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The objective of this work was to identify representative and discriminatory environments to select rice genotypes using the Biplot GGE technique. The rice data base of the Rice Project 2001-2009 was used. Garin yield and proportion of whole grains, individually and by the use of a selection index (yield + whole grains) were analyzed using Biplot GGE. Every Biplot generated was analyzed for distance in mm. between real localities and the ideal; distances were later standardized. In addition, the discriminatory capacity and representativity of each locality were determined. With the exception of Alanje, the localities more appropriate for higher yields (Sona, Baru), were not the same for the obtention of more whole grains (Tonosi, Baru, Divisa). The selection index identifi ed appropriate locations for select (Tonosi, Alanje, Calabacito, Sona, Baru). All localities were effective in their discriminatory capacity for yield. Differences in representativity were observed, with Calabacito and Changuinola occupying the highest and lowest positions, respectively. All localities showed similar discriminatory capacity and representativity for whole grains. Integrating yield and more whole grains it became posible to separate more discriminatory (Remedios, Tanara, Alanje) and more representative (Calabacito, Tonosi, Baru) locations. The practical implication of this work is that it allows us to prioritize research in localities more appropriate for the identifi cation of superior genotypes.

Identificación de ambientes representativos y discriminatorios para seleccionar genotipos de arroz mediante el Biplot GGE