Egypt. J. Plant Breed. 16 (2): 1 – 27(2012)
INHERITANCE OF MAIZE PROLIFICACY UNDER
HIGH PLANT DENSITY
A. M.M. Al-Naggar1, R. Shabana1 and A.M. Rabie2
1- Department of Agronomy, Faculty of Agriculture, Cairo University, Giza, Egypt.
2- Maize Res. Dept., Toshka Co. Bani Sweif, Egypt.
ABSTRACT
The strong association of prolificacy in maize with tolerance to high plant
density reported in the literature by many investigators has stimulated us to study the
inheritance and expression of such trait under high and low plant densities. A diallel
cross among eight diverse inbred lines in number of ears plant-1 was performed in 2010
season and the resulting F1’s along with their parental lines were evaluated in 2011
season under two plant densities (20,000 and 40,000 plants fed -1) using a split plot design
in randomized complete blocks (RCB) arrangement with three replications at two
locations (Bani Sweif and Minufiya). The main objective was to obtain information on
the expression of genes controlling maize prolificacy under low and high plant density.
Analyses of variance indicated existence of significant differences among locations, plant
densities and genotypes for all studied traits. Performance of inbred lines and F 1 crosses
vary with location and plant density. Parental lines L14, L17, L18 and L53 were the best
in mean performance and general combining ability effects (GCA) for ears plant -1 (EPP),
grain yield plant-1 (GYPP) and grain yield fed-1 (GYPF) under high and low densities.
The best F1 crosses in mean performance and specific combining ability effects (SCA)
under high-density were L14×L17, L14×L18 and L18×L20 for EPP and L14×L17,
L18×L20 and L18×L55 for EPP and GYPP. Type of dominance controlling inheritance
of EPP trait changed from complete dominance to the prolific parent under low density
to complete dominance to the non-prolific parent under high density. Results indicated
that to obtain a hybrid of high EPP and GYPP under high-density, at least one of its
parents should be prolific, but to obtain a hybrid of high GYPF, both of its parents
should be prolific. The magnitude of genetic variance (additive and dominance) and
heritability in narrow-sense for the three traits EPP, GYPP and GYPF was lower under
high-density than that under low-density. Both additive and dominance variances were
highly significant for the three traits, but the magnitude of dominance was higher than
that of additive variance. Results confirm the simple inheritance of EPP trait (one gene)
as reported by some investigators under high and low density. Prolificacy may be rapidly
transferred from a prolific exotic inbred to the non-prolific Egyptian inbreds used in
commercial hybrids by a conversion backcrossing program . Expected genetic advance
(GA) from selection ranged from 9.49% for high EPP to 22.66% for GYPP under highdensity. Estimates of GA were higher under low than under high-density, indicating that
selection for high EPP is more efficient than under low-density. Correlation coefficients
for means vs. GCA effects of inbreds, means vs. heterobeltiosis, means vs. SCA effects
and SCA effects vs. heterobeltiosis of F1 crosses as well as parents means vs. offspring
means and breeding values were estimated and discussed.
Key words: Zea mays, Tolerance, High density, Prolificacy, Diallel, Additive,
Dominance, Number of genes, Breeding value.
INTRODUCTION
Prolific genotypes of maize tend to produce fewer barren plants at
high plant densities (Russell 1968, Duvick 1974, Miller et al 1995 and
Gezahegan et al 2006), and have greater yield stability than the nonprolific
types due to their greater capacity to change the number of ears plant-1 in
response to changes in plant density or environmental conditions (Collins et
al 1965 and Prior and Russell 1975). Prolificacy has the potential to increase
stress tolerance under intensive management (Leon et al 2005).
Very few reports were published on the inheritance of prolificacy in
maize under high plant population. Under low plant densities, studies have
reported partial to complete dominance for prolificacy (Robinson et al 1955
and Laible and Dirks 1968), but some investigators (Duvick 1974 and
Hallauer 1974) have concluded that prolificacy is recessive in nature.
Elsworth (1971) postulated one major gene and two minor genes to explain
the segregation for ear number observed in F2 and backcross populations of
two prolific inbreds, two nonprolific inbreds and one semiprolific inbred.
The demonstration that prolificacy may be rapidly transferred from a
prolific to a nonprolific inbred by backcrossing indicates that relatively few
genes affect ear number. Duvick (1974) reported that progenies of
backcrossing to A188 indicated that at least six chromosome arms possess a
gene or genes affecting prolificacy. Hallauer (1974) concluded that
prolificacy fits the description of a threshold trait in that its inheritance is
quantitative but its expression is qualitative. Harris et al (1976) proposed a
two-gene model in which one gene may be activated early in ear shoot
development to repress silk extrusion and a second gene is activated during
anthesis to repress ear development. Sorrelles et al (1979) reported that
general (GCA) and specific (SCA) combining ability effects were
significant for ear number. They added that the ratio of GCA to SCA
variances ranged from 3.7:1 to 7.4:1, higher ratios were usually associated
with the low population density and additive gene effects were highly
significant for prolificacy. Prolific and non-prolific maize genotypes are
known to respond differently to variation in plant density (Troyer and
Rosenbrook 1983). Success achieved by selection experiments for
enhancing the number of ears plant-1 (Kesornkeaw et al 2009) indicates the
existence of sufficient additive genetic variance in maize populations.
Improvement of maize germplasm for prolificacy led to the improvement of
grain yield under high plant densities (Subandi 1990, Al-Naggar 1991 and
Carena et al 1998)
In the present investigation, a diallel cross among diverse inbred
lines of maize in prolificacy (Al-Naggar et al 2011) was evaluated under
low and high plant densities in the F1 generation. The main objective of this
study was to obtain information on the expression of genes controlling
2
maize prolificacy under low and high plant density. Such information is
needed for developing tolerant maize hybrids to high-density.
MATERIALS AND METHODS
Breeding materials
Eight inbred lines of maize (Zea mays L.), four prolific and high
yielding (L14, L17, L18 and L53) and four non-prolific and low yielding
inbreds (L20, L23, L54 and L55) in the 5th selfed generation isolated from
different exotic and local sources (Al-Naggar et al 2011) were used for
making all cross combinations in a diallel manner (without reciprocals), and
seeds of 28 F1 crosses were obtained.
Evaluating the crosses
Field evaluation of the diallel crosses and their parents was carried
out in the summer season, at two locations, viz. Beba, Bani Sweif
Governorate (on the15th of June, 2011) and Ashmon, Minufiya Governorate
(on the18th of June, 2011). Each experiment included the eight parental
inbreds in the S6 generation and their 28 diallel crosses (i.e. 36 entries). A
split-plot design with randomized complete blocks (RCB) arrangement in
three replications was used. The main plots were assigned to two plant
densities, while the sub plots were devoted to genotypes (inbreds and
crosses, separately grown). The two plant densities included high density
(40,000 plants fed-1) and low density (20,000 plants fed-1). Sub-plots
consisted of two rows, 4.2 m long and 0.70 m wide, with a distance of 15
and 30 cm between hills, for high and low plant densities, respectively. The
sub-plot area was 5.88 m2. Stands were thinned to one plant hill-1 before the
first irrigation. Recommended agricultural practices for maize cultivation
(including N fertilization of 120 Kg N fed-1) were applied.
