Secure Food-Allergen Determination by Combining Smartphone-Based Raw Image Analyses and Liquid Chromatography-Mass Spectrometry for the Quantification of Proteins Contained in Lateral Flow Assays.

Abstract

The current food safety testing system, based on laboratory-based quantification, is difficult to scale up in line with the growth in the export market and does not enable traceability through the nodes of the food supply system. Screening assays, for example, lateral flow assays (LFAs), can improve traceability but often lack the required reliability to guarantee compliance. Here, we present an alternative pipeline for secure on-site compliance testing, using allergens as a case study. The pipeline features smartphone-driven LFA quantification and an liquid chromatography-mass spectrometry (LC-MS) method enabling direct quantification of the allergens contained in the LFA. The system enables swift and objective screening and provides a control measure to verify LFA assay reliability. For the smartphone assay, 8-bit RGB and grayscale colorimetric channels were compared with 16-bit raw intensity values. The latter outperformed RGB and grayscale channels in sensitivity, repeatability, and precision, while ratiometric ambient light correction resulted in excellent robustness for light-intensity variation. Calibration curves for peanut determination using two commercial LFAs featured excellent analytical parameters (R2 = 0.97-0.99; RSD 7-1%; LOD 3-7 ppm). Gluten determination with a third commercial LFA was equally established. A prediction error of 13 ± 11% was achieved for the best performing assay. Good performance-calibration curves (R2 = 0.93-0.99) and CVs (<15%)- were observed for the analyte quantification from the LFA by LC-MS. The LOD for the LC-MS assay was 0.5 ppm, well below the LODs reported for the LFAs. This method creates a digital, fast, and secure food safety compliance testing paradigm that can benefit the industry and consumer alike.