A smartphone image-based method for the colorimetric characterization of historical pigments in mural paintings.

In this article, the detailed description of a smartphone-based analytical method to turn a smartphone into a colorimeter is described and applied to mural painting replicas. The method consists of a camera characterization process, to estimate CIELAB values from RGB camera responses, correcting for potential experimental interferences, like the effect of the lighting/capture geometry or software for color modification and enhancement. Next, the estimated CIELAB descriptors were used to build a chemometric Support Vector Classifier to objectively distinguish among the colors of the different pigments. The method was validated in terms of color reproduction and classification performance.•A smartphone-based method is described to capture mural painting color.•A color gamut-specific camera characterization procedure is developed and the performance of the smartphone-based colorimeter is compared with a spectrophotometer.•A classification method based on the estimated CIELAB descriptors is validated in terms of classification performance.

Unveiling origins, composition, and appearance of ancient Islamic gold coins through elemental and smartphone-based colorimetric studies.

In this article, the Islamic gold coins collections of the University of Valencia is studied for the first time for its elemental composition and colorimetric properties. To that end, non-destructive elemental analysis using energy-dispersive X-ray fluorescence is applied to obtain the coins' elemental profile. Additionally, the colour of the coins is assessed using smartphone-based colorimetry as an innovative non-invasive method. Results indicate that the Islamic coins could be attributed to Almoravids, and the gold origin could be the famous Sudanese gold, an ore which was valued all over the world. Also, the text found in the coins was translated and allowed to objectively identify the mint and year. Based on these results, it can be seen that the earliest coins struck in the Iberian Peninsula are characterised by slightly lower gold concentrations than the ones struck in the northern part of Africa, pointing towards a potential recycling of coins which already circulated in the area. In conclusion, this work provides new analytical insights into a peculiar and unique type of samples, allowing to draw some conclusions in terms of their origins and materials, and for the first time allows to characterise the chromatic coordinates of this type of samples.

Smartphone-based procedure to determine content of single synthetic dyes in food using the Arata-Possetto extraction method.

The use of additives, including dyes, is common in the preparation of food products. The analytical control of artificial food dye content is relevant since some, such as azo dyes, may produce cancer and attention deficit disorders and hyperactivity in children. Consequently, the maximum permitted concentration of azo dyes in food is regulated by current legislation. Therefore, it is of interest to find simple and fast procedures for the control of these compounds. The aim of this study is to determine the concentration of azo dyes in food samples by the Arata-Possetto method - based on the extraction of azo dyes employing natural wool -, followed by the analysis of an image captured by a smartphone camera. After experimentally determining the optimal extraction conditions, the calibration curves for standard solutions of different food dyes and the color of the dyed wool were obtained. Results from dyed wool image processing were compared with the absorbance spectra of the solutions before extraction as measured by a diode array spectrophotometer. The spectrophotometric and the image processing procedures were employed to obtain the calibration curves for different food dyes, which were subsequently employed to analyze food samples. Statistical treatment shows that the results of both methods are comparable.

Development of an automated colorimeter controlled by Raspberry Pi4.

A low-cost new instrument to carry out automated colorimetric analysis has been developed. The device consists of a carousel sampler, built by a 3D-printer, and a Raspberry Pi4-controlled signal measurement module based on the RGBC (red, green, blue and clear) responses of a TCS34725 color light-to-digital converter with IR filter. The device has been tested with calibration standards of different food dyes (Tartrazine, Red Allure AC and Brilliant Blue FCF) and three food samples containing one of each food dye. The new device provides R2 > 0.995 and a LOD of 1.1, 1.4 and 0.1 µmol L-1 for each food dye, respectively. The results are statistically comparable to those obtained with a conventional benchtop spectrophotometer. The proposed device achieves a reduction in sample and waste volume and in analysis time, minimizes the use of energy, and allows in situ measurements, being an automated method it is safer for operators in comparison to the reference method, yielding similar analytical results and following the principles of green analytical chemistry.

Smartphone-based colorimetric study of adulterated tuna samples.

In this work, a colorimetric analysis of adulterated tuna samples is carried out using both a spectroradiometer and a smartphone as capture devices. Yellowfin tuna (Thunnus albacares) slices were treated with nitrate and nitrite salts, as well as with two different vegetable extracts (beetroot and radish), and the resulting NO2- and NO3- concentration was analysed using HPLC-DAD. The results indicate that both nitrite and beetroot treatments work properly as colouring agents in tuna, being nitrate also effective. When assessing the effect of radish, the final flesh had a more whitish colour. Overall, this approach allows to obtain colorimetric data which can distinguish among the different adulterating agents.