Data were recorded on (1) days to 50 % silking (DTS), (2) anthesis-silking
interval (ASI) (number of days between 50 % silking and 50 % anthesis), (3) plant
height (PH) in cm, (4) leaf angle (LANG) between leaf blade and stem for the
leaf just above ear (Zadoks et al 1974), (5) barren-stalks (BS%) (plants bearing
no fertile ears), an ear was considered fertile if it had one or more grains on the rachis),
(6) number of ears plant-1 (EPP), (7) number of kernels plant-1 (KPP), (8) 100kernel weight (100KW) (g) adjusted to 15.5% grain moisture, (9) grain yield plant-1
(GYPP) (g) adjusted to 15.5% grain moisture and (10) grain yield feddan-1 (GYPF)
in ardab by adjusting grain yield plot-1 to 15.5% grain moisture to grain
yield fed-1 (one fed = 4200 m2 and one ardab = 140 kg).
3
Biometrical and genetic analyses
The data collected from each location were subjected to the standard
analysis of variance of split-plot design, combined analysis of variance
across the two locations was performed, after carrying out the homogeneity
test and least significant differences (LSD) were calculated to test
significance of differences between means according to Snedecor and
Cochran (1989). Heterobeltiosis (%) was calculated as 100[ ̅ - ̅̅̅̅ ̅̅̅̅ ,
where: ̅ = mean of an F1 cross, and ̅̅̅̅=mean of its better parent.
Mean squares of studied traits of diallel crosses were divided into
general (GCA) and specific (SCA) combining ability variances and effects
under each location and across locations according to Griffing (1956)
method 2 model I (fixed effects). Although Griffing’s analysis was based on
Model I (fixed effects), since parents of the diallels in this study were
selected in purpose for the validity of diallel analysis, Hayman’s (1954 a
and b) approach (that assumes random model) was used to estimate genetic
components and ratios and to construct Hayman’s Vr-Wr graphs. The
conclusions obtained from Hayman’s analyses will help us to characterize
our genetic material for its proper use in the future breeding programs. The
genetic parameters and ratios were calculated according to methods
developed by Jinks and Hayman (1953), Jinks (1954) and Hayman (1954 a
and b) as described by Sharma (2003). Expected genetic advance: (GA)
from direct selection as a percentage of the mean ( ) was calculated
according to Singh and Chaudhary (2000) based on a 10% selection
intensity as follows: GA=100 k h2n ph / , where: k=1.76 = the standard
selection differential for 10% selection intensity, and ph = the square root of
the denominator of the narrow-sense heritability equation.
Genetic correlation coefficients (rg) were calculated between each
pair of studied traits under each environment (high- or low-density)
according to Singh and Chaudhary (2000) as follows: rg= δ2gxy / (δ2gx . δ2gy)½,
where: δ2gxy = the genotypic covariance for traits X and Y and δ2gx and δ2gy
= the genotypic variance of traits, X and Y, respectively. Rank correlation
coefficients (rs) were calculated according to Kendall (1975) between per se
performance of inbred lines and their GCA effects, between per se
performance of F1 crosses and their SCA effects and between SCA effects
and heterobeltiosis of F1 crosses for studied traits under each environment
(high- or low-density).
In order to determine the capacity of parental inbreds for transferring
prolificacy to their hybrid off-spring, inbred line parents of the diallel cross
were separated into best and worst sets based on performance of their cross
4
combinations, i.e., cross combinations among the best inbred lines for
prolificacy in one set and among the worst inbreds for the same trait in the
other set. Thus, an in-depth analysis of the breeding value of each inbred
line in both sets was performed as the standardized deviation of its progeny
mean from the mean of all progenies developed in the set. The true value of
an inbred line was ascertained via parent-progeny correlation (rop) analysis,
where an inbred line (p) is the independent variable and its F1 off-spring (o)
is the dependent variable for any trait. This analysis was done following the
example given by Sharma (2003).
RESULTS AND DISCUSSION
Analysis of variance
Analysis of variance of split-plot design (data not presented) showed
that mean squares due to densities were significant for all traits at each
location and across locations, except for DTS and PH at each location and
across locations and ASI at Minufiya and across locations and LANG at
Bani-Sweif, indicating that the plant densities have an obvious effect on
most studied traits. Mean squares due to maize genotypes were highly
significant for all studied traits at both locations and across locations,
indicating the existence of genetic differences among genotypes for studied
characters under high and low plant density. Mean squares due to genotype
× plant density interactions were highly significant for all studied traits in
both locations and across locations, suggesting that the genotypes behaved
differently under different plant density conditions, indicating the potential
success of selecting genotypes with improved performance under a specific
plant density, as proposed by Duvick, (1984), Russell (1984), Mahgoub and
El-Shennawy (2005), Kamara et al (2006) and Shakarami and Rafiee (2009).
Mean squares due to genotypes × locations interactions were highly
significant for all studied traits, except for PH and 100-KW, indicating that
the performance of genotypes vary with locations for most characters.
Moreover, mean squares due to the second order interaction (genotype ×
density × location) were highly significant for all studied traits, except PH,
suggesting that maize genotypes (inbred lines and crosses) vary with
locations and plant densities, confirming previous results (Mehasen and AlFageh, 2004 and Kamara et al 2006).
Analysis of variance under each plant density (low or high) for
combined data across locations (data not presented) showed that mean
squares due to parents and crosses under both low and high densities were
highly significant for all studied traits, indicating the significance of
differences among parents and among hybrids. Mean squares due to parents
vs. F1 crosses were highly significant for all studied traits under both
densities, except ASI under low-density and EPP under high-density,
5
indicating the presence of significant heterosis for most studied traits under
both low and high plant densities. Mean squares due to the interaction
between parents × locations and crosses × locations were significant and
highly significant for all studied traits, except PH, LANG and 100-KW of
genotypes × locations, crosses × locations and parents × locations under
low-density, PH of crosses × locations and parents × locations under highdensity, 100-KW for parents × locations under high-density and DTS and
ASI for parents × locations under high-density, indicating that parents and
crosses performed differently in different locations for most studied traits
under high- or low-plant density.
Mean performance
Under low-density, prolificacy (EPP) was exhibited by the lines L14,
L17, L18 and L53 with an average of 1.21 ears plant-1 and less than one ear
plant-1 (non-prolificacy) was shown by the lines L20, L29, L54 and L55
with an average of 0.85 ear under high-density (Table 1). The diallel F1
crosses showed slightly higher EPP than their parents under low density,
ranging from 0.96 ear for the cross (L17 × L29) to 1.50 ears for the cross
(L18 × L20). Under high-density, mean EPP of F1 crosses ranged from 0.70
(L14 × L29) to 1.10 (L18 × L20). It is worthy to note that (L18 × L20)
showed the highest number of EPP among the studied F1’s under both
densities.
