In the past twelve years, digital image colorimetry (DIC) on smartphones has acquired great importance as an alternative to the most common analytical techniques. This analysis method is based on fast, low-cost, and easily-accessible technology, which can provide quantitative information about an analyte through the color changes of a digital image. Despite the fact that DIC is very widespread, it is not exempt from a series of problems that are not fully resolved yet, such as variability of the measurements between smartphones, image format in which color information is stored, power distribution of the illuminant used for the measurements, among others. This article proposes a methodology for the standardization and correction of these problems using self-developed software, together with the use of a 3D printed light box. This methodology is applied to three different colorimetric analyses using different types and brands of smartphones, proving that comparable measurements between devices can be achieved. As color can be related to many target analytes, establishing this measurement methodology can lead to new control analysis applicable to diverse sectors such as alimentary, industrial, agrarian, or sanitary.

The use of smartphones as analytical instruments is becoming increasingly widespread due to their ease of use and low cost. However, it has limitations, such as dependence on the smartphone’s sensor, the light source and the environment, which hinders the reproducibility and comparability of results. This paper presents the development of a portable device, called DUNI, which can be attached to any smartphone and is designed to overcome these limitations. The device, manufactured using 3D printing and with an average cost of €35, consists of an integrating sphere, which incorporates a lighting-electronic system, as well as accessories for measuring on different surfaces. It has been optimised by evaluating the influence of the optical geometry, the size and reflective coating of the sphere, the lighting conditions, and the electronic stability on measurement performance. It has been applied to the determination of hydrogen peroxide and biogenic amines in synthetic samples, achieving relative errors of less than 5% and detection limits between 3 and 6 µM. Overall, the device we have developed constitutes a portable, versatile and low-cost platform that enables quantitative colorimetric measurements using smartphones under controlled lighting conditions, with potential applications in on-site analysis and resource-limited settings.