Journal
FOOD CHEMISTRY
Volume 366, Issue -, Pages -Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.foodchem.2021.130595
Keywords
GMO; Lateral flow stirp; SERS; Simultaneous multiple screening; Food safety; Food labeling; Raman decoding
Funding
- key R&D program of Anhui [201904d07020016]
- Anhui Provincial NSF [1908085QC121]
- MOST of China [2018YFC1603606]
- Fundamental Research Fund for central university [JZ2019HGTB0068, PA2017GDQT0018]
- China Postdoctoral Science Foundation [2019M652167]
- Fund of State Key Lab of Chemo/Bio-sensing and Chemometrics (Hunan University)
- Young and Middle-aged Leading Scientists, Engineers and Innovators of the XPCC [2019CB017]
- Intelligent Manufacturing Institute of HFUT [IMICZ2019007]
- postdoc grant of Anhui [2020B412]
- China Agriculture Research System-48 (CARS-48)
Ask authors/readers for more resources
This study developed a surface-enhanced Raman scattering (SERS)-integrated LFS platform for rapid screening of multiple genetically modified organism (GMO) components in soybean. The platform showed good linear correlations and high sensitivity for quantitative analysis of GMO components, providing a promising alternative for multiple screening of GMO identification in food.
Herein, a surface-enhanced Raman scattering (SERS)-integrated LFS platform was developed for rapid and simultaneous screening of multiple genetically modified organism (GMO) components (promoter, codon, and terminator) in soybean. Research demonstrated that, on the same test line (T line) of single LFS, three different GMP components can be well distinguished with the help of three SERS nano tags. Good linear correlations between SERS signal and concentration of each GMO component were also obtained for quantitative analysis. Of greater importance, whether these multiple analytes coexisted or not, varied in the same concentration trend or not, these multiple GMP components can be rapidly (15 min) and accurately screened with satisfied sensitivity and specificity by decoding the signals on the same T line. We envision that this decoding platform can further improve the potential of LFS and SERS for practical applications and provide a promising alternative for multiple screening of GMO identification in food.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available