Mahmood & et al. 592 CLUSTER ANALYSIS AMONG NINE COTTON GENOTYPES ر

Abstract

The field trial was conducted at Qwshtapa district , Grdmala village, which is 30 km far from center of Erbil city to compare between nine genotypes of cotton (Gossipum hirsutum L) during the growing season 2016, the genotypes were (Coker 310, Lachata ‘Iraqi genotypes ’ Cafko, Dunn 1047, Montana, Stone Ville ‘ USA genotypes ‘, Bakhtegon, Khdorda , Vanamin Iranian genotypes ) using randomized complete block design (RCBD)with three replicates. any fertilizers were not added to the field during the research and Irrigation was done using Statistical analysis of the traits shown significant differences among genotypes , Coker 310 obtained the highest value for number of fruiting brunches, number of Bolls plant-1،Boll weight )g(, seed yield plant-1, ginning% and oil% with values of (8.93 ,29.27,4.23, ,77.67, 39.87 and 28.33 ) respectively. Lashata genotype recorded highest value of protein and linoleic acid % which were (34.82 and 63.68) % respectively. Depending on growth stage, agronomic characteristics and their quality the genotypes were discerning to three main clusters, the first one included (Lachata and Stone Ville) genotypes, while the second clusters indicated only Cafko genotype and the third cluster included (Coker 310, Dunn 1047and, Montana, Bakhtegon , Khdorda and Vanamin) genotypes.

Full text

Iraqi Journal of Agricultural Sciences –:51():592-599 Mahmood & et al.
592
CLUSTER ANALYSIS AMONG NINE COTTON GENOTYPES
ABSTRACT
The field trial was conducted at Qwshtapa district , Grdmala village, which is 30 km far from
center of Erbil city to compare between nine genotypes of cotton (Gossipum hirsutum L)
during the growing season 2016, the genotypes were (Coker 310, Lachata ‘Iraqi genotypes ’
Cafko, Dunn 1047, Montana, Stone Ville ‘ USA genotypes ‘, Bakhtegon, Khdorda, Vanamin 
Iranian genotypes ) using randomized complete block design (RCBD)with three replicates.
any fertilizers were not added to the field during the research and Irrigation was done using
Statistical analysis of the traits shown significant differences among genotypes , Coker 310
obtained the highest value for number of fruiting brunches, number of Bolls plant-1Boll
weight g, seed yield plant-1, ginning% and oil% with values of (8.93,29.27,4.23,,77.67,
39.87 and 28.33 ) respectively Lashata genotype recorded highest value of protein and linoleic
acid % which were (34.82 and 63.68) % respectively. Depending on growth stage, agronomic
characteristics and their quality the genotypes were discerning to three main clusters, the first
one included (Lachata and Stone Ville) genotypes, while the second clusters indicated only
Cafko genotype and the third cluster included (Coker 310, Dunn 1047and, Montana,
Bakhtegon , Khdorda and Vanamin) genotypes.
Keywords: Cotton genotypes, yield, seeds quality, Cluster analysis.
- )592599 


   



(
Gossipum hirsutum
L)
 




8.93,29.27,4.23,77.679.87 
)34.82
 
    

  



*Received:11/9/2019, Accepted:23/12/2019
B. J. Mahmood L. Q. Ahmed K. Kamal A. Hamedi A. Ahmad
Assist. Prof. Lecturer Assist. Lecturer Researcher Researcher
Dept. Field Crops – Coll. Agric. Engin. Sci - Salahaddin - University-Erbil
Bahar.mahmmod@su.edu.krd

