Unmanned Aerial Vehicle (UAV) for High Throughput Phenotyping of Sorghum Crop.

The use of Unmanned Aerial Vehicle (UAV) for agriculture applications has been raised over the last decade because of their potential to be a low-cost, accessible, and practical substitute for satellite and aircraft for acquiring high temporal and spatial resolution remotely sensed data.

A fixed-wing unmanned aerial system equipped with a multispectral sensor (Rededge, Micasense Systems) was used to acquire very high spatial resolution images for evaluating sorghum (Sorghum bicolor L) crop growth and yield. The UAV was flown over a test field in which six sorghum hybrids were grown in three seeding rates and in three replications. We conducted ground sampling for plant leaf area index (LAI) and fractional ground cover (f_c) at the same time of UAV flights. Based on the aerial photographs, different vegetation indices (VIs) were calculated, and used to estimate leaf area index (LAI) and fractional vegetation cover (f_c).

The results show that UAV based VIs are highly correlated with LAI and f_c. These results indicate the potential of low-cost effective UAV images in crop growth assessment during growing season