
267.75
13.57
37.67
42.00
93.33
83.33
88.33
P
3
xP
4
60.88
265.54
13.12
37.93
41.33
90.00
75.00
82.50
P
3
xP
5
62.29
290.54
12.75
38.97
39.00
86.67
83.33
85.00
P
3
xP
6
63.92
262.25
15.03
37.47
38.17
91.67
91.67
91.67
P
3
xP
7
62.71
261.17
13.63
37.67
39.00
93.33
75.00
84.17
P
3
xP
8
63.42
284.96
14.53
35.50
42.21
100.00
75.00
87.50
P
4
xP
5
62.63
275.25
14.17
33.83
31.67
98.33
91.67
95.00
P
4
xP
6
60.83
248.75
14.17
38.60
40.00
88.33
75.00
81.67
P
4
xP
7
58.38
252.21
14.12
40.87
37.67
83.33
66.67
75.00
P
4
xP
8
57.42
256.00
13.67
40.33
40.83
83.33
83.33
83.33
P
5
xP
6
61.38
283.00
11.93
41.73
40.00
100.00
93.33
96.67
P
5
xP
7
61.83
279.75
15.33
39.37
37.67
100.00
100.00
100.00
P
5
xP
8
59.67
281.00
13.20
37.83
37.47
100.00
96.67
98.33
P
6
xP
7
60.96
269.42
13.07
38.87
34.67
81.67
66.67
74.17
P
6
xP
8
60.21
268.08
13.10
39.81
38.67
76.67
78.33
77.50
P
7
xP
8
59.58
258.33
13.97
36.18
40.00
96.67
86.67
91.67
SC 168
65.00
290.00
12.00
32.40
34.00
97.00
86.00
91.50
SC Hytech 2055
69.00
302.00
12.13
43.20
48.33
98.00
93.00
95.50
mean of parent
69.05
179.80
10.79
28.30
30.77
93.33
87.58
90.46
mean of cross
60.71
269.15
14.06
38.95
38.28
93.23
85.86
89.54
mean of Genotype
62.79
251.75
13.27
36.65
36.85
93.25
86.18
89.71
L.S.D 5%
1.54
13.45
1.05
2.32
3.08
9.41
9.08
9.11
L.S.D 1%
2.02
17.64
1.37
3.04
4.04
12.48
12.04
11.95
N., Inf. and Comb. refer to normal, artificial infection by late wilt disease and combined analysis across the two
environments, respectively.
Impact Factor (JCC): 4.7987 NAAS Rating: 3.53
Diallel Cross Analysis for Earliness, Yield, Its Components and Resistance to Late Wilt in Maize
207
Table 2b: Mean performance of all genotypes for grain yield plant-1 and the yield superiority over SC 168 and SC
Hytech 2055 at normal environment (n), infection by late wilt (inf.) and across the previous environments
Genotype
Grain Yield Plant
-1
Relative Superiority (%)
N
Inf.
C.
P
1
140
132.33
136.17
P
2
77.33
71.33
74.33
P
3
53
50.67
51.83
P
4
98.67
89
93.83
P
5
91.67
89
90.33
P
6
164.33
143.33
153.83
P
7
81.67
78.33
80
Over Single Cross 168
Over Single Cross Hytech 2055
P
8
102.33
98.67
100.5
N
Inf.
Comb.
N
Inf.
Comb.
P
1
xP
2
260
255.67
257.83
33.33**
33.86**
33.59**
16.42**
12.96**
14.68**
P
1
xP
3
236.9
240.33
238.62
21.49**
25.83**
23.63**
6.07
6.19
6.13
P
1
xP
4
203
209.67
206.33
4.10
9.77*
6.91
-9.10**
-7.36*
-8.23**
P
1
xP
5
221.67
232.33
227
13.68**
21.64**
17.62**
-0.75
2.65
0.96
P
1
xP
6
163
158.67
160.83
-16.41**
-16.93**
-16.67**
-27.01**
-29.90**
-28.47**
P
1
xP
7
137.33
149
143.17
-29.57**
-21.99**
-25.82**
-38.51**
-34.17**
-36.32**
P1xP8
166.33
178.67
172.5
-14.70**
-6.46
-10.62**
-25.52**
-21.06**
-23.28**
P
2
xP
3
253.33
266
259.67
29.91**
39.27**
34.54**
13.43**
17.53**
15.49**
P
2
xP
4
199.33
190.67
195
2.22
-0.17
1.04
-10.75**
-15.76**
-13.27**
P
2
xP
5
220
221
220.5
12.82**
15.71**
14.25**
-1.49
-2.36
-1.93
P
2
xP
6
206.67
208
207.33
5.98
