Optimal flight height and spectral indices for detecting insect injury in peanut crops using UAS

Abstract

Despite technological advances in agriculture in recent decades, it has been estimated that about 20–30% of peanut production costs are still associated with pest and disease control, due in large part to the unnecessary use of insecticides without proper sampling, a core principle of Integrated Pest Management (IPM). However, technologies like Remote Sensing can be leveraged to provide time savings and speed in detecting injured plants. Therefore, this study aimed to determine the appropriate flight height and geometric resolution to differentiate healthy peanut plants from those injured by Enneothrips enigmaticus and Stegasta bosqueella using unmanned aircraft systems (UAS). To achieve this, controlled and field studies were conducted using the Parrot Sequoia® multispectral sensor. Five vegetation indices (IRVI, NDVI, NDRE, GRVI, and GCI) were generated and statistically compared between infestation treatments. We observed that remote sensing with UAS can only be used to detect insect-induced injuries in peanut crops at 80 and 120 m flight heights. Additionally, only the IRVI, NDVI, and GRVI indices were effective in characterizing infestations. Our study provides valuable new information that will serve as a foundation for using remote sensing to detect insect infestation injuries in peanut crops.