Performance and application of the APSIM Nwheat model in the Netherlands

The objective of this study was to investigate field trends in agronomic characters of soybean (Glycine max [L.] Merr.) performance trials. Field experiments were arranged as lattice designs, and for each plot within an experiment, an environmental covariate representing the spatial trend was calculated using neighbour analysis. Correlations between environmental covariates of different characters were then used to analyse the degree of similarity in their spatial trends. Grain yield, seed protein content, and seed size were more influenced by spatial variations than time to flowering, time to maturity, and oil content. Significant correlations between environmental covariates were found, which demonstrate the similarity of trend patterns in different characters within particular experiments. In field trials exhibiting a high degree of spatial heterogeneity, correlations between environmental covariates of grain yield and protein content were highly positive. This indicates that field conditions, which promote grain yield, would also enhance protein content. Moreover, the observed trend patterns considerably affected the calculation of phenotypic coefficients of correlation between grain yield and seed protein content. The results suggest that spatial analysis should be applied to all characters of interest, when field conditions are not homogeneous.