Smartphone app-enabled dual-mode fluorescence and colorimetric portable sensors using RB@BSA-AuNRs for quality identification of plant-derived products.

The geographical origin of raw materials critically influences the polyphenol (PPs) profile of plant-derived products (PDPs), which in turn determines their quality and authenticity. Herein, we report a smartphone app-enabled dual-mode (colorimetric/fluorescence) portable sensing platform for rapid origin traceability and quality prediction of PDPs, using Chrysanthemum Flos (CF) as a model. The sensor is based on a nanocomposite of rhodamine B-labeled bovine serum albumin and gold nanorods (RB@BSA-AuNRs). In the colorimetric mode, PPs induce BSA detachment from AuNRs, altering their aspect ratio and causing distinct color shifts. In the fluorescence mode, this interaction modulates a gated fluorescence resonance energy transfer (Gate-FRET) process between RB and AuNRs and an internal filtration effect (IFE), resulting in ratiometric fluorescent responses. Variations in PPs content among CF from different origins generate unique colorimetric and fluorescent signatures. These signatures are captured by a smartphone, processed via a custom app, and analyzed by cloud-based machine learning algorithms. This integrated system achieved an average accuracy of 97 % for origin classification and predicted the content of specific compounds and antioxidant activities with errors between 2 % and 19 %. The developed platform offers a rapid, portable, and low-cost approach for on-site quality assessment and traceability of polyphenol-rich plant products.