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197011

USING OF MULTIVARIATE ANALYSIS FOR EVALUATING WHEAT GRAIN YIELD AND ITS COMPONENTS UNDER WATER STRESS CONDITIONS

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Last updated: 05 Jan 2025

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Abstract

Twenty bread wheat genotypes differed in yield performance were
grown at Kafr El-Hamam (El-Sharkea Governorate) during two seasons
(2005/2006 and 2006/2007) under water stress conditions. Five
statistical procedures (simple correlation, multiple linear regression,
stepwise regression, factor analysis and principal components analysis)
were used to study the relationship between wheat grain yield and its
components under water stress conditions. The simple correlation
coefficients revealed that the highest positive correlations to grain yield
were no. of spikes/m
2, no. of grains/spike, biological yield t/ ha and
harvest index.
Stepwise multiple regression analysis showed that 92.90% of the
total variation in grain yield could be explained by the variation in
harvest index, biological yield and grains weight/spike. The linear
regression equation was (Y) = -2.201 + 0.092 X
9 + 0.300 X8 -0.160 X6,
where Y, X
9 , X8 and X6 represent, grain yield t/ ha, harvest index,
biological yield and grains weight/spike, respectively. Factor analysis
indicated that four factors could explain approximately 76.5% of the
total variation, which were 33.90% for grains weight/spike, 1000-grains
weight and biological yield (factor 1), 18.50% for plant height and
harvest index (factor 2), 14.60% for no. of grains/spike (factor 3) and
9.50% for no. of spikes/ m
2. The principal components analysis had
grouped the estimated wheat variables into four main components,
which accounted 77.00% from the total variation of grain yield.
However, harvest index, biological yield, no. of spikes/m
2, grains
weight/spike, no. of grains/spike and 1000-grains weight were the most
important variables greatly affected grain yield. It could be concluded
that the multiple statistical procedures which used in this study showed
that the grains weight/spike, harvest index and biological yield were the
most important yield variables to be considered under water stress
conditions.


DOI

10.21608/fjard.2009.197011

Keywords

Water stress, Wheat, Simple correlation, Multiple linear regression, Stepwise regression, factor analysis, principal components analysis

Authors

First Name

M. A.

Last Name

Abd El-Shafi

MiddleName

-

Affiliation

Agronomy Department, Faculty of Agriculture, Cairo University, Egypt

Email

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City

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Orcid

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First Name

S. A.

Last Name

El-Hassia

MiddleName

-

Affiliation

Mathematic Department, Faculty of Science, Amer El-Mohtar University, Lybia

Email

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City

-

Orcid

-

Volume

23

Article Issue

1

Related Issue

27885

Issue Date

2009-01-01

Receive Date

2021-09-30

Publish Date

2009-01-01

Page Start

12

Page End

21

Print ISSN

1110-7790

Online ISSN

2805-2528

Link

https://fjard.journals.ekb.eg/article_197011.html

Detail API

https://fjard.journals.ekb.eg/service?article_code=197011

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2

Type

Research articles.

Type Code

1,920

Publication Type

Journal

Publication Title

Fayoum Journal of Agricultural Research and Development

Publication Link

https://fjard.journals.ekb.eg/

MainTitle

USING OF MULTIVARIATE ANALYSIS FOR EVALUATING WHEAT GRAIN YIELD AND ITS COMPONENTS UNDER WATER STRESS CONDITIONS

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Type

Article

Created At

23 Jan 2023