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Defining Sunflower Selection Strategies for a Highly Heterogeneous Target Population of Environments

^a Advanta Semillas S.A.I.C., Ruta Nac. 33 Km 636, CC 559, (2600) Venado Tuerto, Argentina
^b CSIRO Plant Industry, Queensland Bioscience Precinct, 306 Carmody Rd., St. Lucia, QLD 4067, Australia

View larger version (26K): [in a new window]   Fig. 1. GGE (A) and AMMI2 (B) biplots of the first and second principal components for oil yield of 10 sunflower hybrids grown in 46 trials. Genotypes are represented by points and environments by vectors. Black and open circles identify central- and northern-type environments, respectively. In B, symbols indicate genotype groups with members of a similar response pattern at the 4-group level for oil yield. See Table 2 for environment codes.

View larger version (26K): [in a new window]   Fig. 2. Average (A) and individual (B) predicted ratios of correlated response in a subregion to indirect selection in the undivided target region (CR/DR) for different selection strategies consisting of 2 or 4 yr, 3 replicates, and a variable number of testing locations, using the variance components estimates for sunflower oil yield in the central, northern, and undivided target regions of Argentina. Arrows in Fig. 2A show different strategies for division of testing resources.

View larger version (52K): [in a new window]   Fig. 3. Surface plots of predicted hybrid-mean repeatability for oil yield in the central (A) and northern (B) subregions as the number of locations and years of testing in multienvironment trials are changed (assumes three replicates for each location-year combination), based on the within-subregion components of variance given in Table 3. Black triangles indicate repeatability estimates for 1-yr or one-location testing combinations assuming one replicate per trial.