ASSESSMENT OF GENETIC PARAMETERS FOR EARLY
MATURING AND GRAIN YIELD IN SOME BREAD
WHEAT CROSSES UNDER OPTIMUM AND LATE
SOWING DATES
Waleed Zaki El-Yamany Farhat
Wheat Research Department, Field Crops Research Institute, ARC, Egypt
wayosha@yahoo.com
Key Words: Wheat, earliness, grain yield, additive, dominance,
epistasis, six populations, generation mean analysis,
genotypic correlation.
ABSTRACT
Considerable attention is paid in the Egyptian National Wheat
Research Program to develop early maturing and high yielding cultivars.
Therefore, six early to moderate maturing bread wheat lines were crossed to
produce three cross populations. The six populations model was used
through three growing seasons from 2017/18 to 2019/20. The objective was
to determine the intra- and inter-allelic gene interactions controlling
earliness and some agronomic traits as well as identify the best germplasm
which had accumulated early maturing gene pool. Results showed that late
sowing date in end of December decreased all studied traits. Both additive
and dominance gene effects and variances were important in inheritance of
the studied traits. Additive effects and variance were larger than
corresponding dominance ones in most cases. Heritability in broad and
narrow sense and expected genetic advance as percent of F2 mean were
moderate to high for all the studied traits. Negative and significant
phenotypic and genotypic correlation between grain yield and earliness traits
were obtained. Generally, most biometrical parameters resulted from cross 2
(line 3 x line 4) and cross 3 (line 5 x line 6) were higher in magnitude
compared to cross 1 (line 1 x line 2), thus, these two crosses would be used
in breeding program for improving earliness and grain yield traits.
INTRODUCTION
Wheat (Triticum aestivum L.) is one of the most important and
strategic cereal crops worldwide. In Egypt, wheat is the main winter
cereal crop used as a staple food for urban and rural societies and the
major source of straw for animal feed.
Considerable attention is paid in the Egyptian National Wheat
Research Program to develop early maturing and high yielding cultivars.
Early maturing allows to escape of environmental stresses like disease
and heat in the end of growing season (Acquaah, 2012). Also, shortduration
wheat varieties are often preferred by farmers for use in crop
intensification. They also require fewer inputs, especially for irrigation,
Egypt. J. of Appl. Sci., 35 (11) 2020 144-162
due to the shorter crop cycle (Mondal et al. 2016). On the other hand,
early maturity genotypes only partially exploit the growing season and
economic yield may be significantly reduced. However, it is known that
longer growth duration is associated with high grain yield (Acquaah,
2012).
Crop maturity in general is affected by many factors in the
environment conditions, including photoperiod, temperature, altitude,
relative humidity, soil fertility, and plant genotype (Acquaah, 2012).
Accordingly, a better understanding of earliness inheritance and type of
gene action would help wheat breeders to efficiently improve early
maturing with high yielding cultivars.
Selection of early maturing genotypes under conflicting
environments like sowing dates, receive more attention in wheat breeding
programs. Late sowing dates in Egypt cause heat stress for wheat plants
during grain filling period resulting in grain yield losses (Abd El-Rady
2018, Abdallah et al. 2019, Farhat et al. 2019 and Koubisy 2019).
Therefore, the present study aimed to enhance wheat breeding
program efficiency through (1) determining intra- and inter-allelic gene
interactions controlling earliness and agronomic traits in three cross
populations of bread wheat, (2) assessing some genetic parameters which
improve selection in segregating generations, and (3) identifying best
genotypes had accumulated early maturing gene pool.
MATERIALS AND METHODS
The present study was carried out at the Experimental Farm of
Sakha Agricultural Research Station, Kafr El-Sheikh, Egypt through three
wheat growing seasons of 2017/18, 2018/19 and 2019/2020. Six moderate to
early maturing bread wheat lines were used as parents. Name, pedigree and
selection history in addition to days to heading and maturity in last 5 wheat
growing seasons which were recorded by National Wheat Research Program
for these parents are presented in Table (1).
In 2017/18, F1 hybrids were obtained for Line 1 x Line 2 (cross
1), Line 3 x Line 4 (Cross 2) and Line 5 x Line 6 (cross 3). In 2018/19,
BC1 (F1 x P1), BC2 (F1 x P2) and F2 seeds were produced for each cross.
In the third season (2019/20), the six populations of each cross (P1, P2,
F1, BC1, BC2 and F2) were evaluated under optimum sowing date (24
November, 2019) and Late sowing date (24 December, 2019) in three
replications. Each replication for each cross consisted of 6 rows for each
population. The rows were 4 m long with 30 apart and 15 cm within
rows. All the recommended cultural practices for wheat production in
north Delta were applied at the proper time. Maximum and minimum
temperatures were presented in Figure (1) according to Sakha
meteorological station.
145 Egypt. J. of Appl. Sci., 35 (11) 2020
Table 1: Name, pedigree, days to heading and maturity in last 5
wheat growing seasons of the studied parents.
Name Pedigree Selection history
Number
of days
to
heading
Number
of days
to
maturity
Line 1 PRL/2*PASTOR//KACHU/3/TRCH/SRTU//KACHU
CMSS10Y00993T-
099TOPM-099Y-
099M-14WGY-0B
87-99 137-155
Line 2
CHEN / AEGILOPS SQUARROSA (TAUS) // BCN
/3/ 2*KAUZ /4/ HAAMA-11
S. 16276 -018S-
010S-3S-0S
75-86 128-139
Line 3
DVERD 2 / AE - SQUARROSA (214) // 2* BCN /3/
GIZA 168 /8/MAI "S" / PJ // ENU "S" /3/ KITO /
POTO. 19 // MO / JUP /4/ K 134 (60) / VEE/7/KAUZ
/6/ ATL 66 / H567.71 // ATL 66 /5/ PMN5 // S948.A1 /
4*CNO67 /3/ PMNS /4/ CMH75A.66
S. 16832 -020S -
08S-1S -0S
83-93 133-137
Line 4
NING MAI 50 /6/ SAKHA 12 /5/ KVZ // CNO 67 / PJ
62 /3/ YD "S" / BLO "S" /4/ K 134 (60) / VEE
S. 16604 -073S -
010S-6S -0S
86-88 140-147
Line 5 WBLL1*2/BRAMBLING // HUBARA-21
S. 17017 -056S -
019S-1S -0S
83-92 133-139
Line 6
TOBA97/ATTILA /8/ KAUZ / ATTILA /7/ KVZ /4/
CC / INIA /3/ CNO // ELGAU / SON 64 /5/
SPARROW "S" / BROCHIS "S" /6/ BAYA "S" /
IMU
S.2011-29-26S-08S-
2S-0S
75-85 126-132
Figure 1: Maximum (Max) and minimum (Min) temperatures in
2019/20 season of wheat growing at Sakha.
