Detection of huanglongbing of citruses (Citrus sp.) through Sentinel-2satellite images in Huimanguillo, Tabasco, Mexico

Resumen

Objective: Develop a fast, practical, and inexpensive methodology for determining plants with HLB symptoms by exploring the potential use of Sentinel-2 satellite images.

Design/Methodology/Approach: Sentinel-2 images were used to perform a supervised classification to discriminate healthy Persian lime trees and trees with HLB molecularly verified by qPCR, and other land uses in the citrus growing area of Huimanguillo, Tabasco.

Results: The results showed that in the green (560nm), red (665 nm), and near-infrared (705 nm) band regions, the spectral response of trees with HLB is higher than that of healthy trees. Likewise, there is an area of 26.96 and 12 981 hectares of Persian lime affected and free of HLB, respectively, with an accuracy of 0.84 % and a Kappa coefficient of 0.83. Field verification corroborated three plantations where plants with HLB were previously detected and are currently in production.

Study Limitations/Implications: The study was carried out in the season of less cloud cover, as this is a limiting factor for the image analysis since it can lead to inadequate tracking of the affected area.

Findings/Conclusions: The results showed that it is possible to differentiate Persian lime plants affected by HLB from healthy plants using Sentinel-2 satellite images