Variability of Fiber Gin Turn out in Cotton Hybrids of the Species

G. Hirsutum L. in Different Growing Zones

S. Egamberdieva

, S. Juraev

and U. Kurbanov

Tashkent State Agrarian University, 100140, University str. 2, Tashkent, Uzbekistan

Keywords: Fiber Variability, Cotton Hybrids, Environmental Adaptation.

Abstract: In 2018-2020, the variability of fiber gin turnout was studied in four hybrid combinations of cotton F

-F

obtained by crossing introgressive forms with high-gin turn outing varieties of foreign selection in the

conditions of the Tashkent, Fergana and Kashkadarya regions. To analyze the variability of economically

valuable traits, we used a graph similar to a box plot used in descriptive statistics. It was shown that in all

years of testing, regardless of the hybrid combination, a greater range of variability in gin turn out appeared

in the Kashkadarya region. Moreover, both right-sided and left-sided transgressions were observed

1 INTRODUCTION

One of the most important areas of work in the

selection of any crop, including cotton, is identifying

the response of plants to the environment, to stressful

condition; determining the level of plant

responsiveness to biotic and abiotic factors. In the

process of growth and development, plants constantly

interact with the environment, resulting in the process

of adaptability of the organism or adaptation.

The basis of adaptation is variability, a property

of an organism that reflects the mechanisms of its

interaction with the environment; it is the most

important factor in evolution, ensuring the

adaptability of species and populations to changing

environmental conditions (Zharkova et al., 2013).

Filipchenko Yu.A. in his book “Variability and

Methods for its Study” defines the concept of

“variability” as “... the phenomenon of some

difference even among closely related individuals ...

and there are no one type of organism that would not

be subject to the effect of this phenomenon"

(Filipchenko, 2001).

According to V.F. Pivovarov, E.G. Dobrutskaya,

the goal of selection is to create genotypes that have

a desired rate of variability (Dobrutskaya, 1997).

https://orcid.org/0009-0005-7368-4073

https://orcid.org/0009-0004-0220-1807

https://orcid.org/0009-0005-7368-4073

The study of the population composition of

varieties and the ontogenesis of plants, the

observations of different morphobiotypes should be

carried out against different environmental

backgrounds (Sinskaya, 1963).

One of the objectives of the research was to study

the variability of traits that determine the phenotype

of cotton plants during selection in four hybrid

combinations, F2-F4, in the conditions of the

Tashkent, Fergana and Kashkadarya regions.

2 MATERIALS AND METHODS

The work was completed between 2018-2020, in

NIISSAVH (Tashkent region, Salar village) and its

branches in the Fergana (Kuva) and Kashkadarya

(Kasbi) regions, within the framework of the project

MV-A-KH-8-2018-205 “Creation of productive

cotton varieties using the adaptive potential of

hybrids and lines, obtained with the participation of

introgressive forms in various soil and climatic

conditions of Uzbekistan.”

The experiments were repeated four times, and

the arrangement of combinations was randomized.

To analyze the variability of economically

valuable traits, we used a box plot, used in descriptive

Egamberdieva, S., Juraev, S. and Kurbanov, U.

Variability of Fiber Gin Turn out in Cotton Hybrids of the Species G. Hirsutum L. in Different Growing Zones.

DOI: 10.5220/0014270400004738

Paper published under CC license (CC BY-NC-ND 4.0)

In Proceedings of the 4th International Conference on Research of Agricultural and Food Technologies (I-CRAFT 2024), pages 395-397

ISBN: 978-989-758-773-3; ISSN: 3051-7710

395

statistics, concisely depicting a one-dimensional

probability distribution (variance). In our

experiments, we drew three boxes in one table - these

are distributions obtained for one trait in one year

from three different regions. The left box is the

distribution of the trait in the Tashkent region, the

middle box is the distribution of the trait in the

Fergana region, and the far-right box is the

distribution of the trait in the Kashkadarya region.

The group sizes do not differ; hence, they are

comparable (Juraev et al., 2023, Juraev et al., 2023,

Juraev et al., 2022, Alimova et al., 2022, Juraev et al.,

2023).

3 RESULTS AND DISCUSSION

In 2018-2020 Four hybrid combinations of cotton F2-

F4 were studied, obtained by crossing introgressive

lines adapted to local conditions with high-yielding

varieties of foreign selection.

