Hyperspectral Sensing of Plant Diseases: Principle and Methods

Abstract

Pathogen infection has greatly reduced crop production. As the symptoms of diseases usually appear when the plants are infected severely, rapid identification approaches are required to monitor plant diseases at early the infection stage and optimize control strategies. Hyperspectral imaging, as a fast and nondestructive sensing technology, has achieved remarkable results in plant disease identification. Various models have been developed for disease identification in different plants such as arable crops, vegetables, fruit trees, etc. In these models, important algorithms, such as the vegetation index and machine learning classification and methods have played significant roles in the detection and early warning of disease. In this paper, the principle of hyperspectral imaging technology and common spectral characteristics of plant disease symptoms are discussed. We reviewed the impact mechanism of pathogen infection on the photo response and spectrum features of the plants, the data processing tools and algorithms of the hyperspectral information of pathogen-infected plants, and the application prospect of hyperspectral imaging technology for the identification of plant diseases.

A Comprehensive Review of Scab Disease Detection on Rosaceae Family Fruits via UAV Imagery

“…They have used this technology for fighting locust attacks. South Africa is adopting smart agriculture not only to expand production but also to contribute to the environment by cutting costs and saving resources [12]. Researchers in China and Japan are employing UAVs, satellites, and AI techniques to formulate such strategies that will diagnose the disease before it becomes visible [26].…”

“…The study in [12] reviews the previous work of numerous authors who describe the use of hyperspectral imaging to detect Scab and other diseases. The findings show that using UAVs, preprocessing of hyperspectral images, vegetation index, ML, and DL methods provide efficient results for disease detection.…”

“…Different countries are using them for field mapping, disease detection, crop spraying, livestock monitoring, smart greenhouse, temporal, and[12,[22][23][24][25] …”

Localization and recognition of specific targets in land-based hyperspectral images based on combined spatial and spectral information

“…Therefore, the traditional hyperspectral imaging technology is also called hyperspectral remote sensing technology, and the hyperspectral images obtained based on the remote sensing platform are called hyperspectral remote sensing images. Because hyperspectral images contain rich spatial and spectral information, hyperspectral imaging has unique advantages in classification and detection of ground objects, and is widely used in agriculture, medicine, military and other fields [2][3][4][5][6][7]. In recent years, with the development of landbased imaging platforms and the continuous improvement of miniaturization and intelligence of imaging spectrometers, scholars have gradually attached importance to the study of land-based hyperspectral images [8].…”

STLAR: A localization and authenticity recognition method for specific targets based on land‐based hyperspectral images

“…Introduction: Hyperspectral images contain rich spatial and spectral information, which gives hyperspectral imaging unique advantages in the classification and detection of ground objects. Hyperspectral imaging is widely used in agriculture, medicine, military and other fields [1][2][3][4]. In recent years, with the development of land-based imaging platforms and the continuous improvement of imaging spectrometers, scholars have gradually attached importance to the study of land-based hyperspectral images [5].…”