Data were recorded on individual plants in the central four rows
and represented by 20 plants for each parent and F1, 50 plants for each
backcross, and 70 plants for each F2 in each replication. The studied traits
were days to heading (DH), days to maturity (DM), grain filling period
Egypt. J. of Appl. Sci., 35 (11) 2020 146
(GFP), grain filling rate (GFR, g day-1 plant-1), plant height (PH, cm),
number of spikes plant-1 (SP) and grain yield plant-1 (GY, g).
The analysis of variance was performed using randomized
complete block design and LSD were calculated to test the significance
of differences among means according to Steel et al. (1997). Difference
between F2 and corresponding environmental variances was tested by F
ratio. Significance of F ratio indicate enough variability in the studied
material to estimate the components of genetic variance. Mather's
(1949) scaling test was performed for confirmation of additivedominance
model reported by Singh and Chaudhary (2010). Estimates
of variances gene effects, allelic interaction and their test of significance
were computed by six-parameter model of Jinks and Jones (1958).
Environmental variance was calculated as the average variances of the
two parents and F1 plants. Genotypic variance was estimated by
subtracting the environmental variance from corresponding phenotypic
variance in F2 populations. Broad and narrow sense heritability and
expected genetic advance from selection as percentage of F2 mean were
estimated according to Mather and Jinks (1982). The phenotypic and
genotypic correlation between grain yield and other studied traits was
estimated for every population under the two sowing dates according to
Steel et al. (1997).
RESULTS AND DISCUSSIONS
The variance for each population in each cross is presented in
Table (2). Highest variance was obtained by the F2 population for all
studied traits in the three crosses, followed by that of backcross
populations (BC1's and BC2's), reporting that the maximum heterogeneity
exists in F2 population. On the other hand, the lowest variance was
obtained by parents (P1's and P2's) and F1 populations, indicating to the
homogeneity of these populations and their variance is due to
environmental factors. These results may be logic and suggests the
validity of estimating the appropriate genetic model and determine the
different gene effects for the studied traits of the three cross populations.
Mean performance
Mean performance of the populations in the three studied crosses
are given in Table (3). The wheat breeder prefers the lowest values of
DH, DM, GFP and PH. Means values for all traits of studied crosses
decreased under late sowing date compared to optimum one, except for
GFR in cross 2 and 3.
147 Egypt. J. of Appl. Sci., 35 (11) 2020
Table 2: The variances for all studied traits of studied six
populations in the three wheat crosses under optimum (SD1)
and late (SD2) sowing dates.
Traits
Sowing
date
P1 P2 F1 F2 BC1 BC2
Cross 1 (Line 1 x Line 2)
DH
SD1 4.87 3.92 4.79 22.04 16.57 10.17
SD2 7.64 7.79 5.28 26.06 11.66 24.23
DM
SD1 2.93 1.71 1.99 8.38 5.64 9.93
SD2 4.43 2.14 3.05 10.43 6.55 7.86
GFP
SD1 5.58 4.73 4.99 15.23 12.55 12.91
SD2 2.18 6.5 3.13 14.00 10.22 13.75
GFR
SD1 0.026 0.028 0.007 0.238 0.151 0.109
SD2 0.028 0.021 0.006 0.077 0.075 0.035
PH
SD1 4.07 8.83 5.50 24.41 10.92 32.21
SD2 6.35 6.18 7.80 67.59 38.85 36.58
SP
SD1 12.32 9.86 8.18 61.43 41.37 30.71
SD2 17.26 3.58 8.71 47.06 25.24 32.02
GY
SD1 75.42 79.86 16.95 703.13 452.26 311.01
SD2 55.45 39.73 10.15 162.43 138.95 73.56
Cross 2 (Line 3 x Line 4)
DH
SD1 2.25 7.1 3.75 17.36 13.75 17.80
SD2 5.95 7.70 8.88 23.17 15.97 17.83
DM
SD1 6.15 8.88 3.46 16.69 12.60 10.44
SD2 4.3 2.06 4.30 10.70 11.09 7.70
GFP
SD1 8.15 14.29 4.38 18.91 20.06 16.09
SD2 6.39 5.73 6.25 14.38 11.86 9.12
GFR
SD1 0.03 0.04 0.01 0.12 0.08 0.09
SD2 0.001 0.001 0.001 0.06 0.05 0.08
PH
SD1 5.5 6.63 6.33 34.12 25.46 14.86
SD2 4.77 4.77 9.07 42.45 29.67 24.64
SP
SD1 10.47 18.10 11.15 43.78 31.29 34.26
SD2 15.34 15.68 12.08 41.79 28.68 32.57
GY
SD1 85.85 89.98 16.95 408.45 252.08 316.19
SD2 3.13 1.36 3.84 164.54 92.62 153.17
Cross 3 (Line 5 x Line 6)
DH
SD1 5.94 3.44 5.71 18.93 14.11 13.62
SD2 8.44 1.34 7.12 35.05 20.43 21.47
DM
SD1 6.76 1.13 3.23 20.88 11.78 20.54
SD2 7.17 1.30 3.23 13.49 10.85 10.29
GFP
SD1 8.12 4.00 8.52 15.27 14.96 15.41
SD2 8.02 2.10 10.15 13.58 13.44 13.40
GFR
SD1 0.02 0.02 0.01 0.09 0.07 0.08
SD2 0.04 0.03 0.01 0.07 0.07 0.06
PH
SD1 10.06 4.94 9.17 17.83 16.33 15.03
SD2 13.07 12.28 9.17 49.61 31.80 31.35
SP
SD1 9.83 9.50 8.33 38.02 22.26 25.83
SD2 10.89 8.19 11.83 26.12 20.44 17.31
GY
SD1 78.49 84.61 29.02 321.31 209.48 235.31
SD2 73.75 54.24 7.58 152.82 153.12 115.72
DH = days to heading, DM = days to maturity, GFP = grain filling period, GFR =
grain filling rate (g day-1 plant-1), PH = plant height (cm), SP = number of spikes
plant-1 and GY = grain yield plant-1.
Egypt. J. of Appl. Sci., 35 (11) 2020 148
Table 3: Mean performance of the six populations in the three
crosses for studied traits under optimum (SD1) and late (SD2)
sowing dates.
