Bud rot evaluation in oil palm (Elaeis guineensis Jacq.) using multispectral imaging, Costa Rica - Alemán-Montes, Bryan (2022)
Introduction. The use of remote sensing to identify the different plant health conditions, and its relationship with crop yield, constitutes a very important tool in the implementation of Precision Agriculture. Objective. To relate the phytosanitary status, obtained by experts through visual assessment, of oil palm (Elaeis guineensis Jacq.) plants affected by bud rot (BR), with the vegetation indices calculated with multispectral images obtained with an unmanned aerial vehicle (UAV). Materials and methods. The study was conducted in a four-hectare plantation with oil palm three-year-old, owned by CoopeCalifornia R.L., located in Parrita, Costa Rica. Four visual assessments of the BR state were conducted from December 2014 to February 2017. With these assessments, the spatial-temporal evaluation of the incidence of BR during 26 months was obtained. In the last evaluation, a flight was performed with a UAV carrying a Parrot Sequoia multispectral camera, with which vegetation indexes were calculated and then related to the BR status of the oil palm plants. Results. A high spatial and temporal variability of BR was found during all visual evaluations performed. A strong relationship was also found between data from field assessments and data generated from remote sensing. The Simple Ratio (SR) vegetation index showed significant differences between plants classified as healthy and plants classified with BR, with degrees 2 and 3 of severity. Conclusions. Field data, obtained through expert judgment, can be linked to high spatial resolution multispectral information to identify BR in commercial oil palm plantations.