Iraqi Journal of Agricultural Sciences –:51():592-599 Mahmood & et al.
593
INTRODUCTION
Cotton (Gossypium hirsutum L.) regards as a
white gold, which is occupying a prominent
position in oil and textile industry, it serves as
a backbone of the countries that made it as
cash crops, and is a significant source of
foreign exchange earnings (1). Cotton is the
second most important oilseed crop in the
world (2). The oil of cotton seeds regards as
the preferred vegetable oil, that produces the
most flavorful potato chips on the market. The
hydrogenate is not necessary for increasing its
oil stability (3). The growth and seed cotton
production per unit area is affected by the
following factors: Genotypes, sowing time,
soil status, and environmental conditions (4).
The yield of cotton was affected significantly
by genotypes and sowing dates (5). On the
other hand (6) referred that genotypes have a
significant role in production of cotton crop,
there were highly significant differences
among genotypes for all qualitative and
quantitative traits. (7) reported from their
study on three genotypes of cotton that there
were e significant differences for number of
bolls and its components (seed and lint). From
a comparisons study among six genotypes (8)
stated that the genotype Lachata was superior
in seed yield, boll weight and ginning out turn
with the values of (4.20 Mg ha-1, 5.25 g and
3.38%) respectively. The degree of variation in
growth and dry matter partitioning was
explored among nine cotton genotypes of
diverse growth habit and how these may affect
crop maturity. Because cotton is an
indeterminate species, the timing of crop
maturity is largely determined by the capacity
of the plant to continue the production of new
vegetative organs and the associated fruiting
sites (9). The results obtained from the study
on four cultivars ( CIM-499,CIM-473 CIM-
496 and CIM-506 ) of upland cotton that there
were significant differences between the
cultivars in seed yield the highest value was
(2.45 ), while the lowest value was (1.20 kg
ha-1 )(10) .Since there are little studies about
comparison among different American ,
Iranian and local genotypes ,for this reason
this study was conducted to focus on the
effect of different genotypes on yield , yield
components and oil quality of nine cotton
genotypes.
MATERIALS AND METHODS
The field experiment was carried out during
summer growing season 2016 at Qwshtapa
district, the village of Grdmala 30 km far from
center of Erbil city, with GPS reading of 360⁰
ON and 44001 E,0411359,03997002 UTM 44
03 ⁰,413.8 m above sea level E using
randomized complete block design (RCBD)
with three replicates. Nine cotton genotypes
were used which two Iraqi genotypes (Coker
310 and Lachata ), four USA genotypes
(Cafko, Dunn 1047, Montana and Stone Ville)
and three Iranian genotypes ( Bakhtegon,
Khdorda and, Vanamin ) The area of each plot
was 6 m2 (3*2m),the distances between rows
were 70 cm and plant to plant was 25 cm so
each plot contains 32 plants. On 30th April, the
cotton seeds were sown uniformly using seed
rate of 25 kg ha-1.The soil properties were
recorded in table(1).
Table 1. Some physic-chemical properties of the studied soil.*
Physical Properties
Value
Particle Size Distribution
Sand
118 g kg-1
Silt
432 g kg-1
Clay
450 g kg-1
Textural Name
Silty Clay
Chemical Properties
Value
Chemical Properties
Value
pH
7.86
Total Nitrogen
0.80 g kg-1
ECe
0.50 dS m-1
Available – P
9.3 mg kg-1
CEC
22.87 Cmolc kg-1
Total CaCO3
250 g kg-1
Organic Matter
9.70 g kg-1
Active CaCO3
15.55 g kg-1
Iron
2.98 mg kg-1
Copper
0.80 mg kg-1
Manganese
2.77 mg kg-1
Zinc
0.50 mg kg-1
Soluble cation and anion
Chemical Properties
Value
Chemical Properties
Value
Potassium
1.14 mmol L-1
Chloride
2.30 mmol L-1
Magnesium
1.55 mmol L-1
Bicarbonate
3.50 mmol L-1
Sodium
0.95 mmol L-1
Carbonate
0.00 mmol L-1
Calcium
2.50 mmol L-1
SO4-2
0.86 mmol L-1
* (11)

