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Abstract

The present research was carried-out to analysis the genetic diversity in a set of 26 Bt-cotton genotypes for seed cotton yield and its associated traits. Results showed that genotypes differed significantly P ≤0.01 for all the traits, registering the significant genetic variability among the genotypes for further evaluation. With regards to mean performance, varieties BH-180 and KZ-389 displayed better performance in terms of plant height, bolls plant-1, seed cotton yield plant-1, monopodial branches plant-1 and sympodial branches length, suggesting that these genotypes can further be exploited for various breeding programs to improve upland cotton genotypes. In cluster analysis, all genotypes divided into nine small clusters, cluster one consisted of five genotypes which were characterized as high yielding genotypes suggesting that genotypes of this cluster could be utilized for future breeding programs in order to get better yielding varieties. In total, first three principal components accounted 75.90% variability, which is considered very high and could be utilized for further breeding programs in cotton. The obtained results may provide a helpful guide for selecting specific genotypes with distinct genetic backgrounds in cotton breeding programs.
SINDH UNIVERSITY RESEARCH JOURNAL (SCIENCE SERIES)
Genetic Diversity Analysis through Phenotypic Assessment in Bt-Cotton Germplasm
M. A. MUGHERI, A. W. BALOCH, M. BALOCH++, T. A. YASIR*, N. GANDAHI, G. H. JATOI**, A. M. BALOCH***
M. ALI****, I. A. BALOCH
Department of Plant Breeding and Genetics, Sindh Agriculture University, Tandojam, Pakistan
Received 4th October 2016 and Revised 1st April 2017
1. INTRODUCTION
The cotton crop is widely cultivated due to the fact
that cultivars upland cotton (Gossypium hirsutum L.)
meet the 90% of world’s cotton demand (Wendel et al.,
1992). The cotton crop is also very important in
Pakistan because it sustains the economy by means of
foreign exchange and employment. The production of
cotton has been maintained since several years
throughout the world, and at present, it is being grown
in nearly more than 100 countries. The top four cotton
producing nations are China, USA, India and Pakistan,
which account nearly 2/3 of world’s cotton acreage
(Dahab et al., 2013). Crop genetic diversity is considered
as the critical element in the production of crops, and it
is also important to identify the genetic diversity in gene
pool for the genetic conservation and breeding
programs. Hence, it is essential to know the
relationships among the plant varieties and genetic
diversity in order to recognize complexity of gene pool
and also to identify the gaps in the genotype collections
(Baloch et al., 2014). In order to get the superior
genotypes, it has become very necessary to properly
exploit the germplasm in hybridization programs and
also to adding the new germplasms; these practices are
enough in order to create the sufficient variations
(Li, et al., 2008). The variability in the germplasm
causes resistance against both abiotic as well as biotic
stresses. For getting the desirable genetic variability,
various plant breeding procedures have been applied
such as hybridization, exotic germplam and the
polyploidy (Esmail et al., 2008). Therefore, in the
current study, genetic diversity was estimated for
various agronomical traits which can further be utilized
in different breeding programs.
2. MATERIALS AND METHODS
The current experiment was conducted at the
Botanical Garden, Sindh Agriculture University,
Tandojam in order to assess genetic variability of some
agronomical traits in Bt cotton (Gossypium hirsutum L.)