High plant density stress caused a significant reduction (13.6%) in
EPP for parental inbred lines and 21.7% for crosses, confirming results of
previous investigators (Tetio-Kagho and Gardner 1988, Andrade et al 1993,
Chapman and Edmeades 1999 and Tokatlidis et al 2005).
Results in Table (1) showed that lines L14, L17, L18 and L53 had
higher grain yield plant-1 (GYPP) than those of lines L20, L29, L54 and L55
by105.0 g and 87.4 g under low and high plant density, respectively. Mean
grain yield plant-1 of F1 crosses ranged from 173.5 to 316.9 g under lowdensity and from 76.7 to 202.1 g under high-density for (L14 × L54) and
(L18 × L20), respectively (Table 1). High plant density stress caused a
significant decrease in GYPP ranging from -49.3% for L20 to -15.1% for
L55 and from -65.9% for the cross (L53 × L54) to -20.8% for the cross (L18
× L55). The inbreds L14, L17, L18 and L53 (1st group) were of high
yielding and L20, L29, L54 and L55 (2nd group) were of low yielding.
Moreover, the average grain yield fed-1 (GYPF) of the 1st group was 29.5
and 31.1 ard fed-1, while the 2nd one was 14.1 and 14.0 ard fed-1 under low
and high plant density, respectively (Table 1). The highest yielding F1 cross
under high plant density, was (L14 × L18) (38.6 ard fed-1) followed by (L17
× L18) (38.5 ard fed-1), (L14 × L17) (38.0 ard fed-1) and (L17 × L54) (37.7
ard fed-1). Under low plant density, the late cross (L14 × L17) also showed
6
Table 1. Means of ears plant-1 (EPP), grain yield plant-1 (GYPP) and
grain yield per feddan (GYPF) for parental lines, their F1
diallel crosses under low (LD) and high (HD) plant density for
combined data across two locations in 2011 season.
Genotype
L14
L17
L18
L53
L20
L29
L54
L55
Average
LSD 05 (P)
EPP
LD
HD
1.17
1.17
1.19
1.33
0.67
0.92
1.00
0.80
1.03
0.33
1.03
1.05
1.03
1.16
0.51
0.77
0.90
0.70
0.89
0.34
Change%
-16.4**
-10.2*
-13.4**
-12.8**
-23.9**
-16.3**
-10.0*
-12.5**
-13.6**
GYPP (g)
LD
HD Change%
Parents (P)
266.6 189.5 -28.9**
245.9 197.8 -19.6**
258.3 142.6 -44.8**
275.7 227.2 -17.6**
219.0 111.1 -49.3**
113.9 90.4 -20.6**
197.8 125.0 -36.8**
95.6 81.2
-15.1*
209.1 145.6 -30.4**
51.3 49.8
Crosses (C)
244.8 178.4 -27.1**
204.8 157.4 -23.1**
196.5 94.1 -52.1**
203.3 96.8 -52.4**
206.8 85.7 -58.6**
173.5 76.7 -55.8**
198.1 115.4 -41.7**
242.1 155.4 -35.8**
234.7 145.4 -38.0**
242.2 103.2 -57.4**
214.6 124.7 -41.9**
259.6 150.4 -42.1**
218.6 108.3 -50.5**
218.2 112.2 -48.6**
316.9 202.1 -36.2**
266.6 103.1 -61.3**
184.4 105.8 -42.6**
243.4 192.7 -20.8**
214.8 110.5 -48.6**
206.7 114.6 -44.6**
270.1 92.2 -65.9**
232.6 99.7 -57.1**
197.1 129.5 -34.3**
184.2 91.4 -50.4**
183.4 112.2 -38.8**
202.2 116.5 -42.4**
254.7 136.0 -46.6**
215.4 100.2 -53.5**
222.5 121.8 -45.3**
72.3 65.8
43.2 38.7
LD
31.6
29.1
29.5
28.0
21.5
6.2
18.8
9.8
21.8
5.0
GYPF (ard)
HD Change%
32.6
31.0
30.7
30.2
21.9
6.3
18.4
9.6
22.6
3.0
1.16 1.02 -12.1**
35.4 38.0
L14XL17
1.10 1.00 -9.10
36.3 38.6
L14XL18
1.11 0.98 -11.7*
29.5 31.9
L14XL53
1.20 0.96 -20.0**
29.3 31.7
L14XL20
0.99 0.70 -29.3**
30.4 27.7
L14XL29
1.19 0.90 -24.4**
24.8 25.0
L14XL54
1.20 0.80 -33.3**
23.3 22.4
L14XL55
1.20 1.00 -16.7**
36.5 38.5
L17XL18
1.10 0.97 -11.8*
36.2 36.5
L17XL53
1.24 0.95 -11.8*
34.6 33.3
L17XL20
0.96 0.76 -20.8**
32.7 34.7
L17XL29
1.19 0.84 -29.4**
40.7 37.7
L17XL54
1.40 0.90 -35.7**
26.5 25.3
L17XL55
1.30 0.90 -30.8**
32.7 33.4
L18XL53
1.50 1.10 -26.7**
26.4 25.3
L18XL20
1.40 0.90 -35.7**
29.5 30.7
L18XL29
1.00 0.80 -20.0**
20.1 19.6
L18XL54
1.20 0.90 -25.0**
31.2 28.1
L18XL55
1.10 0.93 -15.5**
21.5 21.9
L53XL20
1.08 0.85 -21.3**
29.8 29.4
L53XL29
1.04 0.84 -16.0**
29.1 28.8
L53XL54
1.10 0.90 -18.2**
33.1 32.7
L53XL55
1.00 0.84 -16.0**
31.2 28.1
L20XL29
1.11 0.88 -20.7**
25.0 24.5
L20XL54
1.20 1.00 -16.7**
29.8 29.4
L20XL55
1.06 0.80 -24.5**
24.1 23.9
L29XL54
1.10 0.90 -18.2**
27.1 26.5
L29XL55
1.00 0.90 -10.0*
34.0 31.6
L54XL55
Average
1.15 0.90 -21.7**
30.0 29.8
LSD 05 For (C) 0.22 0.15
11.4
6.8
For (P vs. C)
0.13 0.13
7.0 12.6
Change % = 100 × (HD - LD) / LD.
+ = increase and - = decrease
* and ** indicate significance at 0.05 and 0.01 levels of probability, respectively.