Iraqi Journal of Agricultural Sciences –:51():592-599 Mahmood & et al.
594
The thinning of plants was on 16th June;
Irrigation was done using drip irrigation
methods (DIM), which is one of the technical
measures to increase water use efficiency.
Under this method, water is delivered directly
to the root zone of the crops using pipe
networks and emitters. This method is entirely
different from the conventional (11), the
amount of water applied was 1 L .hr-1, all other
agricultural practices were done whenever
necessary. Randomly 10 plants were taken
from each treatment at the mature stage
(opening 60% of bolls) for measuring and
collecting different parameters, in depending
on Fattah (9). Some traits were recorded
including plant height (cm), number of bolls
per plant, boll weight (g), weight of 100
seeds(g) and yield of cotton seeds (kg ha-1),
The cotton bolls were harvested according to
genotypes that were cultivated separately,
finally the cotton seed calculated in unit kg per
hectare. The 100 seeds were taken from each
treatment and measured in gram).
Ginning out turn (GOT)
Before the ginning, seed cotton samples were
air dried. Dusts and inert matter were removed
from samples and then weighed and ginned
separately manually. The lint obtained from
each sample was weighed and its percentage
was calculated by applying the following
formula.
𝐆𝐢𝐧𝐧𝐢𝐧𝐠 𝐨𝐮𝐭 𝐭𝐮𝐫𝐧 (𝐆𝐎𝐓) =
𝑾𝒆𝒊𝒈𝒉𝒕 𝒐𝒇 𝒍𝒊𝒏𝒕
𝒘𝒆𝒊𝒈𝒉𝒕 𝒐𝒇 𝒔𝒆𝒆𝒅+𝒍𝒊𝒏𝒕 × 𝟏𝟎𝟎 (12)
The oil was determined by Soxhlet extraction
apparatus using hexane according to the
methods described by Mahmood et al. (13).
The Total Nitrogen was determined using the
Kjeldahl method then the protein percentage
was determined as follow:
Protein% = N% × constant value which equal
to 6.25 Statistical analysis was done using
SPSS program version 25 for comparing
between means using Duncan’s multiple range
test at probability (p

0.95) (14). Cluster
analysis was conducted between studied
genotypes using XLSTAT-Premium Program
to obtain homogenous groups by
agglomerative hierarchical clustering (AHC)
and principal component analysis (PCA), to
show the similarity and dissimilarity between
genotypes (15).
RESULTS AND DISCUSSION
This study showed significant results
indicating varying genetic diversity of the
genotypes for the studied characters such as,
plant height, number of fruiting brunch,
number of bolls per plant, boll weight and seed
yield per plant and boll yield ha-1. Table 2
shows significant effect between genotypes on
plant height, the highest value (125.40 cm)
was recorded for Lachata, While the lowest
value (103.13cm) recorded for Bakhtegon
genotype this results was in agreement with
those recorded by Saeed et al. (16). The
highest values has for number of fruiting
branch, number of bolls Plant -1, bolls weight
(g) and seed yield plant -1 were recorded from
Coker 310 with the values of( 8.93,29.27,4.23
and 77.67)respectively, while the lowest
values of them (7.20,19.00,3.58and 60.23)
were obtained for Khdorda genotypes
respectively ,these results explain that the
genotype is the main factor affected on the
above traits (17), or it means that genotypes
are differing in their adaptation to Erbil
environments. The same Table, shows the
significant variation in biological yield among
the genotypes, Lachata was recorded the
highest (3.58) Mg ha-1 biological yield, while
Vanamin genotypes recorded the lowest (2.13)
Mg ha-1. This could be due the difference in
yield genetic potentiality of the studied
genotypes (18). The dynamics of dry matter
production and reproductive demand may also
have a significant impact on the yield of
different genotypes (9).

