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166
Chaudhary et al.
Int. J. Biosci.
2019
RESEARCH PAPER OPEN ACCESS
Estimation of heterosis and combining ability for some
quantitative parameters in
Gossypium hirsutum
Muhammad Tanees Chaudhary1, Sajid Majeed1, Amir Shakeel1 , Jia Yinhua2, Du
Xiongming2, Muhammad Tehseen Azhar1*
1Department of Plant Breeding and Genetics, University of Agriculture, Faisalabad-38400,
Pakistan
2Institute of Cotton Research of Chinese Academy of Agricultural Sciences, State Key Laboratory of
Cotton Biology, Anyang 455000, Henan, China
Key words: Cotton; Fiber traits; Genetic effects; Hybrid vigour; SCA.
http://dx.doi.org/10.12692/ijb/15.2.166-173
Article published on August 09, 2019
Abstract
Cotton is an important oilseed andfiber crop in Pakistan as well as in world. Improvement can be madein yield
and fiber characteristics of cotton crop after understanding the various mechanisms of gene actions controlling
the yield contributingtraits.In the current study, four genotypes of cotton namely, NIAB-KIRN, FH-942, PB-896
and PB-76 were crossed in a random mating fashion. The parents and F1 hybrids were planted in field in three
replicationsfollowing randomize complete block design. At maturity, data were collected for yield and fiber
related traits. Analysis of variance of mean valuesexhibitedthe presence of significant variations. This data were
analyzed for their assessment of combining ability, where it is found that the genotype NIAB-KIRN has additive
gene action for number of seeds/boll, seed index and seed cotton yield per plant. Thus, nominated as a good
general combiner.Whereas PB-896 × PB-76 showed good specific combining ability for seed-cotton yield/ plant
and cotton-seed yield per plant, while the combination of PB-896 × FH-942 has exhibited significantly high
heterosis for fiber and seedcotton yield.Based on this information the parents and combinations have potential
of genetic material for yield of seed cotton as well as fiber related parameters.
* Corresponding Author: Tehseen Azhar tehseenazhar@gmail.com
International Journal of Biosciences | IJB |
ISSN: 2220-6655 (Print), 2222-5234 (Online)
http://www.innspub.net
Vol. 15, No. 2, p. 166-173, 2019
167
Chaudhary et al.
Int. J. Biosci.
2019
Introduction
Cotton belongs to genusGossypium andfamily
Malvaceae. More than 50 speciesof genus Gossypium
are reported till now. Amongst them, 45 are diploid
and 5 are allotetraploid, whereGossypium hirsutum
and G.barbadensewhich had both A and D sub-
genomes arecultivated allotetraploid species (Chen et
al., 2007).Naturally G. hirsutum is a perennial,
woody shrub plant with indeterminate type of growth
habit (Cothren and Oosterhuis, 2010). Within
species,genetic variation is necessary to start a
breeding program for the improvement of particular
trait of interest(Azhar et al., 2009). The information
about the extent and type of genetic variation relies
on different methodologies used for its assessment
(Bajracharya et al., 2006). There are severaltypes of
breeding methods that can be utilized to achieve the
desired genetic variability in segregating populations.
These methods include selection after hybridization
and mutation (Esmail et al., 2008). The breeding
importance of different crops depends upon the
combining ability and genetic variation in relation to
traits(Ilyas et al., 2007). For the assessment of
combining abilities,diallel analysis has been used
successfully in variousfield crops like cotton(Singh et
al., 2010), wheat(Mahpara et al., 2017), rice(Shabbir
et al., 2018) and maize(Murtadha et al., 2018).
Combining ability analysis given byGriffing is
beingthought-out to be valuablefor plant
breeders(Griffing, 1956). Mating of genotypes inall
possible combinations extent the genetic variation of
filial generations and is supportive for the estimation
of both combining abilitiesi.e. general and
specific(Gilbert, 1958).Breeding tools which are
utilized for hybrid production based upon high level
of heterosis and specific combining abilities(Khan et
al., 2009). From breeding point of view, commercial
heterosis is important because it is aimed to develop
hybrids which are superior over existing cultivars in
the market.Estimation ofboth combining abilities,i.e.,
general and specific for fibre strength, fibre fineness,
ginning turn out, fiber length and fiber uniformity
ratio in previous studies suggested the idea of
selection to improve these traits(Green and Culp,
1990;Zeng and Pettigrew, 2015; Kothari et al.,
2016;Zhang et al., 2016;Zhang et al., 2017). In
another study, GCA effects werefound to be
significantforfibrestrengh, fibre length and fiber
uniformity ratio (Coyle and Smith, 1997).(Ekinci et
al., 2010)estimated the heterotic effect of yield related
parameters in G. hirsutum, and found significant and
positive effects for heterosis/hybrid vigour and
heterobeltiosis for seed-cotton yield, lint percentage
and boll weight. As both combining abilities i.e.