7
+3.2**
+6.5**
+4.1**
+7.9**
+1.9
+1.6
-2.1
-2.0
+3.7
+7.3*
+6.3*
+8.1**
+8.4**
-8.8**
+0.9
-3.5
+6.1*
+0.7
-3.6
+6.3*
-7.4*
-4.2
+2.2
-4.2
+4.2
-2.3
-10.1**
+1.7
-1.4
-1.0
-1.1
-10.1**
-1.7
-1.4
-0.5
-2.1
-7.2*
-0.2
the highest grain yield (40.7 ard fed-1) followed by the crosses (L17 × L18)
(36.5 ard fed-1), (L14 × L18) (36.3 ard fed-1) and (L17 × L53) (36.2 ard fed1
), which were among the best crosses for GYPF under high plant density.
On the contrary, the cross (L18 × L54) showed the lowest mean GYPF
under both low- and high-densities. High plant density on average caused a
little increase in GYPF of parental inbreds and a little decrease in yield of
their F1 hybrids. However, under high-density 6 out of 28 crosses showed a
significant increase over low-density, ranging from 6.1% for cross (L17 ×
L18) to 8.4% for cross (L14 × L20). Crosses showing higher GYPF under
high-density than their yield under low density, such as (L14 × L18), (L17 ×
L18) and (L14 × L17) may be recommended for commercial use under high
plant density and / or under abiotic stress conditions, such as drought and
low-nitrogen, as well as for breeding programs to improve traits related to
tolerance to such stresses. High plant density is particularly useful in
augmenting selection for drought and low N tolerance (Buren et al 1974,
Troyer 1996, Beck et al 1997, Reeder 1997 and Vasal et al 1997). Several
commercial maize breeders in North America improved drought resistance
by screening under high density (Dow et al 1984 and Beck et al 1997).
Superiority of prolific (P) over non-prolific (N) genotypes
To describe the difference between prolific (P) and non-prolific (N)
inbred lines, data of EPP, GYPP and GYPF were average for the two groups
of inbreds differing in their prolificacy under low and high plant density
(Table 2). Grain yield fed-1 of prolific (P) inbreds was more than two fold
higher than that of non-prolific (N) inbreds under both low and high
densities. Superiority of P over N inbreds in GYPF was due to superiority in
EPP (41.2 and 54.2%) and GYPP (79.8 and 85.8%) under low and high
density, respectively. It is worthy to note that superiority of P over N
inbreds in EPP, GYPP and GYPF was higher under high than under low
density, suggesting that prolific inbreds are more tolerant to high density
than non-prolific inbreds. This conclusion was previously confirmed by
several investigators (Russell 1968, Duvick 1974, Miller et al 1995 and
Gezahegan et al 2006).
Table 2. Mean performance of prolific (P) and non-prolific (N) sets of
inbreds and superiority of P over N under low and high
density.
Prolific (P)
Non-prolific (N)
Superiority P over
N
LowHighLowHighLowHighTrait
density density density density density
density
1.2
1.1
0.8
0.7
41.2
54.2
EPP
261.6
189.3
156.6
101.9
79.8
85.8
GYPP
29.6
31.1
14.1
14.0
109.9
122.1
GYPF
Superiority % = 100 × [(P – N) / N].
8
Partitioning averages for EPP, GYPP and GYPF of F1 hybrids into
their components, i.e. prolific × prolific (P×P), prolific × non-prolific (P×N)
and non-prolific × non-prolific (N×N) hybrids (Table 3) indicated that
GYPF of (P×P) hybrids was the highest under high density (36.2 ard fed-1)
as compared to (P×N) (28.4 ard fed-1) and (N×N) (27.3 ard fed-1). EPP and
GYPP of (P×P) were obviously higher than those of (N×N) hybrids under
both densities. Superiority of (P×P) over (P×N) and (N×N) for three traits
was more pronounced under high than under low density and reached to
32.6% over (N×N) hybrids under high density for GYPF (Table 4). Such
superiority in GYPF under high density of (P×P) hybrids was associated
with superiority in EPP and GYPP as compared to (P×N) (11.4 and 20.0%)
and (N×N) (10.1 and 22.9%) hybrids (Table 4).
Comparing averages of the three groups of hybrids it could be
concluded that the type of dominance controlling inheritance of EPP trait
changed from complete dominance of the higher parent (prolific) under low
density to complete dominance of the lower parent (non-prolific) under high
density. Robinson et al (1955) and Labile and Dirks (1968) reported partial
to complete dominance for prolificacy, but Duvick (1974) and Hallauer
(1974) concluded that prolificacy is recessive in nature.
Table 3. Average performance for EPP, GYPP and GYPF of prolific ×
prolific (P×P), prolific × non-prolific (P×N) and N×N hybrids
under low and high density.
EPP
GYPP
GYPF
LowHighLowHighLowHighCross
density
density
density
density density density
1.16
0.98
223.5
140.5
34.4
36.2
P×P
1.17
0.88
228.3
117.6
28.9
28.4
P×N
1.08
0.89
206.2
114.3
28.5
27.3
N×N
Table 4. Superiority of P×P over P×N and N×N hybrids under low and
high density.
P×N
N×N
Trait
Low-density High-density Low-density High-density
-0.85
11.4
7.4
10.1
EPP
-2.2
20.0
8.4
22.9
GYPP
19.0
27.5
20.8
32.6
GYPF
Superiority % = 100 × [(P – N) / N].
For GYPP, the type of dominance changed from overdominance
under low to dominance of the lower yielding-parent under high density.
Nearly complete dominance to the lower yielding-parent controlled
inheritance of GYPF under both densities. Results in Table (3) indicate that
9
to obtain a hybrid of high performance for EPP and GYPP under high
density, at least one of its parents should be prolific, but to obtain a hybrid
of high GYPF under high density, both of its two parents should be prolific.
Heterobeltiosis
Favorable heterobeltiosis (heterosis relative to better parent) in
studied diallel crosses was positive for EPP, GYPP and GYPF under both
densities. In general, the highest average significant favorable
heterobeltiosis was shown for GYPF (23.7%) under low and 16.9% under
high-density and EPP (2.9%) under low-density (Table 5). Some crosses
showed significant favorable heterobeltiosis for EPP (14 and 5 crosses),
GYPP (2 and 4 crosses) and GYPF (20 and 16 crosses) under low- and
high-plant density, respectively. The most favorable significant
heterobeltiosis under high-density was 42.9% for EPP (cross L20 × L55),
50.4% and 264.7% for GYPP and GYPF (cross L29 × L55), respectively.
It is worthy to note that estimates of heterosis in prolificacy and
grain yield under low density was decreased or even disappeared under high
density. Moreover, hybrid superiority is not necessarily associated with high
heterosis. Crosses showing the highest heterosis were between two nonprolific (or two low-yielding) inbred parents. These results are in agreement
with Duvick (1999), who suggested that a cross between two high yielding
inbreds might exhibit less heterosis but nevertheless produce a high yielding
hybrid and a hybrid is superior not only due to heterosis but also due to
other heritable factors that are not influenced by heterosis.
