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Volume 2 Issue 12, November 2022 ISSN 2181-2020
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Volume 2
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8
ISSN: 2181-2020
Volume 2 Issue 12 (2022): EJAR
Volume 2 Issue 12 (2022): EJAR
THE EFFECT OF ABIOTIC STRESSES ON PLANT
PRODUCTIVITY TRAITS IN PIMA COTTON GENOTYPES
Sh.A.Xamdullaev
J.Sh.Shavkiev
A.A.Azimov
Institute of Genetics and Experimental Biology of Plants, Academy of
Sciences of the Republic of Uzbekistan, Tashkent Region, Uzbekistan
E-mail: xamdullayevshuxrat@gmail.com
https://doi.org/10.5281/zenodo.15210299
ARTICLE INFO
ABSTRACT
Received: 08
th
April 2025
Accepted: 13
th
April 2025
Online: 14
th
April 2025
,
The study evaluated the productivity of Gossypium barbadense L.
genotypes under drought and salinity. ANOVA was used to
analyze yield parameters of 10 genotypes under optimal, water-
deficient, and saline conditions. Genotypes T-479 (23.01 g) and T-
2090 (21.72 g) showed high drought tolerance, while Duru-
gavhar-4 (15.98 g) and T-2024 (15.54 g) exhibited salinity
resilience. Environmental factors accounted for 79% of yield
variability. Stress-tolerant genotypes are recommended for
breeding programs to develop adaptive cotton varieties.
KEYWORDS
Gossypium barbadense L.,
productivity,
drought,
genotyp,
ANOVA,
breeding.
Introduction
Pima cotton (
Gossypium barbadense
L.) holds a significant position in global agriculture
due to its high-quality fiber and considerable economic value (Shavkiev et al., 2022;
Chorshanbiev et al., 2023; Narimanov et al., 2023; Azimov et al., 2024). In regions like
Uzbekistan, where abiotic stress factors such as drought and salinity are widespread, enhancing
the productivity and ensuring yield stability of this crop remains a key objective in the fields of
genetics and plant breeding (Shukhrat et al., 2021; Chorshanbiev et al., 2022; Azimov et al.,
2023). In recent years, studying plant adaptability to stress conditions has become increasingly
relevant due to climate change and increasing scarcity of water resources. In particular,
identifying genotypes with tolerance to adverse conditions such as drought and salinity, and
evaluating their yield potential, serves as a crucial foundation for the development of stress-
resistant cultivars in the future. In this study, the yield performance of fine-fibered
Gossypium
barbadense
L. genotypes was evaluated under optimal, water-deficit, and saline conditions
(Nabiev et al., 2020; Makamov et al., 2022a, 2022b; Matniyazova, 2022). The primary objective
of the research was to assess the genotypes' tolerance to abiotic stress factors, compare their
yield potential, and identify genotypes adapted to drought and salinity. The results not only
reveal the role of genetic diversity and environmental influence on plant productivity but also
provide practical recommendations for future breeding of cotton cultivars tolerant to adverse
environmental conditions.
Literature Review
Stress tolerance indices are widely used to assess genotype performance under water-
deficient and saline conditions. Fernandez (1992) proposed effective selection criteria for
breeding under stress conditions, emphasizing the importance of distinguishing between yield
potential under optimal conditions and stability under stress. Rosielle and Hamblin (1981)
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developed the theoretical framework for selecting genotypes based on yield differences in both
stressed and non-stressed environments
—
an approach that has been successfully applied in
cotton research (Singh et al., 2016; Yehia, 2020).
Studies on cotton (
Gossypium spp.
) have explored drought and salinity tolerance
concerning yield traits and fiber quality. Singh et al. (2016) evaluated
G. hirsutum
genotypes
under drought conditions using stress indices and found significant genetic diversity in yield
components such as boll number and boll weight. Yehia (2020, 2022) assessed Egyptian fine-
fiber cotton (
G. barbadense
) genotypes under water-deficit conditions using the Stress
Tolerance Index (STI) and Principal Component Analysis (PCA), identifying genotypes with
high drought tolerance. Shilpa et al. (2020) highlighted the relationship between fiber quality
and yield under drought stress, underscoring the necessity of multi-trait selection in cotton
breeding programs.