8.90*
7.43*
-7.46*
-8.10*
-7.78*
P
2
xP
7
180.6
188
184.3
-7.38
-1.57
-4.51
-19.13**
-16.94**
-18.03**
P
2
xP
8
214
195
204.5
9.74*
2.09
5.96
-4.18
-13.84**
-9.04**
P
3
xP
4
194
193.33
193.67
-0.51
1.22
0.35
-13.13**
-14.58**
-13.86**
P
3
xP
5
187
185.67
186.33
-4.1
-2.79
-3.45
-16.27**
-17.97**
-17.12**
P
3
xP
6
209
208
208.5
7.18
8.90*
8.03*
-6.42
-8.10*
-7.26*
P
3
xP
7
185.67
198
191.83
-4.79
3.66
-0.6
-16.87**
-12.52**
-14.68**
P
3
xP
8
215
233.67
224.33
10.26**
22.34**
16.23**
-3.73
3.24
-0.22
P
4
xP
5
152.67
143.67
148.17
-21.71**
-24.78**
-23.23**
-31.64**
-36.52**
-34.10**
P
4
xP
6
199.33
218.33
208.83
2.22
14.31**
8.20*
-10.75**
-3.53
-7.12*
P
4
xP
7
218.33
212.67
215.5
11.97**
11.34**
11.66**
-2.24
-6.04
-4.15
P
4
xP
8
222
227
224.5
13.85**
18.85**
16.32**
-0.6
0.29
-0.15
P
5
xP
6
181.2
194.33
187.77
-7.08
1.75
-2.71
-18.87**
-14.14**
-16.49**
P
5
xP
7
210
214.67
212.33
7.69*
12.39**
10.02**
-5.97
-5.15
-5.56
P
5
xP
8
191.67
190.67
191.17
-1.71
-0.17
-0.95
-14.18**
-15.76**
-14.97**
P
6
xP
7
157
167.67
162.33
-19.49**
-12.22**
-15.89**
-29.70**
-25.92**
-27.80**
P
6
xP
8
162
185
173.5
-16.92**
-3.14
-10.10**
-27.46**
-18.26**
-22.83**
P
7
xP
8
175
196
185.5
-10.26**
2.62
-3.89
-21.64**
-13.40**
-17.49**
SC 168
195
191
193
SC Hytech 2055
223.33
226.33
224.83
mean of parent
101.13
94.08
97.6
mean of cross
197.22
202.2
199.71
mean of
177.61
179.78
178.7
Genotype
L.S.D 5%
14.44
14.13
14.08
L.S.D 1%
19.15
18.74
18.46
*and ** indicate p< 0.05 and p< 0.01, respectively. N., Inf. and Comb. refer to normal, artificial infection by late wilt
disease and combined analysis across the two environments, respectively.
www.tjprc.org editor@tjprc.org
208 El Hosary A. A. A & I. A. I. El-Fiki
Table 3a: GCA effects (
i
g
ˆ
) of the studied parental inbred lines for earliness, plant height, no of rows ear-1 and
no of kernels row-1 and 100-kernel weight across the two environments
Parents
Days to
Plant
No of Rows
No of Kernels
100-Kernel
50% Silking
Height
Ear
-1
Row
-1
Weight
P
1
1.46**
-2.99**
0.38**
2.43**
-0.28*
P
2
-2.60**
5.42**
-0.02
0.56**
0.57**
P
3
0.21**
6.91**
-0.28**
-1.58**
1.59**
P
4
-1.27**
-2.14**
0.00
0.00
-0.35**
P
5
1.35**
3.44**
-0.20**
-0.43**
0.30*
P
6
0.76**
-0.81
0.72**
1.10**
-1.17**
P
7
0.70**
-6.71**
0.07
-1.40**
-1.32**
P
8
-0.59**
-3.12**
-0.67**
-0.68**
0.67**
L.S.D(0.05) gi
0.13
1.12
0.09
0.19
0.26
L.S.D(0.01) gi
0.17
1.47
0.11
0.25
0.34
L.S.D(0.05) gi-gj
0.24
2.13
0.17
0.37
0.49
L.S.D(0.01) gi-gj
0.32
2.79
0.22
0.48
0.64
r
0.88**
0.42
0.86**
0.88**
0.15
*and ** indicate p< 0.05 and p< 0.01, respectively. r indicate the correlation coefficient between
i
g
ˆ
effects for
parents and its mean performance
Table 3b: GCA effects
i
g
ˆ
of the studied parental inbred lines for resistant to late wilt% and grain yield
plant
-1
at both and across the studied environments
Parents
Resistant to Late Wilt %
Grain Yield Plant
-1
N
Inf.
Comb.
N
Inf.
Comb.
