Precision farming experiments are generally incompatible with conventional statistical methods and alternative models of response variables (e.g. yield) must be estimated if the effect of the management decision is to be distinguished from other sources of variation. The model-based statistical analyses of these experiments require assumptions regarding the variation of the response variable. When these assumptions are inappropriate (e.g. if the correlation between response variable measurements is poorly modelled) then the inferences from the experiments can be unreliable.

Marchant, B. et al. Establishing the precision and robustness of farmers’ crop experiments. Field Crops Res. 230, 31-45, doi:10.1016/j.fcr.2018.10.006 (2019).