Journal
FOOD CHEMISTRY
Volume 382, Issue -, Pages -Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.foodchem.2022.132237
Keywords
2DC-SERS; Food quality; Nitrification; Protein; DD-SIMCA
Funding
- National Key Research and Develop-ment Program of China [2019YFC1605900]
- National Nature Science Foundation of China [21922403, 21874034]
- Key Research and Devel-opment Project of Anhui Province [202104a07020013]
- Nature Science Research Project of Anhui Province [2108085QB84]
- Funda-mental Research Funds for the Central Universities [PA2020GDJQ0030, JZ2021HGTA0171, JZ2021HGQA0243]
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In-situ tracking of protein residue structural changes using two-dimensional correlation surface-enhanced Raman spectroscopy (2DC-SERS) allows for reliable discrimination between natural and artificially dyed edible bird's nest. A conceptual logical circuit using protein structure indicator and nitrite indicator enables automatic recognition of different bird's nest samples.
In-situ tracking structural changes of protein residues was developed by two-dimensional correlation surface-enhanced Raman spectroscopy (2DC-SERS). The change order of SERS fingerprints during artificial nitrifica-tion of edible bird's nest (EBN) was interpreted as the structural changes of amino acid residues. It inherently realizes reliable recognition of natural EBN and artificially dyed fakes. Both this direct structural tracking of protein residues and the indirect azo dye testing of nitrites/nitrosamines could be used as indicators for discriminating different EBN before and after the artificial dyeing. Limit of detection (LOD) for nitrite and NDMA is about 40.6 ppb and 88.1 ppb, respectively. A conceptual logical circuit of the OR gate was constructed by considering the protein structural indicator (INPUT1) and the nitrite indicator (INPUT2) as two independent inputs for automatic recognition of different EBN samples. A data-driven analog soft independent modeling (DD-SIMCA) model could quickly distinguish normal EBN from A-EBN with 98% specificity.
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