P
1
2.62**
4.94**
3.78**
8.55**
8.54**
8.54**
P
2
-0.21
1.11
0.45
10.58**
6.34**
8.46**
P
3
-2.71**
-7.56**
-5.13**
0.41
2.28
1.34*
P
4
-0.21
-1.89
-1.05**
0.32
-3.03*
-1.35*
P
5
3.12**
6.44**
4.78**
-3.52*
-4.32**
-3.92**
P
6
-0.71
0.44
-0.13
2.41
2.31
2.36**
P
7
0.12
-1.73
-0.80*
-15.55**
-12.09**
-13.82**
P
8
-2.04*
-1.76
-1.90**
-3.21*
-0.02
-1.62**
L.S.D(0.05) gi
1.97
1.90
0.76
3.02
2.96
1.17
L.S.D(0.01) gi
2.61
2.52
1.00
4.01
3.92
1.54
L.S.D(0.05) gi-gj
2.98
2.87
1.44
4.57
4.47
2.23
L.S.D(0.01) gi-gj
3.95
3.81
1.89
6.06
5.93
2.92
r
0.85**
0.89**
0.88**
0.27
0.30
0.29
* and ** indicate p< 0.05 and p< 0.01, respectively. r indicate the correlation coefficient between (
i
g
ˆ
) effects
for parents and its mean performance. N., Inf. and Comb. refer to normal, artificial i nfection by late wilt
disease and combined analysis across the two environments, respectively.
Impact Factor (JCC): 4.7987 NAAS Rating: 3.53
Diallel Cross Analysis for Earliness, Yield, Its Components and Resistance to Late Wilt in Maize
209
Table 4a: SCA effects
ij
S
^
of the studied diallel crosses for earliness, plant height, no of rows ear -1 and no of
kernels row-1 and 100-kernel weight across the two environments
Days to
Plant
No of
No of
100-
Crosses
50%
Rows
Kernels
Kernel
Height
Silking
Ear-1
Row
-1
Weight
P
1
xP
2
-1.91**
26.73**
1.31**
7.20**
2.11**
P
1
xP
3
-2.14**
11.99**
0.98**
9.61**
1.08
P
1
xP
4
-2.37**
15.46**
1.06**
-0.68
2.19**
P
1
xP
5
-2.95**
40.00**
1.74**
1.34*
2.71**
P
1
xP
6
-2.14**
26.79**
1.04**
-5.38**
-4.16**
P
1
xP
7
-1.13**
30.07**
-1.05**
-1.38**
-1.51*
P
1
xP
8
-0.42
23.10**
0.20
0.50
0.67
P
2
xP
3
-1.96**
15.13**
1.76**
6.06**
6.90**
P
2
xP
4
-2.06**
-2.11
0.l62*
1.60**
-0.16
P
2
xP
5
0.19
31.93**
1.50**
4.46**
1.19
P
2
xP
6
-1.71**
4.97
1.27**
0.82
-0.34
P
2
xP
7
-2.94**
6.79*
1.43**
-0.21
1.31
P
2
xP
8
-2.32**
16.15**
0.92**
1.21*
4.15**
P
3
xP
4
-0.62
11.48**
0.06
2.93**
3.48**
P
3
xP
5
-1.83**
30.90**
-0.11
4.40**
0.50
P
3
xP
6
0.39
6.85*
1.26**
1.36*
1.13
P
3
xP
7
-0.76*
11.67**
0.50*
4.06**
2.12**
P
3
xP
8
1.24**
31.87**
2.15**
1.18*
3.34**
P
4
xP
5
-0.01
24.66**
1.04**
-2.31**
-4.89**
P
4
xP
6
-1.21**
2.40
0.12
0.92
4.91**
P
4
xP
7
-3.61**
11.76**
0.71**
5.68**
2.72**
P
4
xP
8
-3.27**
11.96**
1.01**
4.44**
3.90**
P
5
xP
6
-3.29**
31.07**
-1.92**
4.48**
4.26**
P
5
xP
7
-2.77**
33.72**
2.13**
4.61**
2.08**
P
5
xP
8
-3.65**
31.38**
0.74**
2.37**
-0.11
P
6
xP
7
-3.05**
27.64**
-1.06**
2.58**
0.54
P
6
xP
8
-2.51**
22.71**
-0.28
2.80**
2.55**
P
7
xP
8
-3.08**
18.86**
1.23**
1.68**
4.04**
LSD5%(sij)
0.70
6.10
0.47
1.05
1.40
LSD1%(sij)
0.92
8.00
0.62
1.38
1.83
LSD5%(sij-sik)
1.03
9.02
0.70
1.56
2.07
LSD1%(sij-sik)
1.35
11.83
0.92
2.04
2.71
LSD5%(sij-skl)
0.34
3.01
0.23
0.52
0.69
LSD1%(sij-skl)
0.45
3.94
0.31
0.68
0.90
* and ** indicate p< 0.05 and p< 0.01, respectively.
www.tjprc.org editor@tjprc.org
210
El Hosary A. A. A & I. A. I. El -Fiki
Table 4b: SCA effects (
ij
S
^
) of the studied diallel crosses for resistance to late wilt disease and grain yield
plant-1 in both and across the studied environments
Crosses
Resistance to Late Wilt%
Grain Yield Plant
-1
N
inf.