Combining ability variance
Mean squares due to GCA and SCA were highly significant,
suggesting that both additive and non-additive gene effects play an
important role in controlling the inheritance of EPP, GYPP and GYPF under
low and high plant densities (Table 6). A similar conclusion was reported by
Mason and Zuber (1976) and Khalil and Khattab (1998). However, the
magnitude of GCA mean squares was higher than that of SCA mean squares
(the ratio of GCA/SCA mean squares exceeded unity) for the three traits
(EPP, GYPP and GYPF) under low and-high-plant density, suggesting the
existence of more additive than non-additive variance. Similar results were
reported by Subandi and Compton (1974), Shewangizaw et al (1985), Khalil
and Khattab (1998), El-Shouny et al (2003) and Sultan et al (2010).
Results in Table (6) indicate that mean squares due to the SCA ×
location interaction were highly significant for the three studied traits under
low- and high-plant density. However, the GCA × location interaction was
highly significant for GYPP under both densities, indicating that the nonadditive genetic effects for this trait were more affected by locations under
both densities than additive effects. A similar conclusion was reported by
Betran et al (2003 b).
10
Table 5. Estimates of heterobeltiosis (%) for ears plant-1 (EPP), grain
yield plant-1 (GYPP) and grain yield feddan-1 (GYPF) of
diallel F1 crosses under low (LD) and high (HD) plant density
for combined data across two locations in 2011 season.
EPP
GYPP
GYPF
Cross
LD
HD
LD
HD
LD
HD
0.1
-2.8*
-8.2
-9.8
13.5**
14.5**
L14XL17
-2.9*
-23.2**
-16.9**
20.2**
23.9**
L14XL18 -7.7**
-28.7**
-58.6**
-6.4
-0.8
L14XL53 -18.1** -15.8**
3.9*
-9.2**
-23.7**
-48.9**
-5.8
-0.1
L14XL20
-22.4**
-54.8**
-3.4
-14.9**
L14XL29 -13.9** -33.4**
3.2*
-15.0**
-34.9**
-59.5** -16.9** -19.3**
L14XL54
-22.3**
-25.7**
-39.1** -26.3** -31.7**
L14XL55 2.6**
0.8
-4.8*
-6.3
-21.4**
22.5**
20.7**
L17XL18
-14.9**
-36.0**
21.1**
13.9**
L17XL53 -18.4** -17.3**
-10.0**
-1.5
-47.8**
21.9**
9.0*
L17XL20 7.6**
-12.7*
-37.0**
9.4*
11.5**
L17XL29 -16.5** -28.1**
3.8*
-19.4**
5.6
-24.0**
44.2**
23.1**
L17XL54
-11.1*
-45.2** -13.0** -20.3**
L17XL55 19.7** -14.3**
-22.4**
-20.9**
-50.6**
18.8**
11.1**
L18XL53 -2.3*
6.8**
22.7**
41.7**
37.5**
15.0**
L18XL20 26.1**
3.2
-27.7**
14.1**
7.1
L18XL29 17.6** -12.6**
-28.6**
-25.8** -30.5** -36.2**
L18XL54 -16.0** -22.3**
0.8
-12.6**
-5.8
35.1**
24.8**
2.7
L18XL55
-22.1**
-51.4**
12.3*
31.1**
L53XL20 -18.3** -18.7**
-25.0**
-49.6**
5.7
-6.6
L53XL29 -19.6** -21.6**
1.7*
-26.7**
-2.0
-59.4**
25.1**
9.3*
L53XL54
-15.6**
-56.1**
23.7**
4.9
L53XL55 -17.3** -22.4**
11.4**
-10.0*
16.6**
29.7**
-5.8
L20XL29 27.0**
10.3**
-15.9**
-26.9**
14.3**
12.3**
L20XL54 24.6**
42.9**
-16.3**
1.0
35.0**
30.2**
L20XL55 50.0**
0.3
2.2
-6.8
60.8**
61.4**
L29XL54 19.3**
16.9**
123.6**
50.4** 266.4** 264.7**
L29XL55 19.6**
0.0
0.0
8.9*
-19.8**
43.7**
41.6**
L54XL55
Average
2.9
-9.8
-7.5
-26.0
23.7
16.9
* and ** indicate significance at 0.05 and 0.01 levels of probability, respectively.
11
Table 6. Combining ability mean squares EPP, GYPP and GYPF of
diallel among 8 maize inbred lines under low (LD) and high
(HD) plant density for combined data across two locations in
2011 season.
Mean squares
GYPP
GYPF
SOV
LD
HD
LD
HD
LD
HD
4.32** 2.89** 165829.3** 30991.0** 31.1** 32.9**
GCA
0.28** 0.17** 10384.8**
2398.9*
15.1** 11.8**
SCA
0.02
0.02
4240.0**
4088.4**
48.6
26.8
GCA × Loc
0.03** 0.05**
3455.3**
783.2**
51.4** 43.5**
SCA × Loc
15.3
17.2
16.0
12.9
20.7
28.0
GCA / SCA
0.54
0.48
1.2
5.2
0.9
0.6
GCA × Loc / SCA × Loc
* and ** indicate significance at 0.05 and 0.01 levels of probability, respectively.
EPP
Mean squares due to GCA × locations were higher than those due to
SCA × locations for GYPP under both densities, suggesting that the GCA
(additive variance) is more affected by locations than SCA (non-additive)
variance for this trait, while SCA was more affected by locations than GCA
for EPP and GYPF under both densities, indicating that variance due to
SCA (non-additive effects) is more affected by locations than GCA
(additive effects) for these two traits.
GCA effects of inbreds
Parental lines L14, L17, L18 and L53 showed highly significant and
positive GCA effects for EPP, GYPP and GYPF traits, indicating that these
lines may be considered the best general combiners for traits conferring
adaptation to high density stress. Previous studies have proved that positive
GCA for EPP is a good indicator of stress tolerance (Banziger and Lafitte
1997 and Betran et al 2003 b). In general, the best per se inbreds (Table 1)
were the best general combiners (Table 7) for these three traits.
SCA effects of diallel crosses
Positive and significant SCA effects (favorable) for EPP, were
recorded by the crosses (L14 × L55), (L17 × L29), (L18 × L20), (L18 ×
L55), (L53 × L54) and (L20 × L55) under both densities, crosses (L14 ×
L54), (L17 × L53), (L17 × L55), (L18 × L29), (L53 × L29), (L53 × L55)
and (L20 × L54) under low-density and crosses (L14 × L17), (L14 × L18),
(L20 × L29), (L29 × L54) and (L54 X L55) under high-density. For GYPP,
the highest positive and significant SCA effects (favorable) were recorded
by the crosses (L14 × L17), (L14 × L55), (L17 × L29), (L17 × L54), (L18 ×
L20), (L18 × L55), (L53 × L29), (L53 × L54), (L53 × L55), (L20 × L29)
and (L29 × L55) under both densities, crosses (L18 × L14), (L14 × L29),
(L17 × L20), (L17 × L55) and (L18 × L29) under low plant density and
crosses (L29 × L54) and (L54 × L55) under high plant density (Table 8).
