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193674

MULTIVARIATE STATISTICAL ANALYSISOFFABA BEANYIELD AND YIELD COMPONENTS

Article

Last updated: 05 Jan 2025

Subjects

-

Tags

Agricultural Economics and Management Sciences

Abstract

Two field experiments were conducted at Sdment elgabal, BeniSuef Governorate during the two winter seasons of 2011/2012 and
2012/2013 to evaluate the performance of five faba bean varieties (Giza
2, Giza 40, Giza 429, Giza 843, and Misr1) for seed yield and related
traits. Five statistical procedures ,
i.e., descriptive statistics, simple
correlation, multiple linear regression, stepwise regression, factor
analysis and path analysis were applied to determine the relationship < br />between faba bean seed yield and its components.
Highly significant and positive associations were detected
between seed yield (g/plant) and each of plant height, number of
pods/plant and harvest index.
From the multiple linear regression analysis revealed that plant
height, number of seed/ pod, weight of seeds/pod, 100seeds weight and
harvest index were significantly contributing to seed yield. Stepwise
analysis indicated that plant height, number of pods/plant, harvest index
and number of seeds/ pod were accepted as major variables contributing
to seed yield/plant variation with R
2 =68.9%. Factor analysis classified
the eight studied traits into three main factors explaining 70.19% of the
total variability in the dependent structure.
Factor 1 was responsible for 26.74% of the total variation in
yield and included number of pods/plant and seeds weight /pod. Factor 2
included number of seed/pod and 100-seed weight and contributed by
26.46% of the total variation. Plant height, number of branches/plant
and harvest index were the components of the third factor and accounted
for 16.99% of the total variation. Path analysis indicated that the highest
positive direct effects were scored by plant height, number of seeds/pod,
100-seed weight, harvest index and weight of seeds/pod with relative
contribution to total yield variability of 12.13% ,11.78%,7.19%,6.82%
and 4.82%, respectively. The greatest components of indirect effects for
most traits of 16.45% were shown by number of seeds/pod via 100 seed
weight. Consequently, it seems that selection for these last two traits
could be useful for improving faba bean productivity.


DOI

10.21608/fjard.2014.193674

Keywords

Faba bean, descriptive analysis, correlation coefficients, stepwise multiple linear regressions, factor analysisand path analysis

Authors

First Name

S.K.A.

Last Name

Ismail

MiddleName

-

Affiliation

Agronomy Department, Faculty of Agriculture, Fayoum University.

Email

-

City

-

Orcid

-

First Name

Sahar

Last Name

A. Farag

MiddleName

-

Affiliation

Center Laboratory for Design & Statistical Analysis Research, Agriculture Research Center, Giza, Egypt.

Email

-

City

-

Orcid

-

First Name

Iman

Last Name

Kh. Abbas

MiddleName

-

Affiliation

Center Laboratory for Design & Statistical Analysis Research, Agriculture Research Center, Giza, Egypt.

Email

-

City

-

Orcid

-

Volume

28

Article Issue

1

Related Issue

27561

Issue Date

2014-01-01

Receive Date

2021-09-08

Publish Date

2014-01-01

Page Start

108

Page End

121

Print ISSN

1110-7790

Online ISSN

2805-2528

Link

https://fjard.journals.ekb.eg/article_193674.html

Detail API

https://fjard.journals.ekb.eg/service?article_code=193674

Order

7

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

MULTIVARIATE STATISTICAL ANALYSISOFFABA BEANYIELD AND YIELD COMPONENTS

Details

Type

Article

Created At

23 Jan 2023