Literature DB >> 32932080

A novel duplex SYBR Green real-time PCR with melting curve analysis method for beef adulteration detection.

Jiapeng Li1, Yixuan Wei1, Jinchun Li1, Ruixi Liu1, Suigen Xu1, Suyue Xiong1, Ya Guo1, Xiaoling Qiao1, Shouwei Wang2.   

Abstract

An efficient and reliable duplex SYBR Green real-time quantitative PCR (qPCR) method for beef products adulteration detection was developed based on bovine specific and vertebrate universal primers. By analyzing the numbers, positions (Tm value) of melting curve peaks of the duplex PCR products, we simultaneously identified bovine and preliminary screened non-bovine in samples, and also semi-quantified the bovine percentage according to the area ratios of peaks. All of these were necessary for adulteration determination. The specific and universal primers were designed based on mitochondrial genes ND4 and 16S rRNA respectively, their amplicons Tm values were 72.6 ± 0.5 °C and 79-81 °C. There might be some other peaks at 74-78 °C and above 81 °C if non-bovine components existed. Thelimit of detectionwas 1 pgforbovineDNA, and1 - 30 pg fornon-bovineDNAbasedon differentspecies.
Copyright © 2020 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Authenticity test; Beef products; Duplex qPCR; Food adulteration; Food authenticity; Melting curve analysis

Mesh:

Substances:

Year:  2020        PMID: 32932080     DOI: 10.1016/j.foodchem.2020.127932

Source DB:  PubMed          Journal:  Food Chem        ISSN: 0308-8146            Impact factor:   7.514


  2 in total

1.  A Machine Learning Method for the Quantitative Detection of Adulterated Meat Using a MOS-Based E-Nose.

Authors:  Changquan Huang; Yu Gu
Journal:  Foods       Date:  2022-02-20

2.  A Simple and Reliable Single Tube Septuple PCR Assay for Simultaneous Identification of Seven Meat Species.

Authors:  Zhendong Cai; Song Zhou; Qianqian Liu; Hui Ma; Xinyi Yuan; Jiaqi Gao; Jinxuan Cao; Daodong Pan
Journal:  Foods       Date:  2021-05-13
  2 in total

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