Trait
Sowing
date
P1 P2 MP F1 F2 BC1 BC2 LSD0.05
Cross 1 (Line 1 x Line 2)
DH
SD1 96.3 83.9 90.1 90.2 91.9 95.2 88.7 1.6
SD2 91.0 81.7 86.4 88.9 87.2 88.2 82.4 2.1
DM
SD1 149.5 139.0 144.2 145.2 146.2 149.2 144.0 0.7
SD2 135.9 126.9 131.4 133.4 131.8 132.9 129.0 1.5
GFP
SD1 53.3 55.1 54.2 54.9 54.2 54.0 55.3 1.3
SD2 44.8 45.2 45.0 44.5 44.6 44.7 46.5 1.1
GFR
SD1 1.19 0.80 1.00 0.82 1.13 0.95 0.82 0.10
SD2 0.88 0.64 0.76 0.98 0.78 0.78 0.57 0.07
PH
SD1 106.0 87.3 96.6 101.6 96.4 93.5 79.0 1.5
SD2 82.4 72.1 77.3 88.0 80.0 89.7 77.9 1.5
SP
SD1 26.6 18.6 22.6 14.0 23.0 20.4 21.0 2.3
SD2 25.6 17.8 21.7 11.9 22.0 19.5 18.2 2.6
GY
SD1 63.6 44.2 53.9 45.0 61.3 51.2 45.3 5.7
SD2 39.3 29.0 34.2 43.4 34.9 34.5 26.3 2.7
Cross 2 (Line 3 x Line 4)
DH
SD1 86.5 87.2 86.8 88.2 86.4 89.4 90.8 2.2
SD2 83.5 86.9 85.2 85.9 79.3 86.8 89.2 3.1
DM
SD1 141.0 143.7 142.3 145.4 143.1 140.8 145.4 2.4
SD2 126.9 134.8 130.8 130.9 132.8 131.0 133.5 2.9
GFP
SD1 54.6 56.5 55.5 57.2 56.7 51.4 54.6 3.7
SD2 43.5 47.8 45.6 45.1 53.6 44.2 44.4 1.4
GFR
SD1 0.69 0.89 0.79 0.82 0.77 0.75 0.77 0.1
SD2 0.83 0.79 0.81 0.88 0.66 0.69 0.87 0.07
PH
SD1 90.9 99.3 95.1 102.3 101.5 100.2 109.0 1.1
SD2 91.3 96.3 93.8 99.5 96.4 90.2 88.8 1.6
SP
SD1 15.1 22.4 18.7 19.8 17.8 15.7 19.9 3.0
SD2 13.6 20.3 16.9 16.6 16.8 15.0 17.4 1.9
GY
SD1 37.5 49.8 43.7 47.0 43.9 39 42.3 6.3
SD2 36.2 37.8 37.0 39.5 35.4 30.5 38.4 2.8
Cross 3 (Line 5 x Line 6)
DH
SD1 84.8 86.0 85.4 82.7 84.1 85.3 87.4 1.9
SD2 82.0 84.3 83.2 79.6 83.3 82.1 83.6 2.2
DM
SD1 144.1 145.0 144.5 142.9 143.1 142.6 144.4 2.6
SD2 129.0 130.5 129.8 130.9 129.8 129.7 129.6 1.7
GFP
SD1 59.3 59.0 59.1 60.2 59.1 57.3 57.0 2.2
SD2 47.0 46.2 46.6 51.3 46.6 47.6 46.0 2.0
GFR
SD1 0.88 0.79 0.83 0.78 0.68 0.67 0.63 0.12
SD2 0.80 0.77 0.79 0.78 0.71 0.72 0.60 0.11
PH
SD1 93.7 100.8 97.2 103.3 99.9 89.3 104.7 1.5
SD2 90.3 94.9 92.6 98.3 86.9 87.5 93.8 1.6
SP
SD1 27.3 22.3 24.8 16.7 19.4 23.6 20.3 1.7
SD2 25.8 20.3 23.0 18.6 18.7 14.2 16.7 1.1
GY
SD1 51.8 46.3 49.1 46.6 39.9 38.0 35.6 6.3
SD2 37.7 35.6 36.6 39.9 32.8 34.1 27.6 4.7
P1 = first parent, P2 = second parent, MP = mid parent F1 = first generation, F2 =
second generation, BC1 = backcross first parent, BC2 = backcross for second
parent, DH = days to heading, DM = days to maturity, GFP = grain filling period,
GFR = grain filling rate (g day-1 plant-1), PH = plant height (cm), SP = number of
spikes plant-1 and GY = grain yield plant-1.
149 Egypt. J. of Appl. Sci., 35 (11) 2020
Reduction in agronomic and earliness traits under late sowing date may
be a result of high temperature in end of growing season (Abd El-Rady 2018,
Abdallah et al. 2019, Farhat et al. 2019, Hagras 2019 and Koubisy 2019).
Previous studies have observed similar effects of high temperature on days to
heading and maturity and plant height (Mondal et al., 2013 and 2016 and
Hagras 2019). Genotype under late sowing date recorded a few numbers of
growing days, then yield components decrease and hence the economic yield
suffers negatively (Menshawy et al. 2015 and Hagras 2019).
The two parents differed significantly in each cross for all the studied
traits, except for GFP under late sowing date in cross 1, GY under late sowing
date in cross 2, and DM, GFP, and GFR under both sowing dates, DH under
optimum sowing date and GY under late sowing date in cross 3. Differences
were more pronounced between parents in cross 1, then cross 2 for most traits.
Line 1 had the highest values of parents for DH, DM, GFP, PH, SP and GY,
while Line 2 showed an opposite trend for the same traits under both sowing
dates. Moreover, Line 3, 4 and 6 had close values for DH, DM and GFP.
Similar results were obtained by Abdelkhalik (2019), Morsy (2020) and
Sharshar and Genedy (2020).
Means of F1 generation were in-between P1 and P2 means for DH and
DM under both sowing dates, GFP, PH and GY under optimum sowing date in
cross 1, SP under both sowing dates, GFR and GY under optimum sowing date
and DH, DM and GFP under late sowing date in cross 2, and DM under late
sowing date in cross 3. These results indicated presence of partial or absence of
dominance as well as additive gene effects and similar to those of Abd El-Rady
(2018) and Koubisy (2019).
Moreover, means of F1 population was higher than the respective
parents for GFR, PH and GY under late sowing date in cross 1, PH under both
sowing dates, DH and DM under optimum sowing date and GFR and GY under
late sowing date in cross 2, and GFP and PH under both sowing dates and GY
under late sowing date in cross 3. These results indicate the presence of
overdominance with positive heterotic effect.
Also, F1 means were lower than or close to the lower parent for SP
under both sowing dates and GFP under late sowing date in cross 1, GFP under
optimum sowing date in cross 2, and DH, GFR and SP under both sowing dates
and DM and GY under optimum sowing date in cross 3.
Means of F2 population were lower than respective F1 population for
PH under both sowing dates, GFP under optimum sowing date and DH, DM,
GFR and GY under late sowing date in cross 1, DH, PH, GFR and GY under
both sowing dates and DM, GFP and SP under optimum sowing date in cross 2,
and GFP, GFR, PH and GY under both sowing dates and DM under late sowing
date in cross 3. These results indicated to positive inbreeding depression for
these cases.
