Use of unmanned aerial vehicle extracted data to predict health and tiller count in wheat

摘要

Wheat, third most important cereal in the world, is sensitive to nitrogen deficiency. To increase yield, nitrogen (N) inputsare used but production costs may exceed returns if unnecessary applications are made; and the environment maybecome polluted. To improve N management, farmers of the mid-Atlantic generally apply N to wheat based on actualplant growth by counting the number of tillers or N concentration in the plant tissues. Both methods can be laborintensive and time consuming, and tissue testing also requires additional production costs. Remote-sensing technologiesand more particularly Unmanned Aerial Vehicle (UAV) systems are now being used to extract new variables (spectralreflectance and vegetation indices) and to estimate plant growth and N requirements. Previous studies in Virginia haveshown that spectral reflectance data, collected using the ground GreenSeeker? system, could be used to estimate thenumber of tillers and tissue nitrogen content. The objective of this project was to evaluate the accuracy of remote sensingand UAV-based wheat spectral reflectance for estimating tiller density in winter wheat. Tillers were counted regularlyand simultaneously with ground (using handheld GreenSeeker?) and aerial (using UAV) NDVI measurements. EachUAV flight was performed using a Red Green Blue (RGB) and Tetracam (Near InfraRed) camera to extract NDVI andcolor space indices. Our results showed significant correlations between the number of tillers and aerial indices butfurther analysis is needed to identify the best flight time for estimating wheat tiller density and early season Nrequirements.