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Sericulture is a traditional Chinese industry that integrates economic, cultural, and ecological values. The silkworm has a weakened immune system and is reared in high-density conditions, making it highly susceptible to pathogen infections. Therefore, rapid, accurate, and cost-effective pathogen detection methods are critical for disease prevention and control in sericulture production. This review summarizes various pathogen detection techniques, including traditional microscopy, molecular diagnostics, immunoassays, and artificial intelligence-based image recognition, highlighting their advantages and characteristics. Special attention is placed on pathogen detection methods based on the Regularly Interspaced Short Palindromic Repeat (CRISPR)/Cas system. This method has achieved a detection limit as low as 1 fg/μL for Bombyx mori nucleopolyhedrovirus genomic DNA, demonstrating a 100-fold increase in sensitivity compared to conventional PCR and significantly improving detection efficiency. The aim of this review is to provide theoretical insights and technical references for the innovation of early diagnostic technologies for silkworm pathogens and the development of an efficient industrial prevention and control system.
This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
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