Agronomic researchers have recently begun running large-scale, on-farm field trials that employ new technologies that enable us to conduct hundreds of farm trials all over the world and, by extension, rigorous quantitative and data-centered analysis.  The large-scale, on-farm trials follow traditional small-plot trials where the fields are divided into plots, and different treatments are randomly assigned to each plot. Over the past two years, researchers have been designing trials with plots approximately 90 m in length, following recommendations provided in the agricultural engineering literature in the 1990s. However, in this type of research, smaller plots are preferred for the benefit of more repetitions of the treatments on one field. This is important because advice given to producers is based on the experimental results, and such advice would be of greater value with more repetitions. With the minimum width of experimental plots being fixed due to the size of the farming equipment, the purpose of this research is to investigate optimal plot length. While shorter plot length in the experimental design results in additional plots, there is a tradeoff between the richness of the data from a single plot and the number of plots possible in a field. In order to weigh the tradeoff between the richness of the data from one repetition and the number of repetitions possible in one field with different plot length, Monte-Carlo simulations are conducted to compare the Economic Optimum Rates of fertilization (EOR) derived from the estimated yield on the experiment field with variable plot length and determine the optimal plot length.