  There is no doubt on the importance of randomisation in agricultural
experiments by agronomists and biometricians. Even when agronomists extend the
experimentation from small trials to large on-farm trials, randomised designs
predominate over systematic designs. However, the situation may change
depending on the objective of the on-farm experiments (OFE). If the goal of OFE
is obtaining a smooth map showing the optimal level of a controllable input
across a grid made by rows and columns covering the whole field, a systematic
design should be preferred over a randomised design in terms of robustness and
reliability. With the novel geographically weighted regression (GWR) for OFE
and simulation studies, we conclude that, for large OFE strip trials, the
difference between randomised designs and systematic designs are not
significant if a linear model of treatments is fitted or if the spatial
variation is not taken into account. But for a quadratic model, systematic
designs are superior to randomised designs.