On the contrary, F2 population means were higher than F1 means for SP
under both sowing dates, DH, DM, GFR and GY under optimum sowing date
and GFP under late sowing date in cross 1, DM, GFP and SP under late sowing
Egypt. J. of Appl. Sci., 35 (11) 2020 150
date in cross 2, and SP and DH under both sowing dates and DM under
optimum sowing date in cross 3. These results indicated to negative inbreeding
depression in these cases.
In general, means of the BC1's were close to those of their respective
female parents (P1's) and means of the BC2's were close to their respective male
parents (P2's) for all studied traits in the three crosses, that referred to highly
homogeneity for BC with their parents. Similar results were obtained by
Abdallah et al (2019), Abdelkhalik (2019), Koubisy (2019) and Sharshar
and Genedy (2020).
Gene effects
The simple scaling test (A, B and C) was used to detect the presence of
non-allelic interaction (Table 4). Significance of any one of the epistatic scales
would indicate the presence of non-allelic interactions amongst the genes
controlled traits in view. The parameters A, B and C showed significance for
the different traits, indicating the adequacy of the six parameters model to
explain the type of gene action controlling the traits of the studied crosses.
Table 4. Scaling tests (A, B and C) for the studied traits under
optimum (SD1) and late (SD2) sowing dates.
Trait
A B C
SD1 SD2 SD1 SD2 SD1 SD2
Cross 1 (Line 1 x Line 2)
DH 3.9** -3.55** 3.33** -5.83** 7.12** -1.94
DM 3.76** -3.41** 3.98** -2.33** 5.93** -2.5*
GFP -0.14 0.14 0.65 3.49** -1.19 -0.56
GFR -0.12 -0.3** 0.02 -0.49** 0.88** -0.35**
PH -20.52** 9.05** -30.83** -4.24** -10.82** -10.7**
SP 0.39 1.47 9.5** 6.79** 18.82** 20.73**
GY -6.22 -13.79** 1.35 -19.77** 47.3** -15.69**
Cross 2 (Line 3 x Line 4)
DH 4.08** 4.33** 6.31** 5.53** -4.42** -25.05**
DM -4.77** 4.21** 1.85** 1.26* -2.85* 7.79**
GFP -8.82** -0.09 -4.43** -4.14** 1.63 32.84**
GFR 0.00 -0.34** -0.17** 0.06 -0.13 -0.73**
PH 7.15** -10.42** 16.35** -18.08** 11.07** -1.00
SP -3.51** -0.08 -2.4* -2.02 -5.64** 0.4
GY -6.55* -14.67** -12.18** -0.46 -5.89 -11.42**
Cross 3 (Line 5 x Line 6)
DH 3.1** 2.57** 6.25** 3.33** 0.09 7.55**
DM -1.85** -0.63 0.96 -2.17** -2.39 -2.01
GFP -4.95** -3.2** -5.29** -5.5** -2.48 -9.57**
GFR -0.32** -0.14** -0.3** -0.35** -0.51** -0.32**
PH -18.25** -13.5** 5.47** -5.5** -1.32 -34.17**
SP 3.26** -16.12** 1.57 -5.44** -5.41** -8.36**
GY -22.42** -9.34** -21.76** -20.19** -31.72** -21.94**
* and ** = significance at 0.05 and 0.01 levels of probability levels, respectively, DH = days to
heading, DM = days to maturity, GFP = grain filling period, GFR = grain filling rate (g day-1 plant-
1), PH = plant height (cm), SP = number of spikes plant-1 and GY = grain yield plant-1.
Estimates of gene effects calculated from the six-parameters
model for the studied traits are presented in Table (5). Mean effect (m)
refers to the role of the overall mean in addition to the locus effects and
interactions of the fixed loci. All studied crosses exhibited significant (m)
151 Egypt. J. of Appl. Sci., 35 (11) 2020
static for all studied traits, indicating that these traits are under genetic
control. Similar results were obtained by Abdallah et al (2019),
Abdelkhalik (2019), Koubisy (2019).
Table 5. Mean estimates of the six gene effects for studied traits
under optimum (SD1) and late (SD2) sowing dates.
Trait
Sowing
date
m d h i j l
Cross 1 (Line 1 x Line 2)
DH
SD1 91.94** 6.46** 0.27 0.11 0.28 -7.35**
SD2 87.17** 5.78** -4.88** -7.44** 1.14* 16.82**
DM
SD1 146.17** 5.17** 2.74** 1.81 -0.11 -9.56**
SD2 131.75** 3.95** -1.22 -3.24** -0.54 8.98**
GFP
SD1 54.24** -1.29** 2.47 1.70 -0.39 -2.21
SD2 44.58** -1.83** 3.66** 4.2** -1.68** -7.84**
GFR
SD1 1.13** 0.12** -1.16** -0.98** -0.07 1.07**
SD2 0.78** 0.21** -0.22* -0.44** 0.09** 1.23**
PH
SD1 96.4** 14.53** -35.58** -40.53** 5.16** 91.88**
SD2 79.95** 11.81** 26.26** 15.51** 6.65** -20.31**
SP
SD1 22.98** -0.59 -17.57** -8.93** -4.55** -0.96
SD2 21.95** 1.27* -22.31** -12.48** -2.66** 4.23
GY
SD1 61.28** 5.89** -61.08** -52.18** -3.79 57.05**
SD2 34.88** 8.14** -8.59* -17.86** 2.99* 51.42**
Cross 2 (Line 3 x Line 4)
DH
SD1 86.4** -1.47** 16.17** 14.81** -1.12* -25.21**
SD2 79.28** -2.32** 35.59** 34.91** -0.60 -44.77**
DM
SD1 143.15** -4.63** 2.98* -0.07 -3.31** 3.00
SD2 132.84** -2.43** -2.22 -2.31* 1.47** -3.16
GFP
SD1 56.75** -3.15** -13.23** -14.89** -2.2** 28.14**
SD2 53.56** -0.17 -37.65** -37.06** 2.03** 41.28**
GFR
SD1 0.77** -0.02 -0.01 -0.04 0.08* 0.21
SD2 0.66** -0.18** 0.52** 0.45** -0.2** -0.18
PH
SD1 101.48** -8.77** 19.68** 12.43** -4.6** -35.93**
SD2 96.38** 1.33* -21.75** -27.5** 3.83** 56.00**
SP
SD1 17.85** -4.19** 0.82 -0.27 -0.55 6.18
SD2 16.83** -2.38** -2.85 -2.50 0.97 4.60
GY
SD1 43.87** -3.35 -9.51 -12.84 2.81 31.56**
SD2 35.37** -7.94** -1.26 -3.72 -7.1** 18.86**
Cross 3 (Line 5 x Line 6)
DH
SD1 84.06** -2.13** 6.54** 9.25** -1.57** -18.6**
SD2 83.28** -1.55** -5.2** -1.65 -0.38 -4.25
DM
SD1 143.12** -1.84** -0.11 1.49 -1.41** -0.60
SD2 129.83** 0.04 0.38 -0.79 0.77 3.59
GFP
SD1 59.06** 0.29 -6.65** -7.76** 0.17 18.00**
SD2 46.55** 1.59** 5.58** 0.87 1.15* 7.83**
GFR
SD1 0.68** 0.04 -0.17 -0.11 -0.01 0.73**
SD2 0.71** 0.12** -0.18 -0.17 0.1** 0.66**
PH
SD1 99.9** -15.4** -5.43** -11.47** -11.86** 24.25**
SD2 86.88** -6.33** 20.83** 15.17** -4.00** 3.83
SP
SD1 19.37** 3.33** 2.10 10.23** 0.84 -15.06**
SD2 18.74** -2.55** -17.63** -13.2** -5.34** 34.76**
GY
SD1 39.9** 2.40 -14.92* -12.47* -0.33 56.65**
SD2 32.77** 6.48** -4.35 -7.59 5.43** 37.11**
* and ** = significance at 0.05 and 0.01 levels of probability levels, respectively, m = mean
effect, d = additive effect, h = dominance effect, i = additive x additive, j = additive x
dominance and l = dominance x dominance effects, DH = days to heading, DM = days to
maturity, GFP = grain filling period, GFR = grain filling rate (g day-1 plant-1), PH = plant
height (cm), SP = number of spikes plant-1 and GY = grain yield plant-1.