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Table 2. Effect of genotypes on some growth and yield characteristics
Table 3 Refers to the significant differences
among the studied genotypes, Bakhtegon
recorded the highest value for seed index and
fiber plant-1 with the values of (6.40 and 8.65)
respectively. While their lowest values (5.13
and 6.46) were obtained from Cafko and
Montana genotypes respectively, since the
seed index was mostly affected by genotypes
because it depends on velocity of seed growth
which considered genetic characters and to be
the main goal from cotton production (16).
The highest seed% and net ginning out %
(64.80 and 39.87) % were recorded from
Lachata and Coker 310 genotypes
respectively, while their lowest values
(60.13% and 35.40) Lachata and Cafko
genotypes respectively. These results were in
agreement with Others (19), they found that
differences in ginning may be due to
differentiation between genotypes and total
cotton lint yield which reflect positively on
this characteristics as mentioned by (16).
Table 3. The comparison between genotypes on some field characteristics
The results in Table 4 shows significant effect
of cotton genotypes on oil % the highest and
lowest values (36.33 and 18.33 %) were
obtained for Coker 310 and Stone Ville
genotype respectively, these differences
contributed to their genetic properties. While
the highest values for both protein % and
linoleic acid% (34.82 and 63.68 ) % were
obtained for Lachata genotype and the lowest
values(28.47 and 26.90) % were recorded for
Vanamin and Cafko respectively. These results
are in agreement with (20) they indicated that
oil% and protein % in cotton were (18-26 %)
and (32-36%) respectively. It is appear from
the same Table that highest and lowest values
of oleic acid were found from Stone Ville and
Cafko genotype respectively. On the other
hand the highest and lowest values of linolenic
content were recorded from Dunn 1047 and
Vanamin genotypes.
Genotypes
Plant
height
(cm)
No. node
till
branchig(g)
No.
vegetativbr
unch
No.
Fruiting
brunch
No.
Boll
Plant-1
Boll weight
(g)
Seed Yield
Plant-1 (g)
Biological
Yield
Mg ha-1
Coker 310
105.07bc
4.87a
3.33a
8.93 a
29.27a
4.23 a
77.67a
3.39a
Lachata
125.40a
4.33a
3.87a
8.13 ab
22.80ab
3.66ab
68.91ab
3.58 a
Cafko
118.53ab
4.53a
3.67a
8.40 ab
20.27ab
3.62 b
63.58bc
3.16 a
Dunn 1047
107.80bc
4.20a
4.53a
8.8 ab
21.53ab
3.32 b
67.91ab
2.92 ab
Montana
103.15c
5.33a
4.27a
7.33 ab
17.40b
3.45 b
61.88bc
2.87 ab
Stone ville
115.00abc
4.67a
4.27a
8.60 ab
19.40b
3.72 ab
64.55bc
2.81 ab
Bakhtegon
103.13c
5.27a
4.2a
7.33 ab
16.47b
3.84 ab
74.03ab
2.68 ab
Khdorda
105.47bc
5.40a
3.4a
7.20 b
19.00b
3.58 b
60.23c
3.02 ab
Vanamin
110.80bc
4.60a
4.28a
7.60ab
17.73b
3.56 b
50.76a
2.13 b
Genotypes
Seed index
Seed %
Ginning
Fiber/plant
Coker 310
5.30 b
63.91 ab
39.87 a
6.64 b
Lachata
5.52 ab
64.60 a
35.40 b
6.48 b
Cafko
5.13 b
60.13 b
36.09 ab
6.55 b
Dunn 1047
5.63 ab
64.01 ab
35.99 ab
6.89 b
Montana
5.42 ab
62.55 ab
37.45 ab
6.46 b
Stone ville
5.58 ab
61.99 ab
38.01 ab
7.02 b
Bakhtegon
6.40 a
60.91 ab
39.09 ab
8.65 a
Khdorda
5.56 ab
62.65 ab
37.35 ab
6.64 b
Vanamin
5.28 b
62.13 ab
37.87 ab
6.74 b

