International Seminar ICSRD Purwokerto 25-26 August 2013

1. pendahuluan
GxE Interaction assesment of SR Sweet Corn
Yield based on Additive Main Effect and
Multiplicative Interaction (AMMI) and Biplot in
West Java
Syafi’i, M1,*, Melati, R3, Waluyo, B2 , Ruswandi, D4
1 PhD candidate of Plant Breeding, Agricultural Faculty, Padjajaran University, Bandung, Indonesia
2 PhD candidate of Plant Breeding, Agricultural Faculty, Padjajaran University, Bandung, Indonesia
3 Research Assistant of Plant Breeding Lab, Agricultural Faculty, Padjajaran University, Bandung, Indonesia
4 Associate Professor, Departement Plant Breeding and Biotechnology, Padjajaran University, Bandung, Indonesia

2. pendahuluanINTRODUCTION
 In a maize plant breeding program, to obtain
genotypes with high yield results and is widely
adaptable to be the main goal of a breeder.
 Crops yield other than corn is determined by genetic
factors, is also determined by environmental factors.
 The evaluation of the interaction of genotype and
environment (GXE), is very important, because it is
used to select superior genotypes, identify a suitable
environment, as well as recommendations on the
use of adaptive environments cultivars.
 Therefore, It is necessary to evaluate the genotypes
in multi-location to find out who owned a yield
potential of genotypes, and to determine the location
of the representative to be selected.

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To support the success of the best genotypic selection
needs to consider a suitable environment, which divided
the area under cultivation and testing into a small area
that supports high heritability values​​, and a high yield.
Environmental classification can be determined using
statistical methods, such as Cluster Analysis and AMMI.
Cluster analysis to categorize the environment using
principal component analysis (PCA) (Geng et al., 1990;
Kearsey and Pooni, 1996) and analysis of variance
models AMMI combines with principal component
analysis (PCA) (Smith et al., 2002).

4. pendahuluanMaterials and Methods
Research to identify of the 14 genotypes SR Unpad sweet
corn and 2 check varieties held in 4 locations: Jatinangor,
Lembang, Purwakarta and Arjasari. The research was
conducted in January-April 2013.
The design used was a randomized block design, with 3
replicates. Of each genotype were planted on the plot size of
3 x 5 m2 and comprises 100 plants per plot. Fertilization with
standart dosage given at 4 weeks. Disease control is done by
spraying insecticides and fungicides. Observations were
made of the potential yield dry weight.
Estimation of genotype X environment interaction, and AMMI
biplot variants were analyzed by Cropstat 7.2 for windows
(IRRI, 2003) and continued stability analysis model of
Eberhart-Russel (1966).

5. pendahuluanRESULTS AND DISCUSSION
Results the analysis shows the environment (E) has the
greatest influence on the yields, followed genotypes.
AMMI analysis results shows the AMMI component 1
contribute 81.44% of the sum of squares genotype x
environment interactions, as well as components AMMI
2 states 12.26% of the sum of genotype x environment
interaction. Thus AMMI component 1 has a larger sum of
the squares of the genotype and the AMMI 2 has a
smaller sum of squares of the genotype, the cumulative
sum of the squares have contributed to the genotype x
environment.

6. pendahuluanRESULTS AND DISCUSSION

7. pendahuluanRESULTS AND DISCUSSION
 A biplot using genotypic and environmental scores of
two AMMI components (Yan, 2002). A biplot has 4 areas
that depend on the sign owned by genotypic and
environmental scores. In Figure 1, the location is in 2
sectors, locations Jatinangor (JTN), Lembang (LMBG)
and Purwakarta (PWKT) lies in the sector, while the
location Arjasari (AJSR) lies in other sectors apart.
 Genotyping SR 43, SR 32 and SR 33 is the best
genotypes in the location Arjasari. While genotyping SR
15 is the best in location Jatinangor, Lembang and
Purwakarta. The genotypes can high yielding, it is able
to optimize the ability of the environment to be high
yield.

8. pendahuluanRESULTS AND DISCUSSION
Whereas genotypes SR 4, SR 9, SR 22,
SR 24, SR 25, SR 26, SR 30, SR 31, SR
32, SR 41, SR 52, and check varieties
including stable genotypes in locations
Arjasari, Jatinangor, Lembang and
Purwakarta.
Genotypes are able to optimize a
suboptimal environment into high yield, so
these genotypes have wide adaptability.

9. pendahuluanRESULTS AND DISCUSSION
BIPLOT INTERACTION GXE:
Genotypes are located close to the center point
less responsive in comparison with the
genotypes at the farthest. Genotyping of SR 33
and SR 15 have the highest average yield as
indicated by the high value of PCA1 scores, but
SR 15 has a value score PCA2 relatively small,
so it has a more stable performance. Genotypes
with a relatively small value score PCA1 PCA2
scores and relatively small value is stable
genotypes in all locations

10. pendahuluanRESULTS AND DISCUSSION
Whereas genotypes SR 4, SR 9, SR 22,
SR 24, SR 25, SR 26, SR 30, SR 31, SR
32, SR 41, SR 52, including stable
genotypes in locations Arjasari,
Jatinangor, Lembang and Purwakarta.
Genotypes are able to optimize a
suboptimal environment into high yield, so
these genotypes have wide adaptability.

11. pendahuluanCONCLUSION
i. GxE interaction assessment can be carried out by AMMI
analysis and visualization of association between
genotype (G) and GxE interaction biplot analysis.
ii. In the interaction study 16 genotypes at four locations
can be determined genotypes are widely adaptable, and
environment representative superior genotypes for
selection.
iii. Genotypes SR 43, SR 32 and SR 33 is the best
genotypes in the location Arjasari and SR 15 is the best
genotypes in locations Jatinangor, Lembang and
Purwakarta that this genotype may be a specific location
genotype.
iv. SR 4, SR 9, SR 22, SR 24, SR 25, SR 26, SR 30, SR 31,
SR 32, SR 41, SR 52 are stable genotypes.
v. Arjasari is representative locations for screening superior
genotypes.

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Terima kasih
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