N
inf.
N
inf.
P
1
xP
2
-15.43**
-17.04**
-16.23**
65.01**
62.61**
63.81**
P
1
xP
3
0.41
8.29**
4.35*
52.07**
51.34**
51.71**
P
1
xP
4
2.91
-5.71
-1.40
18.27**
25.97**
22.12**
P
1
xP
5
1.24
2.63
1.93
40.78**
49.94**
45.36**
P
1
xP
6
3.41
-1.37
1.02
-23.82**
-30.36**
-27.09**
P
1
xP
7
0.91
2.46
1.68
-31.53**
-25.63**
-28.58**
P
1
xP
8
3.07
2.49
2.78
-14.87**
-8.03
-11.45**
P
2
xP
3
8.24**
10.46**
9.35**
66.47**
79.21**
72.84**
P
2
xP
4
7.41*
14.79**
11.10**
12.56**
9.17*
10.87**
P
2
xP
5
-12.59**
-20.21**
-16.40**
37.08**
40.81**
38.94**
P
2
xP
6
7.91*
12.46**
10.18**
17.81**
21.17**
19.49**
P
2
xP
7
0.41
1.29
0.85
9.70*
15.57**
12.64**
P
2
xP
8
2.57
-2.01
0.28
30.76**
10.51*
20.64**
P
3
xP
4
-0.09
-1.54
-0.82
17.40**
15.91**
16.65**
P
3
xP
5
-6.76*
-1.54
-4.15*
14.25**
9.54*
11.89**
P
3
xP
6
2.07
12.79**
7.43**
30.31**
25.24**
27.78**
P
3
xP
7
2.91
-1.71
0.60
24.94**
29.64**
27.29**
P
3
xP
8
11.74**
-1.67
5.03*
41.93**
53.24**
47.59**
P
4
xP
5
2.41
1.13
1.77
-20.00**
-27.16**
-23.58**
P
4
xP
6
-3.76
-9.54**
-6.65**
20.74**
40.87**
30.81**
P
4
xP
7
-9.59**
-15.71**
-12.65**
57.70**
49.61**
53.65**
P
4
xP
8
-7.43*
0.99
-3.22
49.02**
51.87**
50.45**
P
5
xP
6
4.57
0.46
2.52
6.45
18.17**
12.31**
P
5
xP
7
3.74
9.29**
6.52**
53.21**
52.91**
53.06**
P
5
xP
8
5.91
5.99*
5.95**
22.54**
16.84**
19.69**
P
6
xP
7
-10.76**
-18.04**
-14.40**
-5.72
-0.73
-3.22
P
6
xP
8
-13.59**
-6.34*
-9.97**
-13.06**
4.54
-4.26
P
7
xP
8
5.57
4.16
4.87*
17.90**
29.94**
23.92**
LSD5%(sij)
6.03
5.83
4.13
9.26
9.06
6.38
LSD1%(sij)
8.00
7.73
5.42
12.29
12.02
8.37
LSD5%(sij-sik)
8.93
8.62
6.11
13.71
13.41
9.44
LSD1%(sij-sik)
11.84
11.44
8.01
18.18
17.79
12.38
LSD5%(sij-skl)
8.42
8.13
2.04
12.92
12.64
3.15
LSD1%(sij-skl)
11.17
10.78
2.67
17.14
16.77
4.13
*and ** indicate p< 0.05 and p< 0.01, respectively. N., Inf. and Comb. refer to normal, infection by late wilt
disease and combined analysis across the two environments, respectively.
Impact Factor (JCC): 4.7987 NAAS Rating: 3.53
... These estimates can then be used to draw inferences about the genetic systems involved for yield and its components and the best breeding strategy to improve them. In this respect, the additive gene effects have been reported to be important in the genetic expression of maize grain yield (Wattoo et al., 2014;Sultan et al., 2016;Keimeso et al., 2020 andOnejeme et al., 2020), however, other researchers reported that the non-additive genetic effects represented the major role in the inheritance of maize grain yield and most of its components (Azad et al. 2014;Abdel-Moneam et al., 2015;EL-Hosary and EL-Fiki 2015;Turkey et al., 2018;Imam et al., 2020 andPatel 2022). These differences generally arise due to differences in the genetic materials and the environments under which the experiments were performed. ...
... The results showed that mean squares of sowing dates were highly significant for all studied traits indicating that these characteristics were influenced by sowing dates. Similar results were detected by El-Hosary and El-Fiki (2015), Hassaan (2018), Turkey et al. (2018) and Turk et al. (2020). Meantime, the variance due to genotypes were highly significant for all the studied traits suggesting the presence of wide genetic variability among the studied maize crosses which could be used in maize breeding programs for improving grain yield and the related characters. ...
