Spatiotemporal normalized ratio methodology to evaluate the impact of field-scale variable rate application

Wide assimilation of precision agriculture among farmers is currently dependent on the ability to demonstrate its efficiency at the field-scale. Yet, most experiments that compare variable-rate vs uniform application (VRA and UA) are performed in strips, concentrated in a small portion of the field with limited extrapolation to the field scale. A spatiotemporal normalized ratio (STNR) methodology is proposed to evaluate the impact of VRA compared with UA for on-farm trials at the field scale. It incorporates a base year in which the whole plot is managed with UA and consecutive years in which half of the plot is managed with UA and the other half is managed with VRA. Additionally, a novel normalized relative comparison index (NRCI) is presented where the ratios of VRA/UA sub-plots are compared between a base year and a consecutive year, for any measured parameter. The NRCI determines the impact of VRA on variability using statistical measures of dispersion (variability measures) and on performance with statistical measures of central tendency (performance measures). Variability measures with NRCI values lower or higher than 1 indicate VRA management decreased or increased variability. Performance measures with NRCI lower or higher than 1 indicate subplot impairment or improvement, respectively due to VRA management. The methodology was demonstrated on a commercial drip irrigated peach orchard and a wine grape vineyard. NRCI results showed that VRA drip irrigation reduced water status in-field variability but did not necessarily increase yield. The benefits and limitations of the proposed design are discussed.