general and specific as well as heterosis estimates are
useful tools to determine gene action to achieve
further breeding objectives. Therefore, this research
was aimed to assess GCA, SCA and heterosis in
available cotton cultivars and advance breeding lines
for varioustraits to identify potential breeding
material.
Materialsand methods
Development of F1 hybrids and assessment in field
conditions
The presentedresearchwas conducted during the year
2016-2018 at research area of the Department of
Plant Breeding and Genetics, University of
Agriculture, Faisalabad, Pakistan. The experimental
site is situated at31.42° latitude and 73.08°longitudes.
The planting material for this study was developed by
crossing four genotypes, namely PB-76, PB-896,
NIAB-KIRN and FH-942 in a complete diallel
fashion. The parents were grown in earthen pots in
glasshouse during October 2016. The optimal growing
conditions i.e. temperature (25-35°C)and
lightintensity (25,000-30,000 lux) was maintained
for germination and growth of the plants in
glasshouse. At the time of flowering, self, direct and
reciprocals crosses were made between the genotypes.
A large number of pollinations were made in order to
produce sufficient quantity ofF0seed.Cotton seed
fromselfed and crossed bolls were picked at maturity
and kept separately in cloth bags. Later on F0seed
along with their parents was sown in field in
triplicates according to randomized complete block
design by keeping 75 ×30 cm row and plant spacing.
All the recommended agronomic practices were
adopted including thinning and proper fertigation to
have good plant population per unit area.
168
Chaudhary et al.
Int. J. Biosci.
2019
Data recording
At maturity, data were collected for yield and fiber
traits.The traits involved wereplant height, number of
bolls/ plant, boll weight, seed/ per boll, cotton seed
yield/ plant, seed-cotton yield/ plant,lint index, seed
index, fibre length, fibre strength, fibre fineness and
fibre uniformity ratio. When epical growth of the
main stem had ceased, the plant height startingfrom
the zero node to epical bud of five guarded plants
from each parent as well as progeny was measured by
using measuring rod.All offully opened bolls from
these plants werecounted and picked in cloth bags.
Later on, numbers of seeds per boll were counted.
Average boll weight was calculated by dividing the
total seed cotton yield per plant with the number of
pocked bolls of respective plant. The mean boll weight
of plants in each replication was calculated, likewise
cottonseed yield was also recorded for each plant for
statistical analysis.Weight of lint in a sample and
weight of seed cotton was determined to calculate
ginning turn outby using formula,
While, lint index was recorded by using the following
formula,
A high-volume instrument (modelUSTER® HVI 900
SA) available in the Department of Fiber Technology,
University of Agriculture, Faisalabad was used to
measure fiber quality parameters from clean sample
of lint obtained from bolls of selected plants. This
computerized instrument recorded fiber length (mm),
fiber strength (g/tex), fiber fineness (µg/inch) and
fiber uniformity ratio according to international
standards.
Statistical analysis
The analysis of variance was employedas proposed by
Steel et al. (1997)on recorded datato find the
genotypic variation for selected traits by using
Statistix 8.1 software(McCullagh, 2018).Once it was
known that significant variation exist in the data set,
then comining ability (Griffing, 1956) and heterosis
estimates (Falconer and Mackay, 1996) were
calculated by using Dial98 (Ukai,2006).
Results
Mean squares of various traits for genetic variability
are described in Table 1 and 2. For all the studied
traits including yield and fiber, significant variations
were found in the germplasm genotypes. These
differences indicated the suitability of genotypes for
genetic studies.
Table 1. Analysis of variance in the form of mean squares of various traits for genetic variability.
SOV
DF
PH
NB/P
BW
NS/B
CSY/P
SCY/P
SI
LI
GOT
FL
FS
FF
FUR
Replications
2
27.82
1.06
0.04
16.45
58.6
41.08
0.44
1.36
64.35
1.1
0.41
0.09
18.43
Genotypes
15
308.53**
2.48*
4.76**
57.10**
116.32**
285.80**
0.51*
1.74**
71.54*
2.72**
6.15**
0.28*
53.80**
Error
30
31.18
1.2
1.25
22.77
53.14
14.35
0.14
0.53
21.23
1.31
1.3
0.03
11.35
Where, df stands for degree of freedom; * and **, denote difference significant at 5% and 1% probability levels,
respectively.