Article
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A half diallel set of crosses were made among seven inbred lines of white maize during 2021 growing season to estimate combining ability for days to 50% tasseling, days to 50% silking, plant height, ear height, ear leaf area, chlorophyll content, number of rows per ear, number of kernels per row, ear length, ear diameter, 100-kernels weight and grain yield per plant under two sowing dates (14 th of May "recommended date" and 14 th of June "late sowing date") in two separate field experiments. Each experiment included 21 F1 hybrids and the check variety SC 128 in a randomized complete block design with three replications during 2022 season. Results indicated that mean squares due to genotypes, sowing dates and the interactions between them were significant / or highly significant for all the studied traits. Mean squares due to GCA, SCA and their interactions with sowing dates were highly significant for all the studied traits. The ratios of GCA/SCA variances were less than the unity for all the studied traits indicating that the non-additive genetic effects had the main role of the expression of these traits. The parental inbred lines P3, P4 and P7 seemed to be good general combiners for grain yield and most studied traits under the two sowing dates. The crosses P1xP4, P2xP6, P3xP5, P3xP7 and P6xP7 were the best cross-combinations for grain yield and most of the studied traits under two sowing dates.
... Many authors mentioned that SCA effects are caused by genes that are non-additive (dominant or epistasis), whereas GCA effects are caused by genes that are additive in nature. They also emphasized the importance of non-additive gene activation for specific cotton characteristics [6][7][8][9][10][11][12]. They stressed upon the appreciable degree of variance to GCA and cleared the mean squares due to GCA and SCA were highly significant however the genetic variances due to SCA were greater than GCA for the yield traits showing the nonadditive gene action [13,14]. ...
... These promising hybrids could be selected for further recombination breeding programs based on their performance and significant specific combining ability. Nevertheless, not all of F1 hybrid combinations showed positive SCA values for all the evaluated traits concurrently, stating that specific hybrid combinations having high significant SCA for several traits had both parents with a good GCA [7,61,84,85]. ...
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To generate high-yielding cultivars with favorable fiber quality traits, cotton breeders can use information about combining ability and gene activity within a population to locate elite parents and potential F1 crosses. To this end, in the current study, twelve cotton parents (eight genotypes as female parents and four testers) and their F1 crosses obtained utilizing the linex tester mating design were evaluated for their general and specialized combining abilities (GCA and SCA, respectively) of yield traits. The findings showed that for all the investigated variables, variances owing to genotypes, parents, crosses, and parent vs cross showed extremely significant (P ≤ 0.01) differences. Additionally, throughout the course of two growing seasons, the mean squares for genotypes (parents and crosses) showed strong significance for all the variables under study. The greatest and most desired means for all the examined qualities were in the parent G.94, Pima S6, and tester G.86. The best crossings for the qualities examined were G.86 (G.89 × G.86), G.93 × Suvin, and G.86 × Suvin. The parents' Suvin, G89x G86 and TNB were shown to have the most desired general combining ability effects for seed cotton yield/plant, lint yield/plant, boll weight, number of bolls/plants, and lint index, while Suvin, G.96 and pima S6 were preferred for favored lint percentage. For seed cotton yield, lint percentage, boll weight, and number of bolls per plant per year, the cross-G.86 x (G.89 × G.86) displayed highly significant specific combining ability impacts. The crosses G.86 × Suvin, Kar x TNB, G.93 × Suvin, and G.93 × TNB for all the studied traits for each year and their combined were found to have highly significant positive heterotic effects relative to better parent , and they could be used in future cotton breeding programs for improving the studied traits.
... GCA reflects additive gene effects, while SCA indicates non-additive effects, which influence hybrid performance relative to their parent lines. Research suggests that additive genetic effects play a significant role in late wilt disease resistance [28], while non-additive gene action holds greater significance in determining grain yield under various environmental conditions [29][30][31]. However, there is still a lack of detailed understanding regarding the interaction between late wilt resistance and high yield potential in maize hybrids. ...
