FOOD SCIENCE ›› 2019, Vol. 40 ›› Issue (14): 346-351.doi: 10.7506/spkx1002-6630-20180606-057

• Safety Detection • Previous Articles    

Quantitative Detection of Apricot Kernel-derived and Peanut-derived Components in Apricot Kernel Protein Drink by Droplet Digital PCR

GUO Nannan, ZHANG Yan, LI Yongbo, ZHANG Tao, ZHANG Yalun, ZHOU Wei, WANG Hong   

  1. 1. College of Life Science, Hebei Normal University, Shijiazhuang 050024, China; 2. Hebei Food Safety Key Laboratory, Hebei Food Inspection and Research Institute, Shijiazhuang 050071, China
  • Online:2019-07-25 Published:2019-07-23

Abstract: An accurate method to quantitatively analyze the contents of apricot kernel-derived and peanut-derived components in apricot kernel protein drink products was established based on droplet digital polymerase chain reaction (ddPCR) in this study. We established a linear relationship between plant material mass (M) and DNA copy number (C) after the extraction of nucleic acids from both apricot kernels and peanuts. According to the results of ddPCR, we found that the relationships between the mass of each plant material and DNA concentration and between DNA concentration and DNA copy number were both significantly linear within a certain range. The DNA concentration was utilized as an intermediate value to establish the following formulae: Mapricot kernel = 0.13C + 1.24, Mpeanut = 0.081C ? 0.63. The accuracy and applicability of this method were tested and verified using known mixtures of apricot kernel and peanut and 12 commercial apricot protein drink products. This method enabled accurate and reliable quantitative analysis, and effective identification of whether the adulteration in apricot kernel protein drink products is inadvertent or intentional. Hence ddPCR has strong potential in quantifying apricot kernel and peanut in apricot kernel protein drink products and provides technical support for market supervision of plant protein drink products.

Key words: droplet digital PCR, apricot kernel protein drink, apricot kernel, peanut, quantitative analysis

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