12
Table 7. Estimates of GCA effects of maize parental inbreds for
prolificacy and grain yield under low (LD) and high (HD)
plant density for combined data across two locations in 2011
season.
EPP
GYPP
GYPF
Parent
LD
HD
LD
HD
LD
HD
The best inbred lines
0.05**
0.02**
3.1**
2.4**
7.3**
7.9**
L14
0.08**
0.01**
15.1**
2.4**
10.1**
10.5**
L17
0.06**
0.05**
26.1**
6.3**
8.0**
7.9**
L18
0.02**
0.02**
11.1**
4.3**
7.5**
6.7**
L53
The worst inbred lines
-0.03** -0.02**
-6.9**
-4.0**
-4.9**
-4.5**
L20
-0.08** -0.04** -18.9**
-2.7**
-12.2**
-11.9**
L29
-0.07** -0.02**
-9.2**
-1.6**
-13.2**
-12.7**
L54
-0.04** -0.02** -20.1**
-7.1**
-2.5**
-3.8**
L55
SEgi-gj 0.001
0.002
0.52
0.24
0.06
0.05
* and ** indicate significance at 0.05 and 0.01 probability levels, respectively.
For GYPF, the best positive and significant SCA effects (favorable)
were recorded by the crosses (L14 × L17), (L14 × L18), (L14 × L53), (L14
× L20), (L17 × L29), (L18 × L53), (L18 × L29), (L53 × L20), (L53 × L55),
(L29 × L54) and (L29 × L55) under both densities, crosses (L18 × L20),
(L18 × L55) and (L53 × L29) under low plant density and crosses (L14 ×
L54), (L17 × L53), (L17 × L54) and (L20 × L54) under high plant density
(Table 8). The above crosses may be recommended for maize breeding
programs for the improvement of tolerance to high plant density, as well as
tolerance to low nitrogen and drought stress. It is worthy to note that for the
three studied traits, most of the best crosses in SCA effects for a given trait
included at least one of the best parental inbred lines in GCA effects for the
same trait.
Highly significant strong correlation coefficients were recorded
between per se performance of inbreds and their GCA effects for EPP,
GYPP and GYPF under high and low density (Table 9), indicating the close
relationship between the two parameters, such that inbreds ranking highest
based on per se performance for these traits also show high GCA effects
and vice versa. A similar conclusion was recorded by Betran et al (2003a).
Significant rank correlation coefficients were also observed between ranks
based on per se performance ( ̅c) and heterobeltiosis of F1 crosses (Table 9).
However, such correlations were of medium or low magnitude. In general,
those correlation coefficients were higher in magnitude under high-density
than under low-density for the three traits.
13
Table 8. Estimates of SCA effects (ŝ ij) of diallel among contrasting
maize inbreds differing in prolificacy and grain yield for
studied traits under low (LD) and high (HD) plant density for
combined data across two locations in 2011 season.
EPP
Cross
LD
GYPP
HD
LD
GYPF
HD
LD
HD
-0.07**
0.12**
22.1**
18.7**
4.1**
2.7**
-0.07**
0.02**
29.0**
-1.8**
1.1**
0.4**
-0.02**
-0.01**
-22.2**
-24.5**
7.5**
6.1**
-0.08**
-0.10**
-13.8**
-8.3**
5.0**
3.0**
-0.03**
-0.04**
18.1**
-5.6**
-1.2**
-4.4**
0.10**
-0.11**
-24.9**
-16.0**
-7.8**
7.7**
0.14**
0.02**
10.5**
4.4**
-8.0**
-8.6**
-0.10**
-0.08**
-19.4**
-16.7**
5.9**
2.2**
0.07**
-0.04**
-22.2**
-14.3**
-3.6**
4.0**
-0.07**
-0.02**
17.2**
-5.1**
-2.6**
-4.0**
0.26**
0.01**
7.8**
7.6**
2.0**
1.3**
-0.02**
-0.01**
29.2**
30.4**
-5.2**
2.3**
0.22**
-0.02**
12.8**
-21.7**
-7.8**
-8.3**
-0.08**
-0.04**
-33.1**
-23.6**
7.8**
8.5**
0.31**
0.10**
25.8**
59.2**
1.7**
-2.8**
0.35**
-0.01**
21.2**
-19.5**
1.1**
0.5**
-0.12**
-0.05**
-43.2**
-24.6**
-13.3**
-13.1**
0.05**
0.03**
26.6**
30.8**
1.8**
-2.9**
-0.05**
-0.07**
-36.1**
-9.0**
4.8**
5.1**
0.11**
-0.06**
3.8*
13.0**
4.0**
-4.9**
0.07**
0.01**
42.5**
11.2**
-1.3**
-1.8**
0.04**
-0.04**
23.7**
2.2**
2.4**
0.8**
-0.21**
0.10**
4.1*
6.6**
-4.3**
-4.2**
0.09**
-0.05**
-26.8**
-14.1**
-6.3**
5.4**
0.06**
0.01**
-23.5**
-9.1**
-1.8**
-1.7**
-0.02**
0.13**
-19.6**
18.3**
1.5**
2.1**
-0.02**
-0.02**
26.1**
5.7**
6.9**
7.7**
-0.06**
0.11**
-33.9**
5.2**
-3.4**
-2.4**
2.19
1.02
0.005
0.007
0.24
0.20
0.51
0.24
0.001
0.002
0.06
0.05
* and ** indicate significance at 0.05 and 0.01 probability levels, respectively.
L14XL17
L14XL18
L14XL53
L14XL20
L14XL29
L14XL54
L14XL55
L17XL18
L17XL53
L17XL20
L17XL29
L17XL54
L17XL55
L18XL53
L18XL20
L18XL29
L18XL54
L18XL55
L53XL20
L53XL29
L53XL54
L53XL55
L20XL29
L20XL54
L20XL55
L29XL54
L29XL55
L54XL55
SE Sij-Sik
SE Sij-Skl
Rank correlation coefficients between per se performance ( ̅c) and
SCA effects and between SCA effects and heterobeltiosis were highly
significant and higher-in-magnitude than those between ̅ and
heterobeltiosis. Estimates of correlation coefficients higher than or equal to
14
0.70 were observed between SCA and heterobeltiosis for GYPF under high
and low plant densities, and between ̅ and SCA for GYPP under highdensity only. The high in-magnitude, significant and positive estimates of
rank correlation coefficients for these cases indicate that per se performance
of F1 crosses could be used to some extent as an indicator of their SCA
effects, and the later (SCA effects) as an indicator to heterobeltiosis. This
means that some crosses showing high per se performance, combined with
high heterobeltiosis and high SCA effects for most studied traits could be
obtained (such as L18 × L20 and L29 × L55 for EPP, GYPP and GYPF).
These crosses could be recommended for plant breeding programs as good
germplasm for improving traits related to high-density tolerance.