Egypt. J. of Appl. Sci., 35 (11) 2020 152
Additive gene effects (d) were either positive or negative and
significant in 34 out of 42 cases (81.0 %) in all conditions. These cases
include all traits, except for SP under optimum sowing date in cross 1,
GFR and GY under optimum sowing date and GFP under late sowing
date in cross 2, and GFP, GFR and GY under optimum sowing date and
DM under late sowing date in cross 3. Most of the positive effect was
found for the cross No. 1, referring to highly diversity for their parents
compared to the other crosses and that improving of these traits by
pedigree selection may be effective. These results are in accordance with
the previous findings of Abd El-Rady (2018), Elmassry and El-Nahas
(2018) and Koubisy (2019).
The estimates of dominance (h) effects were positive and
significant in 11 out of 42 cases (26.2 %) namely DM under optimum
sowing date and GFP and PH under late sowing date in cross 1, DH
under both sowing dates, DM and PH under optimum sowing date and
GFR under late sowing date in cross 2, and DH under optimum sowing
date and GFP and PH under late sowing date in cross 3. This indicates
the importance of positive dominance of gene effects in inheritance of
these traits and validity of heterosis breeding program for improving such
traits.
On the contrary, negative and significant dominance gene effects
occurred in 16 out of 42 cases (38.1 %). These cases included GFR, SP
and GY under both sowing dates, PH under optimum sowing date and
DH under late sowing date in cross 1, GFP under both sowing dates, PH
under late sowing date in cross 2, and GFP, PH and GY under optimum
sowing date and DH and SP under late sowing date in cross 3. In general,
these results indicated that both additive and dominance gene effects
were important in the inheritance of these traits. These results are in line
with those obtained by Abd El-Rady (2018) and Koubisy (2019).
Out of 42 cases, additive (d) was larger in magnitude than
dominance (h) effect in 24 cases (57.1 %). These involved all traits,
except for GFP under both sowing dates and PH under late sowing date
in cross 1, DH and DM under both sowing dates, GFR and PH under
optimum sowing date and GFP and GY under late sowing date in cross 2,
and PH under both sowing dates, DH and DM under optimum sowing
date and GFP under late sowing date in cross 3. On the contrary,
dominance was larger than additive variance in the remaining 18 cases
(42.9 %). These results were confound with the findings for relative
importance of additive and dominance in the inheritance of studied traits
153 Egypt. J. of Appl. Sci., 35 (11) 2020
in bread wheat and this may be due to differences in genetic background
of parental materials introduced in these studies (EL-Nahas 2016,
Elmassry and El-Nahas 2018, Abd El-Rady 2018, Abdallah et al.
2019 and Koubisy 2019).
Significant epistatic gene effects were exhibited in 81 out of 126
studied cases (64.3 %) for all three types of epistasis (i, j and l). This
indicates that epistatic gene effects were generally important in the
inheritance of studied traits. Similar results were also obtained by
Koubisy (2019), Sharshar and Esmail (2019) and Sharshar and
Genedy (2020).
Dominance x dominance (l) gene effects were the highest in
magnitude among the three digenetic epistatic effects in 27 out of 42
cases (64.3 %), followed by (i) effects in 12 cases (28.6 %) and then (j)
effects in three cases (7.1 %). Similar trend was given by Abd El-Rady
(2018), Abdallah et al. (2019) and Koubisy (2019).
Positive or negative and significant (i) gene effects were exhibited
in 26 cases (61.9 %) for GFR, PH, SP and GY under both sowing dates
and DH, DM and GFP under late sowing date in cross 1, DH, GFP and
PH under both sowing dates, and DM and GFR under late sowing date in
cross 2, and PH and SP under both sowing dates and DH, GFP and GY
under optimum sowing date in cross 3. This indicates an enhancing effect
of additive x additive type of epistasis for inheritance of these traits.
Additive x dominance (j) type of epistasis exhibited positive and
significant effects in 12 cases (28.6 %), namely PH and SP under both
sowing dates, DH, GFP, GFR and GY under late sowing date in cross 1,
GFR under optimum sowing date and DM, GFP and PH under late
sowing date in cross 2, and GFP, GFR and GY under late sowing date in
cross 3. As additive × dominance epistasis tends to segregate in next
generations, it would be better to delay selection to later generations with
increased homozygosity, where additive and additive × additive
variances are prevailing.
Negative and significant additive x dominance (j) epistatic gene
effects were shown in 14 cases (33.3 %), namely SP under both sowing
dates and GFP under late sowing date in cross 1, DH, DM, GFP and PH
under optimum sowing date and GFR and GY under late sowing date in
cross 2, and PH under both sowing dates, DH and DM under optimum
sowing date and SP under late sowing date in cross 3.
Positive and significant dominance x dominance (l) epistatic gene
effects were shown in 20 cases (47.6 %), namely GFR and GY under
Egypt. J. of Appl. Sci., 35 (11) 2020 154
both sowing dates, PH under optimum sowing date, DH, and DM under
late sowing date in cross 1, GFP and GY under both sowing dates, and
PH under late sowing date in cross 2, and GFP, GFR and GY under both
sowing dates, PH under optimum sowing date and SP under late sowing
date in cross 3.
Negative and significant dominance × dominance gene
interactions were obtained in 10 cases (23.8 %), namely SP under both
sowing dates and GFP under late sowing date in cross 1, DH and GFP
under optimum sowing date and GFR and GY under late sowing date in
cross 2, and PH under both sowing dates, DH and DM under optimum
sowing date and SP under late sowing date in cross 3. These results
indicated to reducing effect of dominance × dominance gene interactions
in the expression of these traits.