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Citation: Ghazy, N.A.; Al-Zaban, M.I.; Safhi, F.A.; Aljabri, M.; Kafsheer, D.A.; Ben Abdelmalek, I.; Kamara, M.M.; Mansour, E.; Hamden, S. Unraveling Abstract: Late wilt disease caused by the fungal pathogen Magnaporthiopsis maydis represents a major threat to maize cultivation in the Mediterranean region. Developing resistant hybrids and high-yielding offers a cost-effective and environmentally sustainable solution to mitigate yield losses. Therefore, this study evaluated genetic variation, combining abilities, and inheritance patterns in newly developed twenty-seven maize hybrids for grain yield and resistance to late wilt disease under artificial inoculation across two growing seasons. The results indicated highly significant variations among assessed hybrids for all measured traits. Combining ability analysis identified IL-306, IL-304, and IL-303 as excellent combiners for grain yield and late wilt resistance, positioning them as superior candidates for hybrid development. Additionally, IL-302 was identified as a strong general combiner for earliness, and IL-307 and IL-309 demonstrated potential for producing short-statured hybrids critical for improving lodging tolerance and maximizing yield. Specific combining ability effects indicated promising earliness, yield, and disease-resistance hybrids, including IL-303×T2 and IL-306×T1. GGE biplots presented optimal line×tester combinations, offering strategic guidance for hybrid development. The principal component analysis demonstrated strong associations between grain yield, late wilt resistance, and key agronomic traits, such as ear length and kernel number. The observed robust positive association between grain yield, late wilt resistance, and yield attributes suggests selection potential for improving maize productivity. Moreover, the genotypic correlations revealed that earlier silking, taller plants, and higher kernel counts were strongly linked to enhanced yield potential. Genetic parameter estimates indicated a predominance of non-additive genetic effects for most traits, with moderate to high broad-sense heritability suggesting substantial genetic contributions to phenotypic variance. This research provides valuable insights to support the development of disease-resistant and high-yielding maize hybrids addressing critical food security challenges.
... al., 2014); the cause of late wilt disease (Samra et al., 1962;Samra et al., 1968;El-Naggar et al., 2015;El-Naggar, 2019). This disease is significantly affects the sensitive maize hybrids (El-Shehawy, et al., 2014;El-Hosary and El-Fiki, 2015) and subsequently increases the loss in the final grain yield (El-Naggar et al., 2015). Due to the risk of this disease (Payak et al., 1970;Pecsi and Nemeth, 1998;Molinero-Ruiz et al., 2010, andDrori et al., 2013;El-Naggar et al., 2015), several attempts have been interested to reduce its negative impact (Abd-El-Rahim, et al, 1982;Shalaby, et al., 2009;Ghazy and El-Nahrawy, 2020;El-Naggar and Yassin, 2024). ...
... It has been reported to cause severe damage in the Egyptian maize hybrids [9,10]. However, negative correlation had been previously found between disease incidence and grain yield [11,12]. ...
... Quantitative Trait Locus/Loci (QTL) conferring LWD tolerance have been detected and validated as a step toward this end (Al Taweel 2013; Sunitha et al. 2021). Several studies indicate the possibility that many genes are involved in controlling LWD resistance in maize (El-Hosary and El-Fiki 2015). Further research investigation is essential to identify stable QTL with large phenotypic variation explained (Sunitha et al. 2021). ...
Chapter
Maize late wilt disease (LWD) is typified by a vascular occultation that occurs late in plant development, usually during or after flowering. The disease causal agent, the soil and seed-borne fungi, Magnaporthiopsis maydis, causes significant economic losses in Egypt, Israel, Spain, Portugal, and India. Since its discovery in the early 1960s in Egypt, the knowledge base of the disease was significantly expanded. This includes basic information on the pathogen and its mode of action, disease symptoms and damages, methods to study and monitor the pathogen, and above all, control strategies to restrain M. maydis and reduce its impact on commercial maize production. Three approaches stand out from the various control methods inspected. First, the traditional use of chemical pesticides was investigated extensively. This approach gained attention when, in 2018–2020, a feasible and economical treatment based on Azoxystrobin (alone or in combination with other fungicides) was proven to be effective even in severe cases of LWD. Second, the growing trend of replacing chemical treatments with eco-friendly biological and other green protocols has become increasingly important in recent years and has already made significant achievements. Last but not least, today’s leading strategy to cope with LWD is to rely on resistant maize genotypes. The past two decades’ introduction of molecular-based diagnostic methods to track and identify the pathogen marked significant progress in this global effort. Still, worldwide research efforts are progressing relatively slowly since the disease is considered exotic and unfamiliar in most parts of the world. The current review summarizes the accumulated knowledge on LWD, its causal agent, and the disease implications. An additional important aspect that will be addressed is a future perspective on risks and knowledge gaps.
... The genetic heterogeneity makes it easier to identify preferred genes and hence prospective genotypes according to agronomic productivity and LWD resistance (Kamara et al., 2021). Similarly, El-Hosary and El-Fiki (2015) and Mosa et al. (2017) reported genetic variations in maize hybrids for grain yield and LWD resistance. Moreover, the presence, prevalence, and severity of plant pathogens are influenced by climate change. ...
... Maximizing agricultural production depends mainly on promoting early maturing high-yielding corn hybrids to cover the mounting consumption of corn genotypes. It depends mostly on diallel crosses utilizing combining ability mating patterns for distinguishing early-maturing high-yielding hybrids and helps to identify the most appropriate parents along with their best combining ability and dimension of gene actions (El-Hosary and El-Fiki, 2015;Ibrar et al., 2021). In this regard, the application of Griffing's approach (Griffing, 1956) has been all-encompassing to understand the type and magnitude of the genetic effects in parents using offspring data for traits of interest (Glover et al., 2005;Fahad et al., 2020;Revilla et al., 2021). ...