Figures 1-3 show the results of variability in fiber

yield for three generations of the F2-F4 hybrid

combination [(L-247 x S-484) x L-248]. It shows that

the greatest variability of the trait occurs in the third

generation of hybrids tested in the Fergana region: the

range was 8.9%. In the second and fourth generations,

the variability of the trait ranged from 2.6 to 5.6%.

The smallest range of variability in fiber yield for this

combination was observed in the Tashkent region

from 2.6 to 3.2%. In the Kashkadarya region, the

range of variability of the trait was from 2.6 to 5.2%.

This combination is also characterized by high

average fiber yields of 38.5-40.4%.

The hybrid combination [(Bukhara 6x L-h) x L-

247) x (L-247 x S-6593)] had the greatest variability

in fiber yield in the Kashkadarya region: in F2, F3 and

F4, respectively 6.2, 5. 1 and 7.1% (Fig. 4 - 6). In the

remaining two areas, the amplitude of the trait

variability was significantly less, from 2.8 to 5.1%.

Due to selections among this hybrid population, it

was possible to increase the average fiber yield.

The average fiber yield of the hybrid combination

[L-248 x (L-243 x S-2552)] was relatively low,

ranging from 33.8 to 38.3. However, in different

generations and in different regions there were forms

with a fiber yield of 39 – 41.8%. The highest

amplitude of variability of the trait, 8.8%, was

observed in the Kashkadarya region in the third

generation. In the remaining two regions, the

variability of the trait ranged from 3.4 to 4.5% (Fig.

7-9).

For the hybrid combination L-248 x S-2016, with

the exception of the fourth-generation experiment in

the Kashkadarya region, where the variability in fiber

yield was 10.7%, the range of variability in the

experiments was relatively narrow - from 1.7 to 4.7%.

The average fiber yield for this combination also

varied between years (Fig. 10-12).

The results of a three-year trial showed significant

differences in fiber yield both between hybrid

combinations and between groups in the regions.

Analysis of variance of hybrids showed that the share

of the influence of the genotype on the variability of

the trait in F2 was equal to 72%, in F3 - 41%, in F4 -

40.1%. The influence of the environment on the trait

in F2 was 11.3%. In F3, the influence of the

environment on the trait turned out to be unreliable,

since the P-value for the environmental factor was

greater than 0.05. The contribution of the

environment to the manifestation of the trait in F4 was

12.6%. In F4, the hybrid combination F4 [(F8 L-247

x S-484) x L-248] was highlighted, which showed

stability of the trait over the years, while its average

fiber yield in different regions reached 39-40%.

4 CONCLUSIONS

To summarize, it can be noted that in all years of

testing, regardless of the hybrid combination, the

widest range of variability in fiber yield appeared in

the Kashkadarya region. Moreover, both right-sided

and left-sided transgressions were observed. Analysis

of phenotypic variability in fiber yield in hybrids of

different genetic origins showed that the magnitude

of variation in the value of the trait largely depends

on the contribution of the genotype.

As V.V. Syukov writes, molecular genetic studies

in recent years confirm that phenotypic variability

includes, in addition to paratypic and genotypic

variability, also genotype-environment interactions,

which are mainly epigenetic in nature (Syukov et al.,

2010). A.H. Paterson et al (Paterson et al., 1991)

found in tomatoes that different QTLs appear for the

same trait under different environmental conditions.

Similar results were obtained by C.W. Stuber et al

(Stuber et al., 1992) on corn, M.C. Ungerer et al

(Ungerer et al., 2003) on Arabidopsis, Zh. Jiang et al

(Jiang et al., 2001) on soybeans, as well as A. Börner

et al (Börner et al., 2002), Yu.V. Chesnokov and

colleagues (Chesnokov et al., 2008, Chesnokov et al.,

2012), V.V. Syukov et al. (Syukov et al., 2012) on

wheat.

Our previous studies have shown that genotypic

variability makes a fairly significant contribution to

the formation of fiber yield, ranging from 42.9 to

60.7%. External conditions influenced the trait from

I-CRAFT 2024 - 4th International Conference on Research of Agricultural and Food Technologies

396

10 to 21%. The influence of the interaction of

genotype-environment factors on fiber yield turned

out to be insignificant.

Using genetically enriched breeding material in

various ecological zones, we managed to create

varieties with a wide reaction rate based on the

expression of polygenes that are adequate to changes

in a complex of environmental factors.

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Variability of Fiber Gin Turn out in Cotton Hybrids of the Species G. Hirsutum L. in Different Growing Zones

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