In general, maximum number of inter- and intra-allelic interaction
types of gene effects were exhibited by PH under both sowing dates and
DH, GFR and GY under late sowing date in cross 1, PH under late
sowing date in cross 2, and SP under optimum sowing date and GFP and
GY under late sowing date in cross 3. This suggests that the selection in
early segregating generations could be used for the improvement of these
traits in the respective crosses.
Type of epistasis was considered as complementary when
dominance and dominance × dominance gene effects have the same sign,
and duplicate epistasis when the sign was different. Opposite signs of
dominance and dominance x dominance type of gene effects were
recorded for all the studied traits, except for SP under optimum sowing
date in cross 1, DM under both sowing dates and SP under optimum
sowing date in cross 2, and DM under both sowing dates and DH, GFP
and PH under late sowing date in cross 3. These results reveal that
duplicate epistatic gene action is important in the inheritance of most
studied traits compared to complementary epistasis. Similar trends were
also reported by Abd El-Rady (2018), Koubisy (2019), Morsy (2020)
and Sharshar and Genedy (2020).
Components of variance and genetic parameters
Variance components and other genetic parameters are presented
in Table (6). Phenotypic variance in F2 populations differed significantly
from the corresponding environmental variance for all studied traits.
Consequently, the genotypic variance was the major part of the
phenotypic variance.
155 Egypt. J. of Appl. Sci., 35 (11) 2020
Table 6. Variance components and some genetic parameters for
studied traits under optimum (SD1) and late (SD2) sowing
dates.
Trait Sowing date Vph VG VE h2
b h2
n GS %
Cross 1 (Line 1 x Line 2)
DH
SD1 22.04** 17.51 4.53 79.46 78.67 8.28
SD2 26.06** 19.15 6.91 73.50 62.26 7.51
DM
SD1 8.38** 6.17 2.21 73.61 14.23 0.58
SD2 10.43** 7.22 3.21 69.23 61.86 3.12
GFP
SD1 15.23** 10.13 5.10 66.51 32.77 4.86
SD2 14.00** 10.07 3.94 71.89 28.81 4.98
GFR
SD1 0.24** 0.22 0.02 91.41 90.75 0.91
SD2 0.08** 0.06 0.02 76.25 57.71 0.33
PH
SD1 24.41** 18.28 6.13 74.87 23.30 2.46
SD2 67.59** 60.81 6.77 89.98 88.38 18.72
SP
SD1 61.43** 51.31 10.12 83.52 82.66 58.09
SD2 47.06** 37.21 9.85 79.07 78.32 50.42
GY
SD1 703.13** 645.72 57.41 91.84 91.45 81.52
SD2 162.43** 127.32 35.11 78.39 69.17 52.07
Cross 2 (Line 3 x Line 4)
DH
SD1 17.36** 12.99 4.37 74.84 18.23 1.81
SD2 23.17** 15.65 7.51 67.57 54.10 6.77
DM
SD1 16.69** 10.52 6.16 63.07 61.98 3.64
SD2 10.7** 7.15 3.55 66.81 24.45 1.24
GFP
SD1 18.91** 9.98 8.94 52.74 8.85 1.40
SD2 14.38** 8.25 6.12 57.41 54.11 7.89
GFR
SD1 0.12** 0.10 0.02 80.61 58.41 0.42
SD2 0.06** 0.06 0.001 94.57 0.49 0.00
PH
SD1 34.12** 27.97 6.15 81.97 81.81 9.70
SD2 42.45** 36.25 6.20 85.39 72.06 10.03
SP
SD1 43.78** 30.54 13.24 69.76 50.27 38.40
SD2 41.79** 27.43 14.37 65.62 53.45 42.31
GY
SD1 408.45** 344.19 64.26 84.27 60.87 57.77
SD2 164.54** 161.76 2.78 98.31 50.62 37.83
Cross 3 (Line 5 x Line 6)
DH
SD1 18.93** 13.90 5.03 73.43 53.55 5.71
SD2 35.05** 29.41 5.64 83.92 80.44 11.78
DM
SD1 20.88** 17.17 3.71 82.25 45.23 2.97
SD2 13.49** 9.59 3.90 71.08 43.29 2.52
GFP
SD1 15.27** 8.39 6.88 54.94 1.15 0.16
SD2 13.58** 6.82 6.75 50.26 2.30 0.38
GFR
SD1 0.09** 0.07 0.02 78.85 39.15 0.25
SD2 0.07** 0.05 0.02 69.32 24.24 0.14
PH
SD1 17.83** 9.77 8.06 54.82 24.11 2.10
SD2 49.61** 38.10 11.51 76.80 72.71 12.14
SP
SD1 38.02** 28.80 9.22 75.75 73.52 48.23
SD2 26.12** 15.82 10.30 60.56 55.52 31.20
GY
SD1 321.31** 257.27 64.04 80.07 61.57 56.98
SD2 152.82** 107.63 45.19 70.43 24.08 18.71
* and ** = significance at 0.05 and 0.01 levels of probability levels, respectively, Vph = phenotypic
variation, VG = genotypic variance, VE = environmental variance, h2
b= broad sense heritability,
h2
n= narrow sense heritability , GS % = expected genetic advance as percentage of F2 mean, DH =
days to heading, DM = days to maturity, GFP = grain filling period, GFR = grain filling rate (g day-1
plant-1), PH = plant height (cm), SP = number of spikes plant-1 and GY = grain yield plant-1.
Egypt. J. of Appl. Sci., 35 (11) 2020 156
Heritability is very important for wheat breeder to predict
behavior of succeeding the breeding program and effective selection.
Heritability in broad-sense was found to be moderate to high for all
studied traits. Narrow sense heritability ranged from moderate to high in
most cases, except for DM and PH under optimum sowing date and GFP
under late sowing date in cross1, DH and GFP under optimum sowing
date and DM and GFR under late sowing date in cross 2, and GFP under
both sowing date, PH under optimum sowing date and GFR and GY
under late sowing date in cross 3. These results indicated that additive
gene action was important in the inheritance of most traits and selection
may be more effective for improving such traits of all genotypes in early
segregating generations. In addition, the remaining traits are inherited by
non-additive gene action and selection for these traits will be effective in
late generations. These results were corroborated with those obtained by
Ataei et al (2017), Abd El-Rady (2018) and Koubisy (2019).
Heritability along with genetic advance are more helpful in
predicting the gain under selection than heritability alone (Johnson et al.,
1955). According to Johnson et al. (1955) genetic advance as percent of
mean classified as low (<10%), moderate (10-20%) and high (>20%).
