The overuse of antibiotics in food production systems has exacerbated antibiotic resistance in foodborne pathogens, creating significant risks to public health and food safety. This situation makes it imperative to develop practical monitoring tools for tracking antibiotic resistance in foodborne pathogens. However, most existing detection technologies still rely on manual operation and are time-consuming and operationally complex. This prevents them from being used for immediate on-site testing along the food processing chain. Phenotypic detection establishes the functional expression of antibiotic resistance, while genotypic detection elucidates its genetic basis. Through complementary functional validation and mechanism analysis, both approaches collectively provide indispensable evidence for the precise and comprehensive assessment of antibiotic resistance. This review aims to provide concrete solutions for rapid detection by systematically integrating genotypic and phenotypic strategies, while clarifying future research directions for antibiotic resistance detection approaches. This review systematically discusses the diversity of antibiotic resistance, analyzes the advantages and limitations of traditional detection methods, and elaborates in detail on various rapid detection techniques for antibiotic resistance based on genotypes and phenotypes. This review finally summarizes the development trends of emerging technologies and proposes improvement suggestions. Future antibiotic resistance detection technologies will focus on simultaneous analysis of genotypes and phenotypes and move toward fully automated, intelligent, integrated analysis. Ultimately, this review provides robust safeguards for food safety and helps establish a secure, controllable food processing chain. • ●The diversity of antibiotic resistance in foodborne pathogens was reviewed. • ●The relation between antibiotic resistance genotypes and phenotypes was revealed. • ●The advantages and limitations of traditional detection methods were analyzed. • ●Rapid detection strategies for antibiotic resistance were discussed. • ●Prospective trends for the rapid detection of antibiotic resistance are proposed.
He et al. (2026) studied this question.