Beyond RGB: Integration of an 8-Channel Digital Light Sensor into a Fully Automated Platform for Colorimetric Sensor Arrays.

Sensing arrays are a powerful tool for discriminating complex samples without the need for pretreatment steps or separation techniques. Among them, colorimetric sensor arrays rely on the color change of specific reagents upon interaction with the chemicals present in the sample. Typically, the color change of each sensing element is obtained through digital image acquisition, followed by color data extraction using a color space (i.e., RGB model). Despite its widespread application, the RGB model limits color information to only three channels, which can reduce the method's discrimination capability. Moreover, the image acquisition, followed by color extraction, can be time-consuming, particularly when the array includes dozens of reagents. In this study, we propose, for the first time, the integration of a fully automated analytical platform with an 8-channel digital light sensor for application in colorimetric sensor arrays. As a proof-of-concept, the system was used to discriminate various food products (e.g., tea, sauces, soda, and juice) based on their acid-base properties using six pH indicators. Eleven microliters of each indicator were deposited onto rectangular filter paper, followed by the addition of each food sample. The paper sensors were then placed in their respective positions on the automated platform. Color changes were measured using a digital light sensor integrated into the system. The total data acquisition time was less than 1 min. The resulting data were processed by using principal component analysis (PCA) and hierarchical cluster analysis (HCA), successfully enabling sample discrimination. This study presents a simple, fast, low-cost, and fully automated analytical platform that enhances the capabilities of colorimetric sensor arrays by coupling them with a multichannel optical detection system.