GGE-Biplot Analysis for the Suitability of Soybean Varieties in an Agroforestry System based on Kayu Putih (Melaleuca cajuputi) Stands

Alam, Taufan and Suryanto, Priyono and Nurmalasari, Aprilia Ike and Kurniasih, Budiastuti (2019) GGE-Biplot Analysis for the Suitability of Soybean Varieties in an Agroforestry System based on Kayu Putih (Melaleuca cajuputi) Stands. Caraka Tani: Journal of Sustainable Agriculture, 34 (2). pp. 213-222. ISSN 26139456

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Abstract

The existence of genotype and environment (G x E) interaction causes difficulty in selecting suitable varieties of soybean in an agroforestry system based on kayu putih stands. This study aimed to determine the suitability of adaptive, stable and high yield soybean varieties in an agroforestry system based on kayu putih stands by using GGE-Biplot analysis. The experiment was conducted from May to August 2018 at Menggoran Forest Resort, Playen District, Gunungkidul Regency, Special Region of Yogyakarta, Indonesia. The experiment was conducted using a Randomized Complete Block Design (RCBD) with five block as replications. The first factor was soil type in Menggoran Forest Resort, consisting of Lithic Haplusterts, Ustic Epiaquerts and Vertic Haplustalfs. The second factor was soybean varieties, consisting of Anjasmoro, Argomulyo, Burangrang, Dering I, Devon I, Gema and Grobogan. The observation was carried out on seed dry weight of soybean per hectare. The data were analyzed using Combined Analysis of Variance (ANOVA) with α = 5% and GGE-Biplot. Dering I was the most suitable varieties in an agroforestry system based on kayu putih stands and showed the mean of highest yield of 1.22 tons ha-1. © 2019 Universitas Sebelas Maret.

Item Type: Article
Additional Information: cited By 5
Uncontrolled Keywords: agroforestry system; GGE-Biplot; kayu putih; soybean; suitability; varieties
Subjects: S Agriculture > SD Forestry
Divisions: Faculty of Forestry
Depositing User: Wiwit Kusuma Wijaya Wijaya
Date Deposited: 14 Oct 2024 06:17
Last Modified: 14 Oct 2024 06:17
URI: https://ir.lib.ugm.ac.id/id/eprint/7284

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