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Table 4.The comparison between genotypes on some quality characteristics
Genotypes
Oil %
Protein%
Oleic%
Linoleic%
Linolenic%
Coker 310
28.33a
29.25d
15.96g
53.34b
0.51c
Lachata
25.00b
34.82a
35.94b
63.68a
0.40c
Cafko
26.00ab
31.32c
15.88g
26.90 h
1.46b
Dunn 1047
24.33bc
33.22ab
27.70d
45.87d
2.25a
Montana
20.67d
34.13a
28.61c
45.53d
0.58c
Stone ville
19.67d
34.76a
47.56a
48.30c
1.69b
Bakhtegon
24.67bc
33.71a
21.79f
33.55g
1.47b
Khdorda
24.00bc
31.73bc
35.71b
36.75f
0.39c
Vanamin
22.00d
28.47d
24.59e
39.94e
0.33c
Fig 1 explains the results of statistical analysis
using Dendrogram, which classified the
genotypes to three main clusters, the first one
included (Lachata and Stone Ville), the second
clusters included only Cafko genotype and the
third cluster included the remain genotypes
which were (Coker 310, Dunn 1047and,
Montana, Bakhtegon, Khdorda, and Vanamin).
The genotypes within the same cluster are
similar in the studied characters. It explains
that the Dunn1047 and Montana genotypes
are much more similar than Vanamin in the
same clusters.
Fig 1. Dendrogram obtained from a cluster analysis of the genotypes
Table 5 shows the proximity matrix of this
research, which refers to similarity and
dissimilarity, the highest value (43.32) refers
to higher dis-similarity. Relationship between
the two Genotypes Lachata and Cafko, the
same dis-similarity were obtained between
Lachata and Bakhtegon (41.68) it means there
are highest differences between them while the
value of 8.32 refers to the similar relation
between Dunn 1047and, Montana as
mentioned
Table 5. The proximity matrix (Euclidean distance)
Coker 310
Lachata
Cafko
Dunn
1047
Montana
Stone Ville
Bakhtegon
Khdorda
Coker 310
Lachata
31.988
Cafko
32.382
43.316
Dunn 1047
20.465
27.837
25.593
Montana
23.691
32.388
28.358
8.324
Stone ville
38.877
26.526
39.763
22.365
23.053
Bakhtegon
25.943
41.677
22.954
18.701
19.715
35.419
Khdorda
28.645
34.434
26.199
13.297
13.321
21.111
17.751
Vanamin
23.268
32.914
18.512
10.825
12.138
26.274
18.296
14.299
Fig 2 Shows some observations on the studied
genotypes it’s clear that at the right side the
closest distance mean more similarity in the
same cluster there are different manner
between the genotypes stone Ville and
Dunn104 was in the positive side while Cafko
and Lachata was negative .this explanation is
the same for the second cluster.

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597
Fig 2. Cluster analysis of the characteristics of the genotypes
There is a very high correlation between seed
yield and the number of the ball per plant,
plant height, seed % and linoleic acid as
mentioned in Fig 3. Clustering variables can
be a useful way to discover which traits or
groups of traits tend to similar or vary together
in a population.
Fig 3. Cluster analysis between variables in the comparison study
In Figure 4 the genotypes and variables are
merged and give a different explanation. The
variables close to the center there will not be
significant differences between them for
example in leachate and Kafko genotype is
closest in yield, seed%, and fruiting brunch
…etc variables. Protein seed, oleic and linoleic
is more close to Dunn 1047 and Stone -Ville
genotype, any of the variables are close mean
there is a positive reaction between them and
the other side has a negative reaction with the
first one.

Iraqi Journal of Agricultural Sciences –:51():592-599 Mahmood & et al.
598
Fig 4. Cluster analysis between variables in the comparison study
Conclusion
The studied genotypes had shown significant
differences in most traits, the Lachata and
Coker 310 genotypes were the most superior
in most quantitative and qualitative characters
comparing with other cultivars.
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