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Early maturity and genotype by environment interaction (GEI) have always been challenging concerns for breeders in selecting appropriate parents for breeding programs. The presented study aimed to investigate early maturity and the dimension of gene action, as well as, assess the performance of half-diallel populations using eight advanced sweet corn inbred lines and their 28 F1 hybrids with two commercial checks for maturity and yield-related traits in the spring of 2018 at the Nowshera (plain) and Swat (hilly) areas, Khyber Pakhtunkhwa, Pakistan. Analysis revealed significant differences among the genotypes for the studied traits over both locations. General combining ability (GCA) effects were significant for all the traits at both the agro-climatic conditions, except 100-kernel weight, with the specific combining ability (SCA) effects relevant for grain yield at both locations. The GCA-SCA ratio for studied traits indicated dominance gene action, which also gained support by higher values of SCA than GCA variances. Based on the results, the identified inbred lines SWTS-1-8 and SODS-1 serve as good general combiners for traits like earliness and grain yield attributes, making them better parents to improve the stated characteristics in sweet corn. However, the F1 hybrids, i.e., NARCCCRI-19 × CCRI-34 at Nowshera and CCRI-34 × SODS-1 at Swat, showed the best specific combiners for maturity. Likewise, F1 hybrids, i.e., SWTS-1-4 × SWTS-1-8 and SWTS-1-8 × CCRIS-34, emerged as desirable for grain yield at Nowshera and Swat, respectively. The inbred lines for the mentioned hybrids can be a source of germplasm improvement, breaking through undesirable linkages in future sweet corn breeding programs.
... Yet, today's primary means to contain the disease relies on resistant maize hybrids [16,[39][40][41]. This environmentally-friendly and cost-effective strategy requires constant efforts to scan and identify new resistant varieties. ...
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Full-text available
Context Maize late wilt disease caused by the fungus Magnaporthiopsis maydis significantly damages crops in Israel and in other countries. Resistant maize cultivars are the preferred method for restraining the disease. However, the pathogen populations of Spain and Egypt have varying aggressiveness, and virulent strains can overcome host resistance. In 2001 and from 2016-2019, 17 M. maydis strains were isolated from infected maize fields in Israel. Objective The current study characterized the difference in virulence among those isolates. Methods The isolates’ effects on seed germination, plant development, and severity of disease symptoms were evaluated. Results and conclusions The isolates from Israel display a diverse degree of aggressiveness that is not linked to their geographic distribution. The virulent strains are found in mixed populations, whereas less virulent M. maydis isolates exist. Aggressive strains harmed the development of plants and ears and caused severe wilting and death. In contrast, plants inoculated with less virulent strains exhibited only mild dehydration signs, and crop yield was similar to that of the non-infected control. Interestingly, different host cultivars can evoke specific virulence of M. maydis strains. Moreover, some pathogen strains significantly repress plant development, while the impact of other strains was evidenced by wilting symptoms. Significance The current research further increases our understanding of the pathogen and our ability to control it.
... For controlling the late wilt disease of corn, several management strategies have been developed. One of the most effective methods for disease control is using resistant cultivars [3,10]. The National Maize Program at the Agricultural Research Center in Giza, Egypt, has identified many sources of resistance through the screening of thousands of local and exotic germ lines since 1963. ...
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The rapid spread of late wilt disease among maize cultivations has resulted in serious economic losses in many countries. Harpophora maydis is the main cause of this destructive vascular disease. Here we evaluate the fungicidal activity of chitosan and nano-chitosan against six aggressive isolates of H. maydis collected from different Egyptian governorates. Pathogenicity tests for these isolates show that the highest disease severity was found for the Giza isolate. The isolates were tested for their response to the fungicide Permis, chitosan, and nano-chitosan treatments in vitro and in vivo. Nano-chitosan treatments fully inhibited the radial growth of H. maydis isolates at concentrations of 5 and 10 mM, compared to the full control growth (9 cm in diameter). On the other hand, in vitro, in vivo, and molecular diagnosis results showed high antifungal activity of chitosan and nano-chitosan compared to the Permis fungicide. Chitosan at the nano and normal scales proved a potent ability to enhance plant resistance in response to H. maydis. Disease severity (DS%) was extremely decreased among the tested cultivars by using nano-chitosan; the highest percentage was obtained on Giza 178 cv, where the DS% was 21.7% compared to 42.3% for the control. Meanwhile, the lowest percentage was obtained on Giza 180 cv with DS% 31.2 and the control with 41.3%. The plants treated with nano-chitosan showed the highest growth parameters for all cultivars. Such natural treatments could reduce the impact on the environment as they are non-pollutant natural compounds, protect the plants by reducing fungal activity, and induce plant resistance.
