Application of environmental DNA technology for monitoring agricultural and forestry pests

Author of the article:LONG Shu-Ting1, 2** ZHANG Yi-Fei1, 2*** LIU Yu-Fang2 PAN Ben-Shan1, 2 ZOU Qi-Hui1, 2

Author's Workplace：1. Sanya Institute of Hunan University of Science and Technology, Sanya 572024, China; 2. School of Life Science and Health, Hunan University of Science and Technology, Xiangtan 411201, China

Key Words：terrestrial pests; environmental DNA (eDNA); agricultural and forestry pest monitoring; digital PCR; early warning

Abstract：Early detection and precise monitoring of agricultural and forestry insect pests are fundamental for food security and ecosystem health. Conventional surveillance methods are often constrained by limited sensitivity for low-density populations, high operational costs, and heavy reliance on experts in morphological species identification. Environmental DNA (eDNA) technology enables the non-invasive detection of target organisms by extracting trace genetic material from various environmental substrates, including water, soil, air and plant surfaces. As an emerging molecular tool, eDNA has demonstrated considerable potential for the early detection of invasive pests, surveillance of cryptic and low-abundance populations, and tracking of migratory insect dynamics. This review synthesizes recent global advances in terrestrial eDNA research for agricultural and forestry pests. We systematically analyze eDNA release and degradation mechanisms, sampling strategies, species-specific assay development, and core detection technologies, including quantitative PCR (qPCR) and droplet digital PCR (ddPCR). Furthermore, statistical approaches (such as occupancy models) are summarized alongside representative applications in the surveillance of agricultural, forest, stored-product and invasive, insect pests. Although eDNA-based approaches substantially improve the sensitivity of detection, their widespread implementation in terrestrial ecosystems is hindered by rapid DNA degradation, pronounced spatial heterogeneity, lack of standardized protocols, incomplete reference databases, and challenges in quantitative interpretation. Future research should prioritize establishing standardized multi-substrate sampling frameworks, expanding DNA barcode reference databases for major economic pests, developing airborne eDNA continuous monitoring and portable field-deployable detection platforms, and integrating artificial intelligence-assisted risk assessment. Advancing these frontiers will contribute to a robust theoretical framework for terrestrial arthropod eDNA monitoring, facilitating its application in precision pest management and agricultural biosecurity.