Utilization of UAV Remote Sensing in Plant-Based Field Experiments: A Case Study of the Evaluation of LAI in a Small-Scale Sweetcorn Experiment

In crop production, which is largely dependent on environmental conditions, various attempts at environmental or social changes have been highlighted, and many field experiments are needed for them. However, since field experiments in agricultural production are constrained by high labor and time consumption, alternative methods to respond to these constraints are required. In this study, to establish a new method for application to field experiments, we proposed the evaluation of the leaf area index (LAI) of all individual plants in an experimental sweetcorn field using an unmanned aerial vehicle (UAV). Small-scale field experiments were conducted over two years. In the first year, the nitrogen fertilizer level was changed, and the plant density and additional nitrogen fertilizer application time were changed in the next year. Three vegetation indices (VIs), namely, the normalized difference vegetation index (NDVI), enhanced vegetation index 2 (EVI2), and simple ratio (SR), were validated to quantify the LAI estimation using a UAV for individual plants. For the evaluation of the individual plants, we used a plant-based method, which created all of the plant buffers based on the points of existing plants and the plant distance. To confirm the impact of the method, we additionally demonstrated the relationship between the LAI and yield, the results of statical analyses, and the difference of the center and the border of the field. Among the three VIs, index SR was found the most promising in the estimation of the LAI of the individual sweetcorn plants, providing the strongest correlation of yield with SR. Because a lot of data were obtained using the plant-based method, the statical differences in the LAI and yield were more easily detected for the plant density and fertilizer treatments. Furthermore, interesting differences between the center and the border of the field were found. These results indicate the availability and impact of plant-based evaluations using UAVs in near future field experiments.