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A half diallel cross among 5 inbred lines of maize was evaluated under two different nitrogen rates for yield and yield components characters i.e., ears No. plant-1, ear length, ear diameter, 100-kernel weight, grain yield plant-1 and shelling percentage to evaluate the role of GCA and SCA of inbred lines in hybrids performance under normal and stress of nitrogen levels and to establish the magnitude of heterosis. Mean squares of genotypes were highly significant for all studied traits under both nitrogen levels, except shelling percentage under normal nitrogen level. General and specific combining ability (GCA and SCA) mean squares were significant or highly significant for all studied traits, except shelling percentage under normal nitrogen level at GCA and SCA. GCA/SCA ratios revealed that the non-additive gene action for all studied traits under both nitrogen levels was detected. The best combiners were P4 (Inb.204) and P5 (Inb.213) for most of studied traits under normal and stress nitrogen levels. This result indicated that these inbred lines could be considered as good combiners for improving these traits. The best crosses for ears No. plant-1 were P1 (Inb.84) ×P3 (inb.144) and P3 (Inb.144) ×P4 (Inb.204), for ear length was P2 (Ink95) ×P4 (Inb.204), for ear diameter was P1 (Inb.84) ×P3 (Inb.213), for 100-kernel weight was P2 (Inb.95) ×P4 (Inb.204) and for gram yield plant-1 was P1 (Inb.84) ×P3 (Inb.144) under both nitrogen levels. These crosses could be selected and used in breeding programs for improving these traits. Results showed significant or highly significant heterosis over mid or better parents for all studied traits, except shelling percentage under normal nitrogen level. The best crosses over both their mid-parents and better-parent for ears No. plant-1 was P3 (Inb.144) ×P4 (Inb.204), for ear length was P2 (Inb.95) ×P4 (Inb.204), for ear diameter was P-1 (Inb.84) ×P5 (Inb.213), for 100-kernel weight was P2 (Inb.95) ×P4 (Inb.204), for grain yield plant-1 was P1 (Inb.84) ×P3 (Inb.144) under both nitrogen levels and for shelling percentage was P1 (Inb.84) ×P3 (Inb.144) under stress nitrogen level.
Article
Gray leaf spot disease (GLS; caused by Cerco- spora zeae-maydis Tehon and Daniels) is among the major maize (Zea mays L.) production con- straints in southern Africa. Maize is predomi- nantly grown by small-scale farmers without fungicides; hence, there is need to develop GLS resistant hybrids. There is limited information about the mode of inheritance for GLS resis- tance in regionally adapted germplasm. This study was initiated to determine gene action controlling GLS resistance. Seventy-two hybrids were generated by mating 27 inbred lines in a North Carolina design II scheme. Experimental and check hybrids were evaluated in an 8 by 12 α-lattice design with two replications at three locations, during the 2004-2005 season. There was signifi cant variation among the hybrids for GLS resistance and yield. Inbreds L13, L15, L18, L19, and L24, from A, N3, B, K, and SC heterotic groups, respectively, contributed high levels of resistance to hybrids. Both general combin- ing ability (GCA) and specifi c combining ability (SCA) effects were highly signifi cant (P < 0.01), but the predominance of GCA for GLS (86%) and yield (74%) indicated that additive effects were more important than nonadditive gene action in controlling both traits. Hybrids ranked similarly for GLS across environments, suggest- ing that few signifi cant crossover genotype by environment interactions, which would cause problems in hybrid selection, were observed. Overall, results indicated that it would be readily possible to develop inbred lines with high GLS resistance from this germplasm.
Article
F1 generation of 6x6 diallel cross of maize (Zea mays) was evaluated for combining ability effects under normal and high temperature conditions in the Department of Plant Breeding and Genetics, University of Agriculture Faisalabad during 2005-06. The mean squares due to genotypes, GCA, SCA and reciprocal effects were found as highly significant except non-significant to GCA effect for 100-grain weight under high temperature condition. The GCA/ SCA variance ratio exhibited that all traits were predominantly under non-additive control. The inbred line 935006 was found as the best general combiner with better mean performance for all traits under both temperatures followed by R2304-2 and F 165-2-4. The best cross was cross 935006 x R 2304-2 and its reciprocal followed by F 165-2-4 x R 2304-2, F 165-2-4 x 935006 and R 2205.5-4 x R 2304-2 and their reciprocals. These crosses showed good positive SCA effects alongwith better mean performance for grain yield per plant and most of the traits under both temperature regimes.
Heterosis and combining ability of six inbred lines of maize in diallel crosses over two years
  • A A El-Hosary
El-Hosary, A.A. (1989). Heterosis and combining ability of six inbred lines of maize in diallel crosses over two years. Egypt. J. Agron. 14(1-2): 47-58