Maui: modular analytics of UAS imagery for specialty crop research

Abstract Background: Imaging sensors (e.g., multispectral cameras) mounted on unmanned aerial systems (UAS) have emerged as a powerful tool for deriving insights about agricultural fields, from plant morphology phenotyping to plant disease monitoring. Advances in computer vision-based image analysis have enabled researchers to rapidly and accurately isolate crop spectra in UAS images. Specialty crops often employ unique production styles, such as trellising or inter-cropping. This presents a barrier to using existing image processing methodologies developed for broad-acre, row cropped systems