Abstract:
J. Agr. Sci. Tech. (2016) Vol. 18: 789-803
789
Parametric and Non-parametric Measures for Evaluati
ng
Yield Stability and Adaptability in Barley Doubled
Haploid Lines
M. Khalili
1
, and A. Pour-Aboughadareh
2
∗
ABSTRACT
Multi-environment trials have a significant role in
selecting the best cultivars to be used
at different locations. The objectives of the prese
nt study were to evaluate GE interactions
for grain yield in barley doubled haploid lines, to
determine their stability and general
adaptability and to compare different parametric an
d nonparametric stability and
adaptability measures. For these purposes, 40 doubl
ed haploid lines as well as two
parental cultivars (Morex and Steptoe) were evaluat
ed across eight variable environments
(combinations of location-years-water regime) durin
g the 2012-2013 and 2013-2014
growing seasons in Iran. The Additive Main effect a
nd Multiplicative Interaction (AMMI)
analysis revealed that environments, genotypes, and
GE interaction as well as the first
four Interaction Principal Component Axes (IPCA1 to
4) were significant, indicating
differential responses of the lines to the environm
ents and the need for stability and
general adaptability analysis. The stability parame
ters
S
i
(3)
,
S
i
(6)
,
NP2
,
NP3
,
NP4
as well as
Fox-rank (Top) were positively and significantly co
rrelated with mean yield, suggesting
these statistics can be used interchangeably as sui
table parameters for selecting stable
lines. The results of Principal Components Analysis
(PCA) showed that the first two PCAs
explained 92% of total variation for ranks of mean
grain yield and parameters, and also
clustered stability parameters on the basis of stat
ic and dynamic concepts of stability. In
general, the parametric and non-parametric stabilit
y measures revealed that among
tested doubled haploid lines at different environme
nts, the line DH-30 followed by DH-29
and DH-3 were identified as lines with high grain y
ields as well as the most stable for
variable environments of semi-arid regions of Iran.
Keywords
: Dynamic and static stability, GE interaction, Pri
ncipal Components Analysis (PCA).