germplasm. In a total, 26 Bt-cotton genotypes (Table-2)
were grown in Randomized Complete Block Design
with three replications. The distance of 30 and 75 cm
was kept between plant to plant and row to row,
respectively. All recommended practices were applied
at appropriate time. The traits studied were plant height
(cm), monopodial branches plant-1, sympodial branch
plant-1, sympodial branch length (cm), bolls palnt-1, boll
weight (g), seed index (100-seed weight, g) and seed
cotton yield plant-1(g). The analysis of variance, mean
comparisons and principal component analysis were
derived through Statistix v. 10 software, while cluster
analysis was carried out through NTSys-pc ver. 1.2
software. software by putting matrix (0 and 1). For
obtaining matrix, the recorded phenotypic data was
converted into 0 and 1 matrix as suggested by
Shakhatreh et al. (2010) and upland cotton genotypes
++Corresponding author’s email: munaizabaloch@yahoo.com
*College of Agriculture, Bahauddin Zakaria University, Bahadur Sub-Campus Layyah
**Department of Plant Pathology, Sindh Agriculture University, Tandojam, Pakistan
***Department of Horticulture, Sindh Agriculture University, Tandojam, Pakistan
****Department of Biotechnology, Sindh Agriculture University, Tandojam, Pakistan
Abstract: The present research was carried-out to analysis the genetic diversity in a set of 26 Bt-cotton genotypes for seed cotton yield
and its associated traits. Results showed that genotypes differed significantly P ≤0.01 for all the traits, registering the significant
genetic variability among the genotypes for further evaluation. With regards to mean performance, varieties BH-180 and KZ-389
displayed better performance in terms of plant height, bolls plant-1, seed cotton yield plant-1, monopodial branches plant-1 and
sympodial branches length, suggesting that these genotypes can further be exploited for various breeding programs to improve upland
cotton genotypes. In cluster analysis, all genotypes divided into nine small clusters, cluster one consisted of five genotypes which were
characterized as high yielding genotypes suggesting that genotypes of this cluster could be utilized for future breeding programs in
order to get better yielding varieties. In total, first three principal components accounted 75.90% variability, which is considered very
high and could be utilized for further breeding programs in cotton. The obtained results may provide a helpful guide for selecting
specific genotypes with distinct genetic backgrounds in cotton breeding programs.
Keywords: Genetic diversity, seed cotton yield, Gossypium hirsutum, Bt-cotton.
http://doi.org/10.26692/sujo/2017.12.0050
Sindh Univ. Res. Jour. (Sci. Ser.) Vol.49 (004) 739-742 (2017)
grouped into three groups based on their mean and
standard deviations. The three groups were:
1. Mean -1 standard deviation.
2. Mean -1 to +1 standard deviation.
3. Mean +1 standard deviation
3. RESULTS AND DISCUSSION
Analysis of variance and mean performance:
The analysis of variance for all the characters is
given in (Table-1). The obtained results revealed that
genotypes differed significantly at P ≤0.01 probability
level for plant height, monopodial branches plant-1,
sympodial branches plant-1, sympodial branches length,
bolls plant-1, boll weight, seed index and seed cotton
yield plant-1, suggesting that studied materials possess
useful genetic resources for variety of traits thus can
extensively be used for upcoming breeding programs.
Almost similar results have also been reported by
Baloch et al. (2014). The data regarding mean
performance of genotypes is given in (Table-2). The
data revealed that genotype BH-180 produced the tallest
plants of 146.30 cm while BZU-75 recorded the shortest
plants measuring of 108.67 cm as compared to the rest
of the genotypes. In case of monopodial branches
plant-1, the genotype KZ-389 produced maximum (3.33)
number of monopodial branches plant-1;however, no
monopodial branches plant-1 was found in BZU-75,
NIAB-1, CIM-602, VH-282 and CEMB-33 genotypes.
For sympodial branches plant-1, FH-118 produced the
highest number of sympodial branches plant-1 (27.66),
whereas Tarzen-402 produced the lowest number of
sympodial branches plant-1 (17.33). With regards to
sympodial branches length, the variety KZ-389
measured the longest branch length (34.077 cm) against
the other genotypes, while the shortest (11.10 cm)
branch length was measured from AGC-777. With
respect to bolls plant-1, the variety BH-180 set
maximum number of bolls plant-1 (46.16) while
minimum (28.16) number of bolls plant-1 were obtained
from AGC-777.AGC-777 weighed bigger bolls
of 4.15g, while the smaller bolls were observed in
variety BH-180 (3.17 g). The variety Tarzen-402 gave
higher seed index (7.46 g), however, the variety FH-118
gave the lower seed index(6.20 g). The variety BH-180
produced maximum seed cotton yieldplant-1 (148.08 g),
whereas the variety FH-118 gave the lowest seed cotton
yieldplant-1 (122.23 g). In general, varieties BH-180 and
KZ-389 displayed better performance in terms of plant
height, bolls plant-1, seed cotton yield plant-1,
monopodial branches plant-1 and sympodial branches
length, indicating that these cotton genotypes offer great
potential for further evaluation.
