Honigeinlagerung

Farmers seek optimal combinations based on genotypes and agronomic management that can consistently deliver outputs close to the potential of their on-farm environments, while minimizing the risk of uneconomical outcomes. An improved understanding of the environmental context for attainable crop performance can enhance on-farm resource use efficiency. Genotype (G) performance often varies across environments (E), leading to variance differences and rank changes among genotypes (Crossa et al., 2004). Environmental information can be applied to identify appropriate groupings of the environments sampled in multi-environment trials (METs) and to quantify their relationships to the target production environment and to assist interpretations of plant responses to the environments, G×E interactions. The fact that crop performance is strongly influenced by the environment, made researchers consider weather variables to better explain (Heslot et al., 2014) or predict (JarquIn et al., 2014) genotypic performance. Prediction of the genotypic value of a candidate genotype in a specific environment is especially desirable for unobserved environments, i.e. environments for which genotypic data do not exist. However, many important environmental parameters that are required for the interpretation of experimental results and the outcomes of prediction models are not captured routinely in METs. The objectives of this study were to i) to determine critical points for the development of an approach to recommend wheat genotypes registered in a national catalog to farmers, ii) identify suitable predictors for the environmental dimension of G×E interactions and ways that they can be captured routinely in multi-environment trials (METs).