As a special carrier of traditional Chinese culture, baijiu is rich in terms of types and ingredients. Its quality analysis and control are always important and complex issues that urgently need reliable evaluation methods. In this study, four different modified CdTe quantum dots (QDs) were used to characterize their sensing performance to various baijiu. A sensor array was then constructed through the complementary properties of differential fluorescence signals. To achieve an accurate and rapid evaluation of different baijiu types, a linear discriminant analysis (LDA) was introduced to extract and process spectral information. And the array was able to distinguish commercial baijiu samples with different aroma-types, brands, qualities and storage years with a recognition rate of 100%. In addition, according to the heat map, the organic acids in baijiu were shown to be the main components causing the fluorescence change through electron transfer (hydrogen bond) and resonance energy transfer among QDs and acids. Furthermore, using the partial least squares regression (PLSR) model, five representative organic acids were accurately quantified with a quantitative range of 10 μmol/L-80 μmol/L with a high selectivity. This QDs fluorescence sensing strategy provides an accurate, simple, and fast baijiu sensing method, which provides a potential use for on-line baijiu monitoring.
Keywords: Commercial baijiu; Fluorescent sensor array; Linear discriminant analysis; Partial least squares regression; Quantum dots.
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