Accordingly, the expected genetic advance as percent of F2 mean was
moderate to high for GFR, SP and GY under both sowing dates and PH
under late sowing date in cross 1, SP and GY under both sowing dates,
GFR under optimum sowing date and PH under late sowing date in cross
2, and GFR, SP and GY under both sowing dates and DH and PH under
late sowing date in cross 3. These results indicated the possibility of
practicing selection in early generations to select high yielding
genotypes. Meanwhile, the remaining traits, which showed the lowest
values of expected genetic advance, suggesting the role of environmental
factors and dominance gene action in inheritance of these traits.
Generally, most biometrical parameters resulted from cross 2 and
3 were higher in magnitude compared to cross 1. Consequently, it could
be concluded that these two crosses would be of interest in breeding
program for improving earliness and grain yield traits.
Correlation coefficients.
High genotypic correlation, which is the correlation of breeding
values helps in selection for genetically controlled traits. Phenotypic and
genotypic correlation coefficients between GY and other studied traits
are presented in Table (7). At both sowing dates, genotypic correlation
coefficient was higher than corresponding phenotypic correlation
157 Egypt. J. of Appl. Sci., 35 (11) 2020
coefficient for most studied traits in the three studied cross populations,
indicating to the inherent association among these traits and the
phenotypic expression of these traits were less influenced by the
environment. Similar results were reported by Dabi et al. (2016) and
Baye et al. (2020).
Table 7. Coefficient of phenotypic and genetic correlation between
grain yield and studied traits under optimum (SD1) and late
(SD2) sowing dates.
Correlation
Sowing
date
DH DM GFP GFR PH SP
Cross 1 (Line 1 x Line 2)
Phenotypic
correlation
SD1 -0.04 0.07 0.11 0.81* 0.21* 0.68*
SD2 -0.19* -0.02 0.25* 0.41* 0.20* 0.91*
Genotypic
correlation
SD1 -0.04 0.07 0.11 0.81* 0.21* 0.68*
SD2 -0.19* -0.02 0.25* 0.41* 0.20* 0.91*
Cross 2 (Line 3 x Line 4)
Phenotypic
correlation
SD1 -0.20* 0.001 0.19* 0.98* 0.02 0.32*
SD2 -0.26* -0.31* -0.05 0.71* 0.07 0.34*
Genotypic
correlation
SD1 -0.26* 0.11 0.41* 0.58* 0.03 0.45*
SD2 -0.32* -0.54* -0.06 0.96* 0.05 0.46*
Cross 3 (Line 5 x Line 6)
Phenotypic
correlation
SD1 -0.10 -0.03 0.07 0.99* 0.19* 0.42*
SD2 -0.48* -0.35* 0.13 0.87* 0.001 0.39*
Genotypic
correlation
SD1 -0.20* -0.10 0.12 0.50* 0.25* 0.45*
SD2 -0.40* -0.50* 0.23* 0.16* 0.05 0.56*
* and ** = significance at 0.05 and 0.01 levels of probability levels, respectively, DH =
days to heading, DM = days to maturity, GFP = grain filling period, GFR = grain filling
rate (g day-1 plant-1), PH = plant height (cm), SP = number of spikes plant-1 and GY =
grain yield plant-1.
Positive and significant phenotypic and genotypic correlations
were observed between GY and each of GFR, PH and SP under both
sowing dates and GFP under optimum sowing date in cross 1, GFR, and
SP under both sowing dates and GFP under optimum sowing date in
cross 2, and SP under both sowing dates, GFR and PH under optimum
sowing date and GFP under late sowing date in cross 3. Accordingly,
selection for such traits could be helpful for grain yield improvement in
segregating populations. These results were in line with those obtained
by Hassani et al. (2017).
Phenotypic and genotypic correlation were negative and
significant between GY and DH under late sowing date in cross 1, DH
under both sowing dates and DM under late sowing date in cross 2, and
DH under late sowing date and DM under late sowing date in cross 3.
Only phenotypic correlation was negative and significant between GY
and DH under optimum sowing date in cross 3. These results referred to
the change in the weather conditions (Mondal et al. 2013 and 2016 and
Egypt. J. of Appl. Sci., 35 (11) 2020 158
Pask et al. 2014). This negative correlation could be used as indicator to
select the promising genotypes that combine early maturing and high
yield potential especially in cross 2 and 3.
CONCLUSION
Generally, the biometrical parameters resulted from cross 2 and 3
were higher in magnitude compared to cross 1. Consequently, it could be
concluded that these crosses would be used in breeding program for
improving earliness and grain yield traits. Negative correlation between
grain yield and earliness traits indicated that earliness could be used as a
criterion in breeding for tolerance to high temperature stress in end of
growing season. This negative correlation also enables to select the
promising genotypes which had early maturing and high yield
potentiality especially in cross 2 and 3.
ACKNOWLEDGEMENTS
This research was supported by Wheat Research Department,
Field Crops research, ARC, Egypt.
REFERENCES
Abd El-Rady, A. G. (2018). Genetic analysis of some agronomic traits
in two bread wheat crosses under heat stress conditions. J. Plant
Production, Mansoura Univ., 9 (1): 21-28.
Abdallah, E. ; A. H. Salem ; M. M. A. Ali and K. Y. Kamal (2019).
Genetic analysis for earliness and grain yield of bread wheat
(Triticum aestivum L.) under heat stress. Zagazig J. Agric. Res.,
46 (6A): 1-16.
Abdelkhalik, S. A. M. (2019). Assessment of some genetic parameters
for yield and its components in four bread wheat crosses using
six parameter model. Egypt. J. Plant Breed., 23 (5): 719-36.
Acquaah, G. (2012). Principles of plant genetics and breeding. 2nd ed.
John Wiley & Sons.
Ataei, R. ; M. Gholamhoseini and M. Kamalizadeh (2017). Genetic
analysis for quantitative traits in bread wheat exposed to
irrigated and drought stress conditions. Int. J. of Experimental
Botany 86: 228-235
Baye A., B. M. B. Berihun and B. Derebe (2020). Genotypic and
phenotypic correlation and path coefficient analysis for yield
and yield-related traits in advanced bread wheat (Triticum
aestivum L.) lines. Cogent Food & Agriculture., 6 (1): 1-17.
Dabi, A. ; F. Mekbib and T. Desalegn (2016). Estimation of genetic
and phenotypic correlation coefficients and path analysis of
yield and yield contributing traits of bread wheat (Triticum
159 Egypt. J. of Appl. Sci., 35 (11) 2020
aestivum L.) genotypes. Int. J. Natural Resource Ecology
Management., 1 (4): 145-154.
Elmassry, E. L. and Marwa M. El-Nahas (2018). Genetic behavior of
some agronomic characters in three bread wheat crosses under
different environmental conditions. Alexandria J. of Agricultural
Sciences 63 (5): 313-25.
El-Nahas, Marwa M. (2016). Estimation of gene action for yield and its
components characters in bread wheat under drought condition.
Alex. J. Agric. Res. 61 (3):307-314.
