Year related interactions for seed yield and oil content in rapeseed agronomic management trials interpreted using climatic variables

Abstract

Interaction in agronomic trials seriously complicates the identification and recommendation of the highest yielding cultivars for specific environmental conditions. As the part of the study aimed to investigate the influence of climatic variables through the rapeseed development stages, the objective of the presented study was to identify the most important climatic variables in cultivar x year interactions for seed yield and oil content of four commercial rapeseed cultivars. The cultivars were grown during the four cropping seasons in two independent trials: the first one investigated the effect of five nitrogen rates, and the second effect of three sowing dates. Throughout rapeseed developmental stages, thirty climatic variables were derived from the original meteorological records and used for data interpretation. Experimental data were processed by mixed model analysis and individual factorial regression model. All interactions had highly significant impact on seed yield and oil content in both trials, except of year x cultivar interaction in sowing date trial. Individual factorial regression model identified that the considerable number of climatic variables had impact on these interactions. In conclusion, the results of this study shawed that more complex factorial regression models are needed ta be constructed in order to give us a more robust interpretation of data.