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Identification and quantification of cassava starch adulteration in different food starches by droplet digital PCR
Jia Chen1, Yalun Zhang2, Chen Chen2
1College of Food Science and Technology, Hebei Agricultural University, Baoding, Hebei, China.
Abstract:
We report a rapid and accurate quantitative detection method using droplet digital PCR (ddPCR) technology to identify cassava adulteration in starch products. The ddPCR analysis showed that the weight of cassava (M) and cassava-extracted DNA content had a significant linear relationship-the correlation coefficient was R2 = 0.995, and the maximum coefficient of variation of replicates was 7.48%. The DNA content and DNA copy number (C) measured by ddPCR also had a linear relationship with R2 = 0.992; the maximum coefficient of variation of replicates was 8.85%. The range of cassava ddPCR DNA content was 25 ng/μL, and the formula M = (C + 32.409)/350.579 was obtained by converting DNA content into the median signal. The accuracy and application potential of the method were verified using the constructed adulteration model.

