A Review of On‐Site Detection Methods for Plant Health Based on Electrical Characteristics

Recent developments in IoT technology provide new solutions for field‐based monitoring of plant health. Among the many rapid detection techniques applied to the perception layer of IoT, electrical feature‐based detection technology stands out due to its distinct advantages such as low cost, ability to extract internal plant information, and immunity to external light sources. This article provides an overview of on‐site detection methods for plant health based on electrical features. Basic experimental and research methods for plant health detection are presented in the dimensions of sample collection and preprocessing, electrical feature extraction, and data processing. The article then classifies and elaborates on these methods based on four key research subjects: plant ontology, symbiotic bacteria, pathogens, and the microenvironment. For each subject, it introduces the underlying detection principles, traces technological developments, and analyzes the current state of applications, major scientific challenges, and prevailing research hotspots. This article aims to integrate research results from various fields from the perspective of plant health detection, extract research results with inherent correlations from different disciplines such as agriculture, food, environment, detection, and data analysis, and connect them through the development of electrical detection technology, providing interdisciplinary references and perspectives for researchers in this field.