An effective analytical droplet digital PCR approach for identification and quantification of fur-bearing animal meat in raw and processed food. (1st September 2021)

• Record Type: Journal Article
• Authors: Yu, Ning; Ren, Junan; Huang, Wensheng; Xing, Ranran; Deng, Tingting; Chen, Ying
• Is Part Of: Food chemistry. Volume 355(2021)
• Publication Date: 2021-09-01
• Subjects: Identification -- Quantification -- Droplet digital PCR -- Fur-bearing animal meat; Food -- Analysis -- Periodicals; Food -- Composition -- Periodicals; 664
• DOI: 10.1016/j.foodchem.2021.129525
• Languages: English
• ISSNs: 0308-8146

Abstract

Graphical abstract: Highlights: DdPCR assay is established and optimized for fur-bearing animal meat quantification. Single copy nuclear gene was selected for meat quantification. Internal control strategy was applied to transform the copy ratio to weight. The ddPCR method is sensitive and accurate even with additives in meat. Abstract: Available nuclear gene sequences for meat detection are still rare and little applicability in the investigation of new types of meat adulteration such as fox, mink and raccoon dog was performed. In the present work, we developed a reliable qualitative and quantitative detection method for fur-bearing animal meat based on droplet digital PCR (ddPCR). Three sets of primers and probes targeted nuclear genes for fox, mink and raccoon dog were designed for ddPCR system; In addition, turkey was selected as internal reference to transform the copy numbers to the fraction of target species. Results indicated that the dynamic ranges of three fur-bearing animals were all from 1% to 90%; the limit of detection (LOD) and limit of quantification (LOQ) for three fur-bearing animals were same, with LOD 0.1% (w/w) and LOQ 1% (w/w). Moreover, we confirmed that different additives had no effect on quantification accuracy in the ddPCR assay.