It wasfound that NIAB-KIRNexhibited highest
positive GCA effect for cottonseed yield (Table
3).Furthermore, PB-76 and FH-942 had maximum
positive and significant GCA for number of seeds/boll
and yield of cotton-seed respectively.PB-896 showed
significant and maximum GCA for uniformity ratio of
fibre.The cross among NIAB-KIRN × FH-942
exhibited positive SCA for plant height while its
parental genotypes exhibited negative GCA for this
trait.The hybridof PB-76×PB-896 revealed
maximumeffects ofSCA for number of bollsper
plant,fiber fineness and seed index. While hybrids
namely, FH-942 × PB-76 and PB-896 × PB-76
showed negative SCA fornumber of boll per plant
WhileFH-942×PB-76 revealed as good specific
combiner for seed index and boll weight. PB-896 ×
FH-942 was proved to be best combination for
uniformity ratio of fiber and seed/boll. For yield of
seed cotton and GOT%, hybrid PB-896 × NIAB
KIRNexhibited highest value for SCA.
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Chaudhary et al.
Int. J. Biosci.
2019
Table 2. Analysis of variance in the form of mean squares of various traits for combining ability analysis.
SOV
DF
PH
NB/P
BW
NS/B
CSY/P
SCY/P
SI
LI
GOT
FL
FS
FF
FUR
GCA
3
8.66**
1.42*
0.20*
0.45*
63.67**
111.06**
0.02**
0.22ns
11.02**
0.69*
0.80*
0.06*
12.45**
SCA
3
216.51**
0.97*
2.72**
3.65**
33.85**
83.01**
0.13*
1.05*
25.28**
1.69*
4.00**
0.14*
14.87*
Reciprocals
6
15.73*
0.77*
0.84*
0.96*
13.44*
55.87*
1.45*
0.56*
6.78*
2.77**
3.66*
0.58**
6.76*
Error
30
2.09
0.19
0.45
1.53
2.84
23.66
2.04
1.38
7.34
2.65
1.73
0.45
3.87
Note: List of abbreviations has been provided.
The cross of FH-942 × NIAB KIRN displayed positive
significant SCA for fiber length. The cross among
NIAB KIRN × PB-76 showed positive SCA for fiber
strength.These findingsindicated the existence of
non-additive gene behavior ingoverning
theseparameters.
In addition to combining ability, the heterotis
percentages for all of traits are briefed out in Table
4.The hybrid of NIAB-KIRN × FH-942 exhibited
maximum heterosis for plant height while indirect
cross of these accessions exhibited highly significant
heterosis for number of bolls per plant. For number of
seeds per boll and boll weight, PB-896 × FH-942
showed highest heterosis estimates.Heterosis %age
was ranged from 2.01% to 26.23% for plant
height.Nine out of twelve hybrids displayed
maximum positive and significant heterosis. PB-76 ×
FH-942 showed highest hybrid vigor for boll
weightwhile the hybrid PB-896 × PB-76 exhibited
highest heterosis estimate for seed present per boll
and yield of seed-cotton.
The heterosis was ranged from 2.43 to 56.74% for
seed-cotton yield per plant.Maximum heterosis %age
for fibre length (11.89%) and fibre strength (8.4%)
were exhibited by hybrids PB-896 × PB-76 and PB-76
× FH-942, respectively.
Table 3. General and specific combining ability effects data for all traits.
