ArticlePloS one2020
Identification and quantification of cassava starch adulteration in different food starches by droplet digital PCR.
Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 13 citations in OpenAlex.
- Research on quantitative detection technology of raccoon-derived ingredient adulteration in sausage products.Food science & nutrition · 2024Article
- CRISPR/Cas9-gene editing approaches in plant breeding.GM crops & food · 2023Review
- DNA Accounting: Tallying Genomes to Detect Adulterated Saffron.Foods (Basel, Switzerland) · 2021Article
- Digital PCR: What Relevance to Plant Studies?Biology · 2020Review
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
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.
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