Statistical methods such as analysis of variance (ANOVA), PCA, and correlation analysis
have enhanced the reliability of stress tolerance studies. Yehia (2022) proposed a
comprehensive evaluation approach that combines PCA and stress tolerance indices for cotton
genotypes. However, the literature tends to focus more on single-stress studies (e.g., only
drought or only salinity), with fewer investigations on their combined effects. Moreover, while
G. hirsutum
has been extensively studied, there is a lack of data on the physiological responses
of
G. barbadense
genotypes under salinity stress.
This study aims to fill these gaps by evaluating the yield performance of
G. barbadense
genotypes under both water-deficit and saline conditions using statistical analyses such as
ANOVA. This integrative approach provides a comprehensive understanding of stress tolerance
and facilitates the identification of genotypes suitable for drought- and salinity-prone
environments.
Materials and Methods
This study was conducted under lysimetric conditions using different water regime
treatments. The first treatment (well-watered control) involved optimal irrigation, with a total
water application of 4800
–5000 m³/ha. The second treatment simulated drought stress, with
a total irrigation volume of 2800
–3000 m³/ha (Shavkiev et al., 2019; Shavkiev et al., 2021;
Makamov et al., 2023). Salinity stress conditions were modeled using moderately saline soil
collected from the Syrdarya region, applied in lysimeter settings. All other agrotechnical
practices were kept uniform across the different treatments.
Yield-related traits of
Gossypium barbadense
L. genotypes were evaluated under both
optimal and stress-induced (drought and salinity) conditions. The plant material consisted of
breeding lines and cultivars developed by researchers at the Institute of Genetics and
Experimental Biology of Plants, Academy of Sciences of Uzbekistan. Data were collected from
plants grown in lysimeter conditions.
To determine the significance of environmental effects and genotypic differences, the
collected data were analyzed using multifactor analysis of variance (ANOVA). The significance
level was set at
P
< 0.05.
Results
Under optimal conditions, plant yield varied among genotypes, ranging from 24.60 g to
41.57 g, demonstrating a high yield potential. The highest yield was recorded in the "T-2025"
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genotype (41.57±1.57 g), confirming its excellent growth and yield potential when fully
supplied with water and nutrients. The lowest yield was observed in the "T-2090" genotype
(24.60±0.87 g), indicating its stable but relatively low productivity. Among other genotypes, "T
-
479" (36.96±0.86 g) and "T
-
5570" (37.37±1.63 g) also showed high yie
lds. Overall, most
genotypes exhibited a moderate, stable yield ranging from 25 g to 37 g.
Under water-deficit conditions, yield significantly decreased, varying between 14.41 g
and 23.01 g. The highest yield under drought stress was recorded in the "T-479" genotype
(23.01±1.54 g), indicating its high tolerance to water stress, with minimal difference compared
to its optimal yield (36.96 g). The lowest yield was observed in the "T-2024" genotype
(14.41±1.13 g), showing a significant reduction (over 11 g) fr
om its optimal yield (25.64 g),
indicating its low adaptability to drought stress. Meanwhile, the "T-
2090" (21.72±0.59 g) and
"Duru-gavhar-
4" (17.98±1.80 g) genotypes performed relatively better under drought
conditions, with "T-2090" maintaining stability with low standard deviation. As a general trend,
water-deficit conditions reduced yield by an average of 10
–
15 g compared to optimal
conditions, confirming the negative impact of this stress factor on productivity.
Table 1. Yield performance (g/plant) of pima cotton genotypes
Genotypes
Yield under Optimal
Conditions (g/plant)
Yield under Water-
Deficit Conditions
(g/plant)
Yield under Salinity
Conditions (g/plant)
X
±
SE
SD
X
±
SE
SD
X
±
SE
SD
Angor (T-1981)
31,19±1,38
2,40
16,27±1,62
2,80
11,15±0,53
0,92
T-479
36,96±0,86
1,49
23,01±1,54
2,66
11,02±0,70
1,22
T-2025
41,57±1,57
2,72
18,48±0,63
1,10
12,54±1,04
1,81
T-2024
25,64±1,07
1,85
14,41±1,13
1,95
15,54±0,79
1,36
T-5570
37,37±1,63
2,83
16,17±1,37
2,37
10,28±0,78
1,36
T-481
24,71±1,35
2,33
15,61±1,32
2,29
14,28±0,40
0,69
T-563
27,44±0,83
1,43
16,92±0,94
1,62
14,42±0,47
0,81
Bo
‘
ston (T-663)
28,97±0,87
1,50
17,89±0,69
1,20
14,93±1,05
1,81
Duru-gavhar-4
28,81±1,32
2,28
17,98±1,80
3,13
15,98±0,59
1,02
T-2090
24,60±0,87
1,50
21,72±0,59
1,02
13,51±0,61
1,06
Under salinity stress conditions, yield further decreased, ranging from 10.28 g to 15.98 g.
