The Economic Performances of Different Trial Designs in OnFarm Precision Experimentation: A Monte Carlo Evaluation

On-farm precision experimentation (OFPE) has expanded rapidly over the past years. While the importance of efficient trial designs in OFPE has been recognized, the design efficiency has not been assessed from the economic perspective. This study reports how to use Monte Carlo simulations of corn-to-nitrogen (N) response OFPEs to compare economic performances of thirteen different OFPE trial designs. The economic performance is measured by the profit from implementing the N “prescription” (i.e., estimated site-specific economically optimal N rates) provided by analysing the OFPE data generated by a trial design. Results showed that the choice of trial design affects the final economic performance of OFPE. Overall, the best design was the Latin square design with a special pattern of limited N rate “jump” (LJ), which had the highest average profit and lowest profit variation in almost all simulation scenarios. The economic performance of the high efficiency fixed-block strip design (SF1) was only slightly lower than that of LJ, and could be a good alternative when only strip designs are available. In contrast, designs with gradual trial rate changes over space were less profitable in most situations, and should be avoided. Those results were robust to various nitrogen-to-corn price ratios, yield response estimation models, and field sizes used in the simulations. It was also found that the statistical efficiency measures of trial designs roughly explained the designs’ economic performances, though there are still much part remaining unexplained.