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Judul: | Aplikasi GGE Biplot Untuk Evaluasi Stabilitas dan Adaptasi Genotipa-Genotipa Dengan Data Percobaan Lingkungan Ganda |
Penulis: | E. Jambormias & J. Riry || email: jbdpunpatti@yahoo.com |
Jurnal: | Budidaya Pertanian Vol. 4 no. 2 - hal. 84-93 Tahun 2008 [ Pertanian ] |
Keywords: | GGE Biplot, stability, local adaptation, specific location, MET data |
Abstract: | Evaluation of stability, local adaptation and specific adaptation of genotypes on specific environment from a Multi-environment Trials (MET) Data become more difficult when there is a genotype-by-environment interaction. GGE Biplot display offers a better solution to evaluate such a tendency, especially to show mega-environment differences; stability, local adaptation and location-specific adaptation and to evaluate the trial environment whether a mega-environment is representative as a suitable environment to plant production. The research data were soybean (Glycine max L. Merrill) yield data from a computer simulation from a trial location. The data structured were a 7 x 7 factorial of experiment (genotype factor with seven number genotypes and environment factor with seven number locations) with three replication which were nested in seven locations, and one location was assumed as a specific environment (marginal environment). Genotypes were coded as G1, G2, G3, G4, G5, G6, G7, and environment were coded as L1, L2, L3, L4, L5, L6, L7. Data analysis was initiated by singular value decomposition (SVD) of the genotipe x environment cross tabulation data. The Singular value and principal component scores was used to generate a biplot curve between the first principal component (PC1) and the second principal component (PC2). The results of the data analysis showed: 1) there were three different mega-environments; 2) one genotype (G5) was agronomically stable; 3) two genotypes (G1 and G6) showed local adaptation at each mega-environment; 4) one genotype (G6) showed a specific adaptation to a specific environment; and 5) two locations that was suitable for increasing plant yield so that the mega-environment the contained these locations represented a trial environment that was suitable to increasing plant yield. |
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