Document Type : Research Paper
Authors
1
Department of Plant Science and Agricultural Resources, Faculty of Agriculture, Khon Kaen University, Khon Kaen 40002, Thailand.
2
Department of Biological and Agricultural Engineering, the University of Georgia, Griffin, Georgia 30223-1797, USA.
Abstract
The adaptive responses of crop genotypes and patterns of genotype x location (G x L) interaction are important to crop improvement as they are the basis for selection for specific adaptation and for elucidation of the causes of G x L interaction. Their legitimate assessment, however, requires yield data for the test genotypes for a large number of sites and over multiple years. Such data are seldom available from actual trials but could be provided by a crop simulation model. The objectives of this study were to assess the adaptive responses of a set of diverse peanut genotypes and to determine the various patterns of G x L interaction between pairs of these genotypes using a modeling approach. Pod yield of 17 peanut lines was simulated for 112 locations covering all peanut production areas in Thailand over three seasons and 30 years with the Cropping System Model (CSM) CROPGRO-Peanut. The data were analyzed for the adaptive response to locations of each peanut genotype with linear regression. Patterns of G x L interaction for the individual pairs of genotypes were determined. The results showed that the test genotypes could be classified into five groups based on mean yield and adaptive response, i.e., average yield with a low (<1.00) regression coefficient (Entries 5, 6, 8), above average yield with an average (=1.00) regression coefficient (Entries 3, 7, 10, 11, 12), above average yield with a high (>1.00) regression coefficient (Entries 13, 15, 17), below average yield with a low regression coefficient
(Entry 1), and below average yield with an average regression coefficient (Entries 2, 4, 9, 14, 16). These characteristics are the basis for selection for either broad or specific adaptation. All three patterns of G x L interaction, i.e., no interaction, non-crossover interaction and crossover interaction, were also identified. Further analysis of these interaction patterns is recommended to elucidate the crop characters and environmental factors that are the causes of G x L interaction. The results indicate the potential of using crop simulation models as a tool to analyze adaptation of crop genotypes and to determine the pattern of G x L interaction for the individual genotype pairs.
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