Crosses
PH
NB/P
BW
NS/B
CSY/P
SCY/P
SI
LI
GOT
FL
FS
FF
FUR
P1
0.80*
0.69 **
0.08
0.92
-0.44
-0.26
-0.03
0.20
-1.58
-0.04
0.40
0.11 *
1.42
P2
1.20*
-0.44
-0.07
1.72*
-0.61
1.47
-0.06
-0.27
1.72
-0.46
-0.49
-0.14 **
-0.62
P3
-0.65*
-0.07
-0.22
1.42
4.45 **
5.95 *
0.07
0.03
0.06
0.27
0.06
0.03
0.92
P4
-1.35*
0.18
0.21
0.62
3.39 *
4.23*
0.03
0.04
-0.20
0.23
0.03
-0.01
-1.72 *
P1 × P2
-14.55**
-1.68 **
-1.72 **
-0.40
10.61**
15.78 **
0.49 **
-1.19 **
2.75*
-2.32**
-3.82 **
-0.74 **
-0.40
P1 × P3
6.65
-0.24*
0.94 **
-3.09 **
-2.37
-2.58
0.35**
0.51 **
5.05**
0.24
0.12
-0.13 *
-3.09 **
P1 × P4
-12.33 *
-0.73 *
-1.36 **
6.43 **
2.59
4.0
0.34**
-0.12
-4.37**
0.48
-0.28
-0.03
6.43 **
P2 × P1
0.34
2.21*
2.75*
4.55**
2.34*
0.65
3.28*
3.11**
0.65
1.98*
0.045
3.43**
4.55**
P2 × P3
-10.21
0.29 *
-1.45 **
3.36 **
-4.22 *
-7.36 *
-0.07
1.17 **
2.8*
0.23 ns
1.68 **
0.25 **
3.36 **
P2 × P4
9.09
0.77*
0.82 *
-1.03
-3.85 *
-2.58
0.19*
-1.20 **
-3.87**
-0.79 *
1.08 **
0.05
-1.03
P3 × P1
2.45*
-0.43 *
-0.39
-3.45**
0.46
0.76*
-2.11*
-1.83
2.87**
-0.34
0.34
-2.43*
-3.45**
P3 × P2
-0.24
0.32 *
-2.67*
2.65*
-3.45*
-1.89
0.30
0.44
-3.67**
2.76*
3.45**
1.63
2.65*
P3 × P4
20.64 **
0.37 *
-1.70 **
2.39 *
3.31
7.79 *
-0.02
0.21
-5.14**
-0.86 *
0.16
-0.08
2.39 *
P4 × P1
-1.54*
0.42 *
0.03
-1.33
-2.31
6.87*
-3.21*
-2.56*
0.38
-3.38**
-2.98**
0.03
-1.33
P4 × P2
0.34
-2.64*
3.45*
0.27
5.34*
-5.34
3.45*
-0.55
-0.45
-1.75
-0.34
0.31
0.27
P4 × P3
-0.45
3.45**
0.29
2.12*
0.045
2.45
0.54
1.56
0.29
4.28**
-0.31
0.45
2.12*
Where, P1= PB-896, P2= PB-76, P3-=NIAB-KIRN, P4= FH-942.
Discussion
Genetic improvement in vegetative and reproductive
traits of cotton relies on the magnitude of genetic
variation that exists in germplasm. Therefore, plant
breeders are keen to know about the genetic
component of variation for the concerned trait.
Biometrical data showed significant variation for all
parameters observed in this research. The genetic
component of variation is thanadditionally divides
into two elementsi.e. GCA and SCA.These
components provide appropriate understanding
about genetic control of plant traits. LowerGCA to
170
Chaudhary et al.
Int. J. Biosci.
2019
SCA ratios revealed theprevalence of non-additive
gene action for studied traits. These findings were in
conformitywith (Aslam et al., 2015;Maqboool et al.,
2017;Khokhar et al., 2018).However, Raufet al.
(2005) reported that the involvement of both additive
and non-additive genetic effects for fiber traits.
Parental lines with maximumSCA estimates are
expected to produce productive hybrids by crossing
with suitable testers.Significant GCA effects for
parents indicated the possibilities of transferring
these traits to progenies(Samreen et al., 2008). The
use parents either with positive or negative GCA
depends upon the nature of traits and target of
breeding programs. For example, parents showing
positive GCA for yield of seedcotton can be used to
enhance yield through breeding while for plant height
and fiber fineness, parents with negative GCA are
suitable as lower or medium values for these traits are
desirable(Ashokkumar et al., 2010).
Table 4. Heterosis percentages data for all studied traits.