The highest yield was recorded in the "Duru-gavhar-
4" genotype (15.98±0.59 g), indicating its
high adaptability to salinity stress, with a smaller reduction (13 g) compared to its optimal yield
(28.81 g). The lowest yield was observed in the "T-
5570" genotype (10.28±0.78 g, SD = 1.36),
which showed a sharp decline of approximately 27 g from its optimal yield (37.37 g), confirming
its low tolerance to salinity stress. Among other genotypes, "T-
2024" (15.54±0.79 g) and
"Bo‘ston (T
-
663)" (14.93±1.05 g) showed relatively stable performance under salinity,
indicating their moderate adaptability to stress conditions. Overall, salinity stress reduced yield
by an average of 10
–
25 g compared to optimal conditions, but genotypes like "Duru-gavhar-4"
and "T-2024" maintained stability.
A multifactorial ANOVA analysis was conducted to determine the effect of genotype and
environment on plant yield traits. The differences in yield traits among genotypes were
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statistically insignificant (P-Value = 0.7176 > 0.05), with an F-Ratio value of 0.68. This indicates
that the genotypes studied in the experiment ("T-2025", "T-479", "Duru-gavhar-4", etc.) are
genetically similar in terms of yield, and the observed differences between them are more
related to external environmental factors than genetic influences.
On the other hand, the environmental effect was statistically highly significant (P-Value =
0.0001 < 0.05), with an F-Ratio value of 46.69, showing a strong impact of environmental
conditions (optimal, water-deficit, and salinity) on yield performance. For instance, the "T-
2025" genotype yielded 41.57 g under optimal conditions, but this dropped to 12.54 g under
salinity stress, highlighting the significant role of the environment in trait variability.
The interaction between genotypes and environment was also significant (SS = 313.17,
MS = 17.3981). These values indicate that different genotypes responded differently to
environmental conditions. For example, the "T-2024" genotype had a yield of 25.64 g under
optimal conditions, but it dropped to 15.54 g under salinity, yet it maintained stability
compared to other genotypes. In contrast, "T-5570" showed a sharp decrease from 37.37 g
under optimal conditions to 10.28 g under salinity, indicating low adaptability to stress.
Additionally, "T-2090" genotype showed strong performance with 21.72 g under water-deficit
stress, indicating its good adaptability to such conditions.
In terms of total variation (Total SS = 2044.19), the environmental effect (SS = 1624.59)
accounted for approximately 79% of the total variation, while the effect of genotype (SS =
106.43) and the interaction (SS = 313.17) contributed to a smaller proportion.
Table 2. Multifactorial ANOVA analysis of the effects of genotype and environment
(optimal, water deficit, salinity) on plant yield traits
Source of Variation
Sum of
Squares
(SS)
Mean
Square
(MS)
F-Ratio
P-Value
Genotype
106.43
53.215
0.68
0.7176
Environment
1624.59
540.353
46.69
0.0001
Genotype × Environment
313.17
17.3981
-
-
Total
2044.19
-
-
-
Analysis of plant productivity shows that, under optimal conditions, the genotypes have
high productivity (24.60
–41.57 g), with genotypes such as “T
-
2025” and “T
-
479” showing the
best results in these conditions. While water scarcity reduced productivity by an average of 10
–
15 g, genotypes like “T
-
479” (23.01 g) and “T
-
2090” (21.72 g) demonstrated tolerance to this
stress. Under salinity conditions, productivity further decreased (10.28
–
15.98 g), but
genotypes “Duru
-gavhar-
4” (15.98 g) and “T
-
2024” (15.54 g) maintained stability. ANOVA
analysis confirmed that the primary reason for the differences in productivity is the
environment, not the genotypes (P-Value = 0.0001). Although the genotypes have similar
characteristics, their adaptability to the environment was different.
Conclusion
From a selection perspective, genotypes that showed high performance under stress conditions
are particularly noteworthy. For droug
ht tolerance, the genotypes “T
-
2090” and “T
-
479” are
recommended, while for salinity adaptability, “Duru
-gavhar-
4” and “T
-
2024” are suggested.
Since these genotypes have maintained relatively high productivity under stress conditions,
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they could serve as an important source for developing drought and salinity-tolerant varieties
in the future.
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