Table 9. Rank correlation coefficients among mean performance of
inbreds ( ̅p) and their GCA effects and between pairs of
mean performance of F1’s (̅c), SCA effects and
heterobeltiosis (Hetero.) parameters under low (LD) and
high (HD) plant density for combined data across locations.
Correlation
̅ p vs. GCA
̅ c vs. Hetero.
̅ c vs. SCA
SCA vs. Hetero.
EPP
LD
0.73**
HD
0.76**
GYPP
Inbred lines
0.55**
GYPF
0.45**
0.77**
0.93**
F1 crosses
0.08
0.24*
LD
-0.25*
HD
-0.11
0.21*
0.25**
LD
0.51**
0.32**
0.49**
HD
0.64**
0.74**
0.54**
LD
0.35**
0.27**
0.70**
HD
0.25**
0.27**
0.72**
* and ** indicate significance at 0.05 and 0.01 probability levels, respectively.
Parent-offspring correlation
Genetic correlation coefficients (rop) between per se performance of
parent inbred lines and per se performances of their F1 cross progenies
under low and high plant density computed from combined data across
locations are presented in Table (10). Coefficients under high plant density
were significant and highly significant for GYPP of the best and worst
inbreds and GYPF of the worst inbreds. However, rop under low plant
density was significant and highly significant for GYPP of the best and
worst parental inbreds, EPP of the best inbreds and GYPF of the worst
inbreds.
15
Table 10. Parent-progeny correlation coefficients (rop) between per se
performance of best and / or worst parents (p) and per se
performance of their corresponding offspring (o) under low
and high plant density for combined data across locations.
Low-density
High-density
Trait
Best inbreds Worst inbreds Best inbreds Worst inbreds
-0.43**
0.14
-0.07
0.11
EPP
GYPP
0.37**
0.89**
0.35*
0.37**
GYPF
0.27
0.96**
0.26
0.95**
*and ** indicate that rop estimate exceeds once and twice its standard error, respectively.
Unfortunately, EPP, as the most important adaptive trait to high
density tolerance was not transmitted from the parental inbreds to their
hybrids either as best or worst and under high or low densities. By contrast,
GYPP of the hybrids between the best inbred lines conformed with the per
se performance of parents at both densities. Similar conclusion was noticed
for GYPP under both densities. On the other hand, GYPF was inferior under
both densities for hybrids between inbred lines chosen as the worst for
GYPF. On the contrary, genetic correlation coefficients (rop) were not
significant for EPP and GYPF for best inbreds and EPP for worst inbreds
under high-density. However, rop estimates were not significant for GYPF
for best inbred lines and EPP for worst inbreds under low-density. These
results, suggest the absence of relationship between parents and their
progenies, indicating that performance of progenies for these cases does not
tally with per se performance of parents and therefore, the breeding values
of such parents are poor (Sharma 2003). This follows that selection of
parents based on their mean performance, for hybridization program, would
be disappointing in generating hybrid progenies.
Breeding value for each of the best and worst inbred parent under
high and low-density is presented in Table (11).
The best parents for EPP (L17 and L18) and for GYPP and GYPF
(L17 and L53) showed high breeding values under high-density, however,
their rop values were insignificant. Such parents (L17 and L53) for GYPP
under low-density showed high breeding values (Table 11) and their rop
were significant (Table 10). Moreover, the inbreds (L14) and (L53) for EPP
and (L17) for GYPP under low-density showed high breeding values. On
the contrary, the worst inbred (L20) for EPP, GYPP and GYPF, L54 for
EPP and L29 for GYPF under both high and low plant density and L55 for
GYPP under high-density only showed high breeding values. High and
significant breeding values were shown under high plant density stress by
L17 for EPP, GYPP and GYPF, L53 for GYPP and GYPF, L18 for EPP
16
(Table 11). These inbred lines showed high coincidence with the GCA
effects under high-density (Table 7), suggesting that these inbred lines have
sufficient number of additive genes controlling the respective adaptive traits
to high plant density and the importance of using them in future breeding
programs for developing maize hybrids and synthetics of good tolerance to
high-density.
Table 11. Breeding values for best and worst parental inbreds under
low (LD) and high (HD) plant density for combined data
across locations.
EPP
GYPP
GYPF
Parent
LD
HD
LD
HD
LD
HD
-0.47
0.00
L14
-1.31
0.63
Best inbred lines
-0.70
0.11
L17
0.00
1.05
1.46
1.09
1.12
0.95
L18
0.19
-1.05
-0.15
0.14
0.49
0.44
L53
1.12
-0.63
-0.60
-1.34
-1.13
-1.38
-0.93
-0.93
L20
1.32
1.22
Worst inbred lines
-1.24
-0.92
L29
-0.10
0.00
0.82
0.68
1.13
1.17
L54
-1.11
-1.22
-0.39
-0.79
-0.75
-0.73
L55
-0.10
0.00
0.81
1.03
0.55
0.49
Gene action, heritability and expected selection gain
The additive genetic component of variation (D) was highly
significant for EPP, GYPP and GYPF under both high and low plant
densities (Table 9), indicating that selection may be used for improving
these traits under different plant densities (Mariani and Desiderio, 1975,
Shehata et al 1982 and Ismaeili et al 2005). The dominance component of
variation (H1) was also highly significant for the three traits under both high
and low plant densities, indicating that dominance was also important in the
inheritance of these traits and heterosis breeding could also be considered an
efficient method for improving these traits. In general, the estimates of
additive variance were relatively lower under high plant density than under
low-density.
17
Table 12. Components of variance and heritability diallel among maize
diverse inbred lines under low (LD) and high (HD) plant
density for combined data across locations in 2011 season.
Variance
component
(EPP)
(GYPP)
