Calculating Intra-Row Plant Spacing Metrics from Unmanned Aerial Vehicle Imagery.

Intra-row plant spacing metrics (i.e., mean and standard deviation of plant-to-plant distance) for major fields crops [e.g., maize (Zea mays L.), sorghum (Sorghum bicolor (L.) Moench)] provide insights into field and research plot quality, agronomic explanations for observed crop responses, and feedback on field equipment performance. Such information is highly useful to the crop production, agronomic research, and plant breeding communities. A variety of public- and private-sector groups collect intra-row plant spacing data using traditional methods (e.g., direct measurement of plant-to-plant distances using linear measurement tools and field work crews). These techniques are often laborious, slow, costly, and error-prone. In this presentation, our inter-disciplinary research team will highlight how a properly-operated unmanned aerial vehicle (UAV); a relatively low-cost, high-quality RGB sensor; and advanced image processing techniques can be used to determine intra-row plant spacing information in sorghum in a relatively high-throughput and accurate manner. Expansion of this technique to other crops, potential research and commercial impacts of this methodology, and future areas of research will be briefly discussed.