Smartphone-based colorimetric detection platform using color correction algorithms to reduce external interference.

Smartphone-based digital image colorimetry is a powerful, fast, low-cost approach to detecting target analytes. However, lighting conditions and camera parameters easily affect the detection results, significantly curtailing its applicability in multiple scenarios. In this study, an Android-based mobile application (SMP-CC) is developed, which offers a comprehensive package that includes image acquisition, color correction, and colorimetric analysis functions. Using a custom color card, a built-in algorithm in SMP-CC can minimize the color difference between the standard color block image captured by different smartphones under different lighting conditions and the standard value by an LS171 colorimeter less than 4.36. The algorithm significantly eliminates the impacts of external lighting conditions and differences in cell phone models. Furthermore, the feasibility of SMP-CC was verified by successful colorimetric detection of urine pH, glucose, and protein, demonstrating its potential in smartphone-based digital image colorimetry.

An open-source handheld spectrometer for colorimetric and fluorescence analyses.

Spectrometers are essential analytical devices for analyzing fluid samples in biological, environmental, and disease diagnostic applications. However, the relatively high cost, the lack of portability, and the requirement for a constant power supply of bulky laboratory instruments limit their on-site applications. Herein, a wireless, cost-effective, open-source, and handheld spectrometer was designed and fabricated to realize the colorimetric and fluorescence analyses. It was built from off-the-shelf electronics utilizing 3D printing technology. The assembled device costs as little as $50. It has an overall dimension of 5 × 5 × 8 cm and an overall weight of only 130 g, which can easily fit in the palm of an adult's hand. It can detect light waves in the 405-690 nm range and transmit the read data to the corresponding SpecAnalysis Android application via Bluetooth. The feasibility of the device was demonstrated by the optical detection of Cu(II), bovine serum albumin, and calf thymus DNA. The sensitivity and detection limits of this device were comparable to those of commercial research-grade spectrophotometers and fluorescence spectrometers. The results suggest that the handheld spectrometer can be applied to detect a variety of substances, not limited to quantitative analysis of a specific individual compound.