LD
HD
LD
HD
0.06**
0.03**
3619.56** 1217.95**
D
0.14**
0.04**
6922.57** 2961.63**
H1
0.21** 0.02** 8228.91** 470.72**
h2
1.58
1.11
1.38
1.56
(H1/D)1/2
7.62
22.53
0.18
0.17
H2/4H1
2.76
3.88
2.87
2.85
KD/KR
0.1
0.5
1.7
0.23
h2/H2
47.89
29.07
44.92
43.57
h2n%
-0.95
0.74
-0.89
0.77
r
13.32
9.49
16.83
22.66
GA%
** indicate significance at 0.01 probability level.
(GYPF)
LD
90.27**
143.12**
HD
97.47**
105.60**
226.23** 174.96**
1.26
0.04
2.37
9.40
48.08
-0.88
20.34
1.04
0.02
2.31
22.10
43.16
-0.61
20.02
The dominance variance was more important than additive variance
for the three traits under high-density, indicating that heterosis breeding
would be more efficient than selection for improving most studied traits
under high-density. The overall dominance effects of heterozygous loci (h 2)
controlling most studied traits under both densities were highly significant,
that could be due to the presence of a considerable amount of dominance
effects in the parental genotypes. Average degree of dominance (H1/D) ½
was greater than unity for EPP, GYPP and GYPF under high plant density,
indicating overdominance for these cases. The (H2/4H1) ratio indicated
asymmetrical distribution of positive and negative dominant genes in the
parents for traits under high and low densities. The proportion of dominant
to recessive alleles in the parents (KD/KR) was greater than unity for the
three traits under high and low plant densities, indicating an excess of
dominant alleles and minority of recessive alleles, i.e. (p > q). The
correlation coefficient (r) values between the order of dominance (Vr,Wr)
and parental measurements were significant and positive for the three traits
under high and low plant densities, indicating that the expression of high
scores in most of the parents is associated with dominant genes. Number of
genes (or gene blocks) controlling the inheritance under high density was
one for EPP and reached 22 for GYPF. This result confirms previous reports
about the simple inheritance of EPP trait (Ellsworth 1971 and Harris et al
1976). Prolificacy may be rapidly transferred from a prolific exotic inbred to
the non-prolific Egyptian inbreds used in commercial hybrids by a simple
conversion backcrossing program. The suitability of backcrossing for
18
improving maize prolificacy was previously reported by Duvick (1974) and
others.
Narrow-sense heritability (h2n) estimates were lower in magnitude
under high plant density (stress conditions) than those under low plant
density (non-stress conditions) for the three (Table 12). These results agree
with Rosielle and Hamblin (1981) and Guei and Wassom, (1992). The
highest h2n estimate under high plant density was shown by GYPP (43.57%)
followed by GYPF (43.16%), while the lowest h2n estimate was exhibited by
EPP (29.07%). Expected genetic advance (GA %) from selection, was
higher under low plant density for EPP, but the opposite for GYPP. This
indicates that selection for high EPP is more effective under low density.
Under high density, the highest GA was shown by GYPP (22.66%), while
the lowest GA (9.49%) was shown by EPP (Table 12).
Graphical approach of diallel analysis
The graphical analysis for EPP (Figure 1 and 4), GYPP (Figure 2
and 5) and GYPF (Figure 3 and 6) under low and high plant density,
respectively, show that the regression line intercepted the (Wr) axis below
the origin across locations, indicating overdominance and confirming
Hayman’s numerical analysis (Table 12).
The array points on the Vr-Wr graphs for the three traits under high
density gave evidence that the parents L14, L17, L18 and L53 for EPP,
GYPP and GYPF contained most of the dominance genes, while the parents
L55 for EPP and L29 for GYPP and GYPF contained most of the recessive
alleles. The lines L20, L54 and L55 for EPP, GYPP and GYPF and L29 for
EPP contained equal frequencies of dominant and recessive genes for these
traits (Figs. 1 through 6).
Fig. 1. Vr-Wr graph of ears plant-1 (EPP) for combined data across locations
under low plant density.
19
Fig. 2. Vr-Wr graph of grain yield plant-1 (GYPP) for combined data across
locations under low plant density.
Fig. 3. Vr-Wr graph of grain yield feddan-1 (GYPF) for combined data across
locations under low plant density.
Fig. 4. Vr-Wr graph of ears plant-1 (EPP) for combined data across locations under
high plant density.
20
Fig. 5. Vr-Wr graph of grain yield plant-1 (GYPP) for combined data across
locations under high plant density.
Fig. 6. Vr-Wr graph of grain yield feddan-1 (GYPF) for combined data across
locations under high plant density.
Trait interrelationships across diallel crosses
Number of ears plant-1 (EPP) showed highly significant and positive
association with KPP (rg= 0.80** and 0.88**) under high and low plant
density, respectively, and with GYPP (rg= 0.56**) and GYPF (rg= 0.48**)
under low-density (Table 13). A strong association between number of ears
plant-1 and grain yield was also reported by several investigators (Ordas and
Stucker 1977, Bolanos and Edmeades 1996 and Khazaei et al 2010). On the
contrary, EPP showed highly significant and negative association with BS
(rg= -0.85** and -0.42**) under high and low plant density, respectively and
with ASI (rg= -0.23**) under high-density. Grain yield plant-1 (GYPP)
showed highly significant and positive association with KPP (rg= 0.30**
and 0.52**), GYPF (rg= 0.92** and 0.96**) and PH (rg= 0.31** and 0.28*)
under high and low plant density, respectively, with 100KW (rg= 0.35**)
under high-density and with EPP (rg= 0.56**) and DTS (rg= 0.25*) under
low-density. Moreover, GYPP showed significant and negative correlation
with BS (rg= -0.28*) under low-density (Table 13). Grain yield fed-1
21
(GYPF) trait was highly significant and positively associated with KPP (rg=
0.25* and 0.43**) and PH (rg=0.36** and 0.22*) under high and low
density, respectively, 100KW (rg= 0.39**) under high-density and DTS (rg=
0.21*) under low-density. These results agree with those reported by
Bolanos and Edmeades (1996), Guei and Wassom (1992) and Mehasen and
Al-Fageh (2004). On the contrary, GYPF trait showed strongly negative
association with BS (rg= -0.30**) under low-density.
Table 13. Genetic correlation coefficients (rg) among studied traits
under low (LD) and high (HD) plant densities (data are
combined across two locations).
Trait
DTS (days)
ASI (days)
PH (cm)
LANG (o)
BS (%)
EPP
KPP
100KW (g)
GYPP (g)
GYPF (ard)
EPP
LD
HD
0.18
-0.08
0.09
-0.23*
0.18
0.15
-0.03
-0.02
-0.42**
-0.85**
--0.88**
0.80**
0.07
0.04
0.56**
0.13
0.48**
0.16
GYPP
LD
HD
0.25*
0.09
-0.18
-0.08
0.28*
0.31**
-0.02
0.09
-0.28*
-0.07
0.56**
0.13
0.52**
0.30**
0.15
0.35**
--0.96**
0.92**
GYPF
LD
HD
0.21*
0.10
-0.18
-0.07
0.22*
0.36**
-0.08
0.17
-0.30**
-0.14
--0.43**
0.25*
0.14
0.39**
-----
*and ** indicate that rg estimate exceeds once and twice its standard error, respectively.
In conclusion, high GYPP and high KPP under both densities, high
EPP and low BS under low-density and high 100KW under high-density
may be considered as good secondary traits in the studied diallel crosses for
increasing the efficiency of selection for high GYPF under the
corresponding densities, since they showed highly significant correlations
with GYPF and large estimates of narrow-sense heritability (h2n) for EPP
and GYPP.
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26
‫‪٫‬‬
‫‪٫‬‬
‫‪L14, L17, L18, L53‬‬
‫‪(L14×L17‬‬
‫)‪(L14×L18‬‬
‫)‪(L14×L17‬‬
‫)‪(L18×L20‬‬
‫)‪(L18×L55‬‬
‫‪٫‬‬
‫‪٫‬‬
‫المجله المصريه لتربية النبات ‪)2162( 22 - 6 : )2(61‬‬
‫‪27‬‬
‫‪(L18×L20‬‬