Automated H2O2 monitoring during photo-Fenton processes using an Arduino self-assembled automatic system.

A cheap and easy to use Arduino self-assembled automatic system was employed to continuously monitor the hydrogen peroxide consumption during the photo-Fenton degradation of caffeine, selected as model target compound. The automatic system made it possible to measure the H2O2 concentration in the reaction cell via a colorimetric reaction and to take samples for HPLC analysis minimising the operator manual intervention and exposure to UV radiation. The obtained results were compared in terms of LOD and LOQ with H2O2 measurements manually performed using UV-Vis spectrophotometry, evidencing better analytical performance when using the automatic system; LOD and LOQ were respectively 0.032 mM and 0.106 mM for the automatic system against 0.064 mM and 0.213 mM for UV-Vis spectrophotometry. Furthermore, the photo-Fenton treatment was optimised by means of a Design of Experiments (DoE) investigating the effect of added H2O2 concentration, iron concentration and caffeine initial concentration on system performances. The use of the automatic device for such monitoring provided several advantages: automation (with consequent reduction of the workload), measurement increased precision, reduced reagents consumption and waste production in agreement with the principles of Green Analytical Chemistry.

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.