Antioxidants in Coffee: An Exercise Using HPLC with Post-column Derivatization and Statistical Analysis

被引:3
|
作者
Stathakis, Jonathan G. H. [1 ,2 ]
Cravino, Jake A. [1 ,2 ]
Shalliker, Ross Andrew [1 ,2 ]
机构
[1] Western Sydney Univ, Sch Sci, South Parramatta, NSW 2150, Australia
[2] Western Sydney Univ, Australian Ctr Res Separat Sci, Sch Sci, South Parramatta, NSW 2150, Australia
关键词
Chromatography; Statistical Analysis; Colormetric Reactions; Food Security; Antioxidants; Spreadsheets; ORTHOGONALITY; SEPARATIONS; EXCEL; CHROMATOGRAPHY;
D O I
10.1021/acs.jchemed.1c01191
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
In today's global economy, the origin of the food we eat is becoming more and more difficult to identify. Verifying the authenticity of products to protect supply chains is a complicated problem that requires a multidisciplinary approach. Chemical authentication of foodstuffs often includes a mass spectrometer detector; however, they are costly and require advanced operating skills. As an alternative, simple and robust post-column derivatization processes undertaken with HPLC may potentially provide chemical signatures of samples based upon the antioxidant profiles of the coffee samples. In this experiment, students employed a HPLC-PCD-VIS hyphenated separation protocol to produce a high-resolution chromatogram with minimal sample preparation, and the analysis was tuned to antioxidants in the coffee. Students encountered common analytical instruments and the commercially relevant CUPRAC assay. Using chromatographically derived data, students constructed MS Excel spreadsheets to normalize data and apply information theory to make statements about the similarity between coffee samples. Students were introduced to analytical protocols and chemometric techniques typical of 21st-century solutions to complex problems while utilizing common analytical instruments and reagents. Students were able to gain real-world laboratory skills, including running HPLC columns for sample analysis, method hyphenation, and signal retrieval. Students then utilized software to plot data for interpretation and to simplify data via preprocessing and chemometric operations to solve real-world problems.
引用
收藏
页码:1564 / 1570
页数:7
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