Advances in insect detection and identification technologies —morphological identification, molecular detection, and multimodal intelligent recognition
Author of the article:ZHANG Liu1 GE Yang2 CHEN Ke1 LI Hong-Wei1 YU Yan-Xue1
Author's Workplace：1. Institute of Plant Safety and Quality, Chinese Academy of Quality and Inspection & Testing, Beijing 100176, China; 2. State Key Laboratory Breeding Base of Dao-di Herbs, National Resource Center for Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing 100700, China
Key Words：insects; image recognition; molecular identification; biomimetic olfactory detection technology; acoustic detection technology; artificial intelligence
Abstract：Accurate species identification serves as the foundation for pest monitoring and management, as well as for the development and utilization of biological resources. It is particularly critical for the early warning and precise control of insect pests. This review systematically summarizes current progress in research on insect detection and identification technology, from classical morphological identification and molecular biological detection, to the paradigm evolution of multimodal intelligent recognition based on image, odor and acoustic information. Traditional morphological identification constitutes the cornerstone of the entire technical chain, providing a taxonomic benchmark for the specific collection of subsequent genetic, image, chemical and acoustic signals. Accurate, portable, and rapid, detection and identification methods have become a key focus of research and development. In practical applications, the inherent limitations of single-modal detection techniques make it difficult to meet the demands of efficient prevention and control, thus giving rise to the path of multi technology integration. Future research should focus on establishing multimodal standardized databases, developing portable field equipment, and improving the interpretability of fusion algorithms. These advances are expected to produce efficient, accurate, and deployable, intelligent identification systems, thereby providing essential technical support for curbing the spread of major pests and improving the precision of management strategies.