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Author ORCID Identifier

https://orcid.org/0000-0003-0836-5541

Document Type

Open Access Dissertation

Degree Name

Doctor of Philosophy (PhD)

Degree Program

Food Science

Year Degree Awarded

2019

Month Degree Awarded

September

First Advisor

Dr. Lili He

Second Advisor

Dr. Eric Decker

Third Advisor

Dr. Ryan Hayward

Subject Categories

Food Chemistry

Abstract

Surface-enhanced Raman spectroscopy, short for SERS, is an emerging technology with great potential in food analysis due to rapid detection, high sensitivity, portable instrumentation, and simple sample preparation. However, it is always a bottleneck to obtain reproducible SERS measurements in real analytical cases due to the complicity of food systems and inhomogeneous aggregation of colloidal nanoparticles. To improve its performance for practical applications in food analysis, efforts have been made in improving the reproducibility, enhancing the selectivity and reducing the matrix interference to the analyte. Herein, a self-assembly silver nanoparticles mirror substrate was fabricated to improve the and the quantitative ability and effectiveness of sample preparation for different applications in food analysis, including pesticides detection in beverages, chemical profiling of red wines, and headspace analysis of garlic. The AgNPs mirror was fabricated using the interface between polar and non-polar solvents and showed a uniform arrangement of nanoparticles under the microscope. It demonstrated a great reliability for the detection of a pesticide fonofos in beverages (i.e., apple juice and green tea). AgNPs mirror can also be in situ fabricated in red wines to generate a comprehensive spectrum constituted by signals of five wine phytochemicals, which provided a great potential of SERS in the differentiation, authentication, and quality/safety control of red wines. AgNPs mirror also showed great potential in the headspace characterization of aromatic compounds from Allium species plants. Additionally, a facile rolling method was developed to enrich analyte (i.e., chlordane pesticide) and to amplify its weak SERS activity and a mathematic model was generated and successfully quantified the chlordane in a complicated crude oil sample with a very good recovery. Overall, AgNPs mirror and the rolling method overcame the reproducibility and sensitivity problems for SERS in several challenging food matrices. With these improvements, SERS can be much more reliable for analytical applications and its range of targets can be widely expanded.

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