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Rice Genomics and Genetics 2013, Vol. 4, No. 5, 22-27
http://rgg.biopublisher.ca
22
Research Report
Open Access
Genotype × Environment Interaction (GEI) and Stability Analysis of Backcross
Inbred Lines (BILs) Derived from Swarna × WAB 450 Inter Cross under
Rainfed Ecosystem in North Karnataka state of India
Sangodele Emmanuel A.
1
, Hanchinal R.R.
1
, Hanamaratti N.G.
1
, Vinay Shenoy
2
, Mahantashivayogayya
K.
3
, Surendra P.
1
, Mohammed Ibrahim
3
1 Department of Genetics and Plant Breeding, University of Agricultural Sciences, Dharwad, Karnataka State, India
2 Barwale Foundation, Hyderabad, AP, India
3 Agricultural Research Station Gangavati, University of Agricultural Sciences, Raichur, Karnataka State, India
Corresponding author email: deleadeemma@yahoo.com,
Authors
Rice Genomics and Genetics, 2013, Vol.4, No.5 doi: 10.5376/rgg.2013.04.0005
Received: 16 Jul., 2013
Accepted: 26 Sep., 2013
Published: 14 Dec., 2013
© 2014 Sangodele et al., This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use,
distribution, and reproduction in any medium, provided the original work is properly cited.
Preferred citation for this article:
Sangodele et al., 2013, Genotype × Environment Interaction (GEI) and Stability Analysis of Backcross Inbred Lines (BILs) Derived from Swarna × WAB 450
Inter Cross under Rainfed Ecosystem in North Karnataka state of India, Rice Genomics and Genetics, Vol.4, No.5, 22-27 (doi: 10.5376/rgg.2013.04.0005)
Abstract
The main objectives of this investigation is to determine the GEl effects on grain yield of superior BILs derived from
Swarna × WAB 450 inter cross and to select genotypes that are widely adapted across upland rice growing rainfed areas in North
Karnataka, India. Multi-location yield trials of nineteen superior BILs (BC
1
F
8
) and three checks selected for earliness, productivity,
reaction to blast diseases and grain size were conducted at three locations in six environments. Result of Additive Main effect and
multiplicative interaction (AMMI) analysis showed that genotypes, environments and GEI components were significant. Out of
twenty two genotypes evaluated for GEI effect in this study, six genotypes were found suitable for all environments; six genotypes
for favourable environments while ten genotypes were identified as suitable for unfavorable environments.
Keywords
Genotypes; Environment; Interaction; Population; Adaptation
Introduction
Genotype-environment interaction poses a majour
barrier to the breeder in the process of evolution of
improved variety. Nadarajan et al, (2005) define
environment as the sum total of physical, chemical
and biological factors that influence the development
of an organism. Environment may cause change in the
genetic constitution of a population by pressure of
selection it exercises on the population and in the long
run may lead to evolutionary changes (Dabholkhar,
1992). Since genotype-environment interaction has
masking effect on genotype, it is necessary to estimate
the magnitude of this interaction variance to avoid
over/ under estimation of genotypic variance in
breeding programme.
The importance of
genotype-environment interaction is recognized by
breeder/ geneticist and these are known to be heritable
(Jink et al., 1955) and statistical techniques are
available to estimate them, the main effort of breeder/
geneticist is to reduce them or scale them out.
Interaction of genotypes with environment contributes
to the total phenotypic variation which can be isolated
and tested for significance. Several methods and
techniques have been developed to describe and
interpret the response of genotypes to variation in the
environment. Biologically, genotype with minimum
total variance under different environments is
considered stable (Hanson, 1970). An agronomically
stable genotype has a minimum interaction with
environments but responds favourably to improving
environments (Eberhart et al., 1966). Stability analysis
provides a general solution for the response of the
genotypes to environmental change. Many parameters/
statistics have been used for analyzing stability as
reviewed by Lin et al., (1986), Becker et al., (1988)
and Crossa, (1990). Additive Main effect and
multiplicative interaction (AMMI) analysis has been
shown to be effective because it captures a large
portion of the GE sum of squares and the model often
provides agronomically meaningful interpretation of