Dataset of date palm tree (Phoenix dactylifera L.) thermal images and their classification based on Red Palm Weevil (Rhynchophorus ferrugineus) infestation - Nadeem, Adnan; Ashraf, Muhammad; Mehmood, Amir; Rizwan, Kashif; Siddiqui, Muhammad Shoaib (Frontiers in Agronomy, 2025)
The primary objective of this article is to present a comprehensive dataset for controlling and monitoring red palm weevil (RPW) (Rhynchophorus ferrugineus) infestation. For this purpose, several digital and thermal images of date palm trees (Phoenix dactylifera L.) have been captured from various date palm groves in Khairpur, Sindh, Pakistan. Each image in the dataset is annotated with the farmers’ feedback regarding the health status of the corresponding tree, categorizing it as non-infected, infected, badly damaged, or dead. This dataset aims to facilitate (1) RPW pest management and (2) the development and evaluation of machine learning algorithms for automated date palm tree classification by providing a diverse collection of images and groundtruth labels. It contains 832 images (RGB and thermal) collected through the onground survey in date palm fields, which are classified based on visual inspection and the farmers’ feedback. A neural network-based thermal analysis is made, which validates the initial classification. The dataset shows promising potential for further studies, supporting a wide range of research topics extending the body of knowledge. It is valuable for researchers, industry professionals, public authorities, and others interested in harvesting date palm trees.