Crosses
PH
NB/P
BW
NS/B
CSY/P
SCY/P
SI
LI
GOT
FL
FS
FF
FUR
P1 × P2
-21.50
-7.93
-64.20 **
64.39 *
58.98*
56.74 *
14.56**
-36.40 **
10.56 ns
11.89**
-20.98 **
-19.83 **
2.09 ns
P1 × P3
2.52
3.96
-3.47 ns
2.75 ns
20.22 ns
25.56 ns
-6.09
18.74*
18.16 *
-0.88 ns
-1.58 ns
6.36 *
-4.12 ns
P1 × P4
-21.11
0.03
52.59**
53.45**
6.17 ns
15.33
18.77**
-12.20 ns
-17.14*
-0.71 ns
-4.26ns
-4.85 ns
24.72 **
P2 × P1
7.23
0.23
25.34ns
-14.47 ns
21.67 ns
23.21 ns
2.33 ns
12.39*
17.24*
1.02 ns
2.01 ns
2.02 ns
22.56**
P2 × P3
2.56
0.28
32.73 ns
4.28 ns
12.34*
16.52
3.70*
10.34 ns
17.22 ns
3.11*
4.21ns
11.02 *
12.89 *
P2 × P4
-17.39
0.01
-62.66 **
21.32 ns
-10.34 ns
8.49
-0.57 ns
35.02 *
9.83 ns
-2.01 ns
8.49 *
-2.95 ns
11.55 ns
P3 × P1
5.67
2.07
-7.18 ns
35.56**
3.22 ns
2.43 ns
8.77 *
38.80 **
-15.51 *
-6.19 ns
4.65 ns
-1.32 ns
3.99 ns
P3 × P2
26.23*
15.23
2.03 ns
-12.34 ns
-26.20 ns
-14.23*
1.88 ns
10.21 ns
13.22*
0.23 ns
3.12 ns
23.88**
-3.55 ns
P3 × P4
2.01
1.02
14.23 ns
23.37 ns
2.76 ns
-6.90
7.54*
34.32*
12.32*
3.22 ns
2.21 ns
2.93 ns
0.45 ns
P4 × P1
14.21
-2.20 ns
23.43*
14.21**
34.12 ns
2.54
2.76ns
2.87 ns
10.23 ns
4.22 ns
2.01 ns
3.23 ns
4.23 ns
P4 × P2
13.44
21.43*
12.11 ns
4.75 ns
33.59 ns
-11.54
0.03 ns
12.23*
13.22 *
3.02 ns
3.12 ns
2.04 ns
2.01 ns
P4 × P3
21.13*
2.20 ns
-64.27 **
3.75 ns
19.32*
43.83 ns
-0.20 ns
9.81 ns
-18.66 *
-4.28 ns
3.95 ns
-1.63 ns
13.74*
Where, P1 = PB-896, P2= PB-76, P3= NIAB-KIRN, P4= FH-942.
Present study displayed significant heterosis for fiber
and yield parameters. Results regarding heterotic
effects for seed cotton yield/plant suggested that five
F1 hybrids displayed positive and significant
heterosis.Comparison between the observed heterosis
of hybrids and the GCA effects of their parents
revealed the range of heterosis. Most of the
productive hybridsi.e. (NIAB-KIRN×PB-896)
and(PB-76 × PB-896)were the results of crosses
between parents exhibiting high and low GCA
estimates(Arain et al., 2015). Generally, high
heterosis(Bilwal et al., 2018)was observed in those
crosses where one of the two parents had quite lower
GCA estimate as compare to others. Some of hybrids
were observed with high heterosis values from the
crosses between two parents having high GCA
estimates(Patil, 2018). In many cases, the crosses
between parents possessing high GCAs for a given
traits results into inferior hybrids(Jatoi and Memon,
2016). Thus, based upon the results, the hybrid PB-
896 × PB-76 exhibited superior SCA for yield of
seedcotton and cottonseed yield per plant while the
hybrid PB-896 × FH-942 exhibited highly significant
heterosis for yield of seed cotton and fibre related
parameter. The mentioned results are in accordance
with (Kannan and Saravanan, 2016;Tigga et al.,
2017;Balakrishna et al., 2017).The genetic
components are highly influenced by environmental
conditions, so potential of these hybridscould be
assesses after cultivation in multi-location trials in the
cotton belt of Pakistan.
Conclusion
The investigations found in this study opened the
avenues for exploitation of parents and their hybrids
for heterosis breeding for various traits. The higher
values of GCA, SCA and heterosis indicate that there
is great chance to select the potential genotype for
certain traits which can be exploited in future for
advancement of yield and fiber related parameters.
171
Chaudhary et al.
Int. J. Biosci.
2019
List of abbreviations
GCA, general combining ability, SCA, specific
combining ability, PH, plant height; NB/P, number of
bolls/plant; BW, boll weight; NS/B, number of seed/
boll; CSY/P, cotton seed yield/ plant; SCY/P, seed
cotton yield/plant; SI, seed index; LI, lint index; GOT,
ginning out turn; FL, fiber length; FS, fiber strength;
FF, fiber fineness; FUR, fiber uniformity ratio.
Declaration of interest
Not applicable.
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