Prediction of active compound content and identification of origin of Chrysanthemi Flos using Fe3+-mediated multi-mechanism fluorescence visual sensor with chemometrics

Chrysanthemi Flos (Hangbaiju) is a traditional Chinese medicine and the third most popular beverage after Chinese tea and coffee, but there are geographical confusion and quality control problems in its market distribution. Here, we constructed an Fe3+-mediated fluorescence nanosensing system for the visual identification of Hangbaiju from different origins and the prediction of compounds content, which were verified by HPLC-HRMS. The formation of Fe3+@QDs was the main element of the method under electron transfer (ET) effects, as well as the presence of 1) chelation-quenched fluorescence (CHQF) effects, 2) homogeneous fluorescence resonance energy transfer (Homo-FRET), and 3) the TURN OFF/ON reaction pattern, between caffeic acid and its derivatives (CAs), Fe3+, QDs, flavonoids, and Fe3+@QDs, demonstrated by various characterization methods and density flooding theory (DFT). The visualisation appears green when the sample is high in CAs, red when high in flavonoids, and grey when low in both compounds. The random forest (RF) model based on spectral and visualisation data had an origin identification accuracy of 100 % and 93.33 %, respectively. Eight compounds content prediction based on RF models also showed good results. The best Rp and prediction errors of spectral and visual data were 0.97 and 0.95, 13 % and 12 %, respectively.

Automated summary

In this study, a fluorescence nanosensing system was developed for the visual identification of Hangbaiju and the prediction of compounds content. The system showed high accuracy and was validated using various characterization methods and theory. The application of the random forest model on spectral and visual data further confirmed its effectiveness.