摘要
Composite dyes (CDs) assembled via non-covalent TPP-pH interactions. • CDs-based array captured full-wavelength fingerprints of fermented goji juice. • Accurate quantification of total phenolics and DPPH activity achieved (RPD > 3). • Novel approach for rapid antioxidant monitoring in complex fermentation. Goji berry juice (GBJ) is a highly popular healthy drink among consumers. Rapid monitoring of the antioxidant properties of GBJ is crucial and necessary. A colorimetric sensor array (CSA) based on composite dyes was used for the rapid detection of the antioxidant properties of GBJ. High-dimensional spectral fingerprint information combined with chemometric methods was used to construct a quantitative prediction model. The effects of different preprocessing and feature screening methods on model prediction were compared. Machine learning algorithms were used to establish quantitative prediction models. The CARS-PLSR model achieved accurate quantification of total phenol, with Rp and RPD values of 0.95 and 3.18, respectively. For DPPH free radical scavenging rate, the CARS-LSSVR model had an Rp value of 0.95, an RPD value of 3.33, and an RMSEP of 0.04. The proposed method in the research provides a new idea for the rapid quality monitoring of the fermentation process of GBJ. Download: Download high-res image (127KB) Download: Download full-size image
危险品化学品经营许可证(带存储)