Droplet Digital Polymerase Chain Reaction Assay for Quantifying Salmonella in Meat Samples

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Authors: yingying liang, Yangtai Liu, X. Liu, Jin Ding, Tianqi Shi, Qingli Dong, Min Chen, Huanyu Wu, Hongzhi Zhang
Cited by: 4
References: 37

Abstract

Salmonella, a major global foodborne pathogen, is a leading cause of salmonellosis. Quantitative detection of Salmonella provides a scientific basis for establishing microbiological criteria and conducting risk assessments. The plate count method remains the primary approach for bacterial quantification, whereas the most probable number (MPN) method is commonly used for detecting low levels of bacterial contamination. However, both methods are time-consuming and labor-intensive. Validated digital polymerase chain reaction (dPCR) techniques are emerging as promising alternatives because they enable rapid, absolute quantification with high specificity and sensitivity. Herein, we developed a novel droplet dPCR (ddPCR) assay for identifying and quantifying Salmonella using invA as the target. The assay demonstrated high specificity and sensitivity, with a limit of quantification of 1.1 × 102 colony-forming units/mL in meat samples. Furthermore, the log10 values obtained via ddPCR and plate counting exhibited a strong linear relationship (R2 > 0.99). Mathematical modeling of growth kinetics further confirmed a high correlation between plate count and ddPCR measurements (Pearson correlation coefficient: 0.996; calculated bias factor: 0.88). Collectively, these results indicate that ddPCR is a viable alternative to the MPN method and represents a powerful tool for the quantitative risk assessment of food safety.

Fields of Study & Subjects

Biosensors and Analytical Detection Vibrio bacteria research studies Listeria monocytogenes in Food Safety

Publication details

Journal / source
Foods
Publisher
MDPI AG
Volume
15
Issue
2
Pages
337–337
Publication date
16 January 2026
Language
EN