Farhat, W. Z. E. ; M. M. M. Yassin and M. S. Hathout (2019).
Agronomic and grain quality characters of early maturing
selected bread wheat genotypes under optimum and late sowing
dates. Egypt. J. Plant Breed., 23 (7): 1545-1564.
Hagras, A. (2019). Early maturing wheat genotypes to cope with climate
changes. J. Plant Production, Mansoura Univ., 10 (12): 1005-
1014.
Hassani, I. ; S. Marker and G. M. Lal (2017). Inter-relationship studies
among grain yield and its component characters in wheat
(Triticum aestivum L.). J. of Pharmacognosy and
Phytochemistry., 6 (4): 186-191.
Jinks, J. L. and R. M. Jones (1958). Estimation of the components of
heterosis. Genetics., 43(2): 223-234.
Johnson, H. W. ; H. F. Robinson and R. E. Comstock (1955).
Estimates of genetic and environmental variability in soybean.
Agron. J., 47 (7): 314-318.
Koubisy, Y. S. I. (2019). Generation mean analysis of two bread wheat
crosses under normal and late sowing date conditions. Egypt. J.
Agric. Res., 97 (2): 589-607.
Mather, K. and J. L. Jinks (1982). Biometrical Genetics, 3rd. Chapman
and Hall Ltd., ISBN-10, 0412228904.
Mather, K. (1949). Biometrical Genetics. Dover Publication, Inc., New
York.
Menshawy, A. M. ; A. A. Al-Soqeer and S. M. Al-Otayk (2015).
Earliness, yield and heat sensitivity in bread wheat under natural
heat stress. Egypt. J. Agric. Res., 93 (2A).
Mondal, S. ; R. P. Singh ; E. R. Mason ; J. Huerta-Espino ; E.
Autrique and A. K. Joshi (2016). Grain yield, adaptation and
progress in breeding for early-maturing and heat-tolerant wheat
lines in South Asia. Field Crops Res., 192: 78-85.
Mondal, S. ; R. P. Singh ; J. Crossa ; J. Huerta-Espino ; I. Sharma ;
R. Chatrath ; G. P. Singh ; V. S. Sohu ; G. S. Mavi ; V. S. P.
Sukuru ; I. K. Kalappanavar ; V. K. Mishra ; M. Hussain ;
Egypt. J. of Appl. Sci., 35 (11) 2020 160
N. R. Gautam ; J. Uddin ; N. C. D. Barma ; A. Hakim and A.
K. Joshi (2013). Earliness in wheat: A key to adaptation under
terminal and continual high temperature stress in South Asia.
Field Crops Res., 151: 19-26.
Morsy, A. M. (2020). Genetic analysis controlling the yield and its
relevant traits in three cross populations of bread wheat under
normal and water stress conditions. Egypt. J. of Appl. Sci., 35
(3): 96-115.
Pask, A. ; A. K. Joshi ; Y. Manes ; I. Sharma ; R. Chatrath ; G. P.
Singh ; V. S. Sohu ; G. S. Mavi ; V. S. P. Sakuru ; I. K.
Kalappanavar ; V. K. Mishra ; B. Arun ; M. Y. Mujahid ; M.
Hussain ; N. R. Gautam ; N. C. D. Barma ; A. Hakim ; W.
Hoppitt ; R. Trethowan and M. P. Reynolds (2014). A wheat
phenotyping network to incorporate physiological traits for climate
change in South Asia. Field Crops Res., 168: 156-167.
Sharshar, A. and M. S. Genedy (2020). Generation mean analysis for three
bread wheat crosses under normal and water stress treatments. J.
Plant Production, Mansoura Univ., 11 (7): 617-626.
Sharshar, A. and S. Esmail (2019). Estimation of genetic parameters
for some agronomic traits, and resistance to stripe and stem rusts
using six parameters model in three bread wheat crosses. J. Plant
Production, Mansoura Univ., 10 (12): 1139-1147.
Singh R. K. and B. D. Chaudhary (2010). Biometrical Methods in
Quantitative Genetic Analysis. Kalyani Publisher, New Delhi,
lndia.
Steel, R. G. D. ; J. H. Torrie and D. A. Dickey (1997). Principle and
Procedures of Statistics: A Biochemical Approach. 3rd Ed.,
McGraw-Hill Book Company Inc., New York, USA.
تقدير المعالم الو ا رثية لمتبکير في النضج والمحصول في بعض هجن قمح الخبز
تحت ميعاد الز ا رعة الأمثل والمتأخر
وليد ذکي اليماني فرحات
* قسم بحوث القمح معهد بحوث المحاصيل الحقمية- - مرکز البحوث الز ا رعية مصر
يُولي البرنامج القومي لبحوث القمح في جمهورية مصر العربية اهتماما مت ا زيدا لتطوير
أصناف مبکرة النضج وذات إنتاجية عالية. لذلک، تم استخدام ست سلالات مبکرة إلى متوسطة
التبکير من قمح الخبز لإنتاج ثلاثة هجن. وتم استخدام نموذج الست عشائر خلال مواسم النمو
20 . وکان الهدف هو تحديد التفاعلات الأليمية وغير الأليمية التي / 18/2017 إلى 2019
تتحکم في صفات التبکير ومحصول الحبوب، وکذلک تحديد أفضل الت ا رکيب الو ا رثية التي ت ا رکمت
فيها جينات التبکير في النضج. وتم الحصول عمى اختلافات کبيرة بين ميعاد الز ا رعة الأمثل
161 Egypt. J. of Appl. Sci., 35 (11) 2020
والمتأخر وفيما بين العشائر الستة لکل الصفات. وقد تسببت الز ا رعة المتأخ رة في نهاية شهر
ديسمبر في انخفاض جميع الصفات المدروسة. وکانت تأثي ا رت الفعل الجيني المضيف والسيادي
ذات أهمية في و ا رثة الصفات المدروسة. وکان تأثير الفعل الجيني المضيف أکبر من السيادي
في معظم الحالات. وکذلک کانت قيم المکافئ الو ا رثي بالمعنى الواسع والضيق والتقدم الجيني
المتوقع کنسبة مئوية من متوسط الجيل الثاني متوسطة إلى مرتفعة لمعظم الصفات المدروسة.
وکان معامل الارتباط الظاهري والو ا رثي سالبا ومعنويا بين محصول الحبوب وصفات التبکير في
x معظم الظروف. وبصفة عامة، کانت معظم المعالم الو ا رثية الناتجة عن الهجين 2 )سلالة 3
x سلالة 6( أعمى في قيمتها مقارنة بالهجين 1 )سلالة 1 x سلالة 4( اولهجين 3 )سلالة 5
سلالة 2(، وبالتالي، فإن هذين الهجينين سيکونان مهمين في برنامج التربية لتحسين صفات
التبکير في النضج ومحصول الحبوب.
Egypt. J. of Appl. Sci., 35 (11) 2020 162
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