Cluster analysis:
Cluster analysis has been used as most widely
technique in order to classify the different genotypes
into homogeneous groups. It works on a matrix of
similarity (or dissimilarity) indexes for all possible pairs
of genotypes (Ghaderi et al., 1980). Cluster analysis
was performed to study the patterns of groupings of
genotypes. The dendrogram (Fig-1) was generated from
the UPGMA (Un-weighted Pair Group Method with
Arithmetic Mean) clustering method of genotypes based
on Euclidean distances. The cluster analysis classified
the 26 Bt cotton genotypes into 9 small clusters,
reflecting the presence of wide genetic diversity among
the tested genotypes. Based on obtained results, it is
suggested that the genotypes clustered together into
cluster one, possessing desirable gene combinations for
seed cotton yield plant-1, offering that these Bt cotton
genotypes could be used in future breeding programs in
order to improve seed cotton yield. It has been
suggested that genotypes grouped together into cluster
eight should not be used in cotton breeding programs
since the genotypes of that cluster contain undesirable
gene recombination for seed cotton yield and its related
traits. It is also recommended that hybridization
program should be avoided between cluster one with
cluster eight because later cluster do not possess reliable
gene combinations for yield and morphological traits.
Similar to our results,Xian et al. (2012) also reported
that genetic diversity analysis divided 38 cotton
genotypes into two groups with similar genetic
background.
Principal component analysis:
The conservation and exploitation of genetic
resources could be achieved by partitioning the total
variance into its components. It also offers a chance for
utilization of proper germplasm in crop development for
specific plant characters (Pecetti et al., 1990). PCA is an
important tool to get parental materials for successful
breeding strategies (Nazir et al., 2013). In this study, out
of total eight, first three principal components were
extracted having Eigen value more than one. However,
these principal components (PCs) contributed 75.90%
of the total variability amongst the cotton genotypes
assessed for various yield and its associated traits while
remaining five principal components contributed only
24.10% towards the total diversity for this set of cotton
genotypes. First three principal components explained
75.90% variability, which is considerably high and can
be utilized for further breeding programs in cotton. The
positive and negative loading reveals the occurrence of
positive and negative association trends between the
components and the variables. Therefore, the given
characters (Table 1-3) which load high positively and
negatively contributed more to the genetic variability
and they were the ones that most distinguished the
clusters. As usual, it is customary to choose one variable
from known groups. Hence, for the first group boll
weight value is best choice, which had the largest
M. A. MUGHERI et al., 740
loading from component one, seed index for the second,
plant height for the third group, sympodial branches
plant-1 for the fourth group, monopodial branches plant-1
for the fifth group, sympodial branches length for the
sixth group, bolls plant-1 for the group seventh and seed
cotton yield plant-1 for the eighth group. Recently, Elci
et al. (2014) also derived PCA on morphological data in
Turkish cotton varieties where PCA indicated the
relationships of genotypes in a more significant manner
showing that PCA should be used along with the cluster
to achieve a better perceptive of relationships among
genotypes.
Fig-1 Tree diagram of 26 upland cotton genotypes for 8 characters using hierarchical cluster analysis (Ward’s Method).
Table-1 Mean squares from analysis of variance for various traits in Bt cotton genotypes.
Note: ** = Significant at 0.01 level of probability.
