Identification and quantification of cassava starch adulteration in different food starches by droplet digital PCR.

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 correlat...

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Main Authors: Jia Chen, Yalun Zhang, Chen Chen, Yan Zhang, Wei Zhou, Yaxin Sang
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2020-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0228624
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spelling doaj-135ba8686ca44e1db95c8a06f5bfa03d2021-03-03T21:28:54ZengPublic Library of Science (PLoS)PLoS ONE1932-62032020-01-01152e022862410.1371/journal.pone.0228624Identification and quantification of cassava starch adulteration in different food starches by droplet digital PCR.Jia ChenYalun ZhangChen ChenYan ZhangWei ZhouYaxin SangWe 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.https://doi.org/10.1371/journal.pone.0228624
collection DOAJ
language English
format Article
sources DOAJ
author Jia Chen
Yalun Zhang
Chen Chen
Yan Zhang
Wei Zhou
Yaxin Sang
spellingShingle Jia Chen
Yalun Zhang
Chen Chen
Yan Zhang
Wei Zhou
Yaxin Sang
Identification and quantification of cassava starch adulteration in different food starches by droplet digital PCR.
PLoS ONE
author_facet Jia Chen
Yalun Zhang
Chen Chen
Yan Zhang
Wei Zhou
Yaxin Sang
author_sort Jia Chen
title Identification and quantification of cassava starch adulteration in different food starches by droplet digital PCR.
title_short Identification and quantification of cassava starch adulteration in different food starches by droplet digital PCR.
title_full Identification and quantification of cassava starch adulteration in different food starches by droplet digital PCR.
title_fullStr Identification and quantification of cassava starch adulteration in different food starches by droplet digital PCR.
title_full_unstemmed Identification and quantification of cassava starch adulteration in different food starches by droplet digital PCR.
title_sort identification and quantification of cassava starch adulteration in different food starches by droplet digital pcr.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2020-01-01
description 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.
url https://doi.org/10.1371/journal.pone.0228624
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