Table-2 Mean performance of Bt-cotton genotypes for various traits
Source of
variation
Degree of
Freedom
Characters
Plant height
Monopodial branches plant -1
Sympodial branches plant -1
Sympodial branches length
Replications
2
6.640
3.57692
0.9744
6.9882
Genotypes
25
264.797**
2.16821**
15.3215**
69.9882**
Error
50
30.808
0.28359
2.9877
3.5551
Source of
variation
Degree of
Freedom
Characters
Bolls plant-1
Boll weight
Seed index
Seed cotton yield plant-1
Replications
2
58.5054
0.13702
0.00628
204.334
Genotypes
25
49.7927**
0.16212**
0.26759**
150.098**
Error
50
4.7787
0.0016
0.0455
13.134
Genotypes
Plant
height
(cm)
Monopo-dial
branches plant
-1
Sympodial
branches plant -1
Sympodial
branches
length (cm)
Bolls
plant -1
Boll
weight
(g)
Seed
index
(g)
Seed cotton
yield plant -
1 (g)
BH-180
146.30
1.33
22.00
11.26
46.16
3.17
6.76
148.08
BS-52
141.80
2.00
25.66
19.42
35.33
3.67
6.63
130.60
NS-161
131.37
0.33
19.66
14.02
33.83
3.73
6.33
127.92
Soyaben
131.52
1.33
23.66
18.66
35.05
3.72
6.30
131.89
KZ-389
129.80
3.33
22.66
34.07
41.00
3.35
6.46
139.02
GH-142
129.33
0.33
24.33
12.90
35.50
3.58
6.46
128.51
Leader-1
120.33
0.33
23.66
7.03
36.50
3.57
6.60
131.59
AGC-777
123.67
0.66
23.3
11.10
28.16
4.15
6.30
118.25
Trend-1
121.92
1.33
23.00
9.88
36.50
3.57
6.76
131.75
BZU-75
108.67
0.00
21.00
15.65
35.00
3.67
6.43
129.77
Sitara-12
130.00
1.00
20.00
11.70
36.00
3.64
7.20
132.54
Tarzen-402
125.00
1.66
17.33
1.60
37.83b
3.57
7.46
136.43
NIAB-1
115.00
0.00
19.33
12.46
34.66
3.64
6.46
128.08
CEMB-44
113.00
1.66
20.00
14.86
31.66
3.91
6.26
123.70
CIM-602
111.00
0.00
20.33
14.46
36.66
3.55
6.40
131.45
AA-919
113.67
0.66
21.00
13.56
32.00
3.85
6.30
125.36
SB-149
122.00
0.66
22.00
15.28
37.66
3.54
6.56
135.04
MM-58
115.67
2.00
21.66
14.98
45.66
3.19
6.60
147.77
SLH-4
111.00
0.66
24.00
16.50
37.66
3.57
6.66
135.31
Soyaben-202
122.33
0.33
23.66
18.16
37.50
3.52
6.50
133.73
VH-282
132.33
0.00
19.66
13.60
31.66
3.89
6.20
124.26
JS-1V
117.33
0.66
24.66
14.36
33.33
3.76
6.26
126.91
CEMB-33
117.33
0.00
22.33
14.36
31.66
3.88
6.30
124.30
FH-118
117.67
0.33
27.66
12.86
30.33
3.95
6.20
122.23
Tarzen-3
123.00
2.33
23.66
13.10
35.66
3.54
6.33
127.04
AA-904
116.33
1.00
22.00
12.43
36.66
3.23
6.23
122.67
LSD (5%)
9.1028
0.8733
2.8347
3.0922
3.5851
0.3245
0.3048
5.9435
Genetic Diversity Analysis through Phenotypic Assessment… 741
Table-3 Vector loadings and explained percentage variance by the 8 PCs.
4. CONCLUSION
Highly significant differences were observed among
Bt cotton genotypes evaluated for all the 8 studied traits.
The results of the current study show the presence of
genetic diversity among the selected Bt cotton
genotypes. Parents from divergent clusters can be used
for hybridization in order to separate useful
recombinants in the segregating generations. This
information might be used in the genetics and breeding
programs for improvement of upland cotton genotypes.
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Characters
Eigenvectors
PC1
PC2
PC3
PC4
PC5
PC6
PC7
PC8
Plant height
-0.2116
-0.3224
0.6466
0.2105
-0.5028
-0.3649
0.0493
0.0240
Monopodial branches plant-1
-0.3353
-0.2756
0.2856
-0.1141
0.8098
-0.2413
-0.0014
-0.0555
Sympodial branches plant-1
0.0549
-0.5657
-0.1570
0.6757
0.1077
0.4287
-0.0136
-0.0880
Sympodial branches length
-0.0951
-0.5592
-0.0190
-0.6841
-0.2083
0.3936
-0.0623
-0.0110
Bolls plant-1
-0.5153
0.0504
-0.1804
-0.0059
-0.0548
0.1229
0.5692
0.5978
Boll weight
0.4966
-0.0630
0.3098
-0.0921
0.1392
0.0885
-0.2395
0.7486
Seed index
-0.2675
0.4246
0.5247
0.0682
0.0465
0.6604
-0.1231
-0.1217
Seed cotton yield plant-1
-0.4971
0.0240
-0.2675
0.0702
-0.1096
-0.1042
-0.7727
0.2366
Eigenvalues
3.38706
1.60614
1.07494
0.81725
0.57447
0.37777
0.11320
0.04918
Percent of variance
42.3
20.1
13.4
10.2
7.2
4.7
1.4
0.6
Cumulative percent of variance
42.3
62.4
75.9
86.1
93.2
98.0
99.4
100.0
M. A. MUGHERI et al., 742
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