This article describes the development of a mobile colorimetric analysis tool. The application, called PhotoMetrix, employs the techniques of simple linear correlation for univariate analysis and principal components analysis (PCA) for multivariate exploratory analysis. The image data are captured by the main camera of the device and converted into red, green and blue (RGB) histograms. As regards the application, the iron determinations were performed in vitamin supplements (univariate module) and differentiation of banknotes was performed by PCA (multivariate module). For the iron determinations, three samples of vitamins at concentrations of 14, 40 and 50 mg of iron per tablet were tested and the results were not statistically significant (p > 0.05) compared to the reference method. The differentiation of banknotes was performed on Brazilian and Argentinean banknotes. The results showed clustering of the same types of banknotes, and through the loadings graph it was possible to observe the variables through the formation of clusters.

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This study investigated the application of infrared spectroscopy with multivariate calibration methods for at‐line monitoring of the degradation of soybean oil in industrial frying processes by determining when the acidity index and total polar materials (TPM). The infrared spectra (650–3,200 cm−1) were acquired using the attenuated total reflection accessory (ATR‐FTIR), with a resolution of 4 cm−1, and 16 scans. Partial least‐squares regression (PLS) models were evaluated for individual and simultaneous determination, and results were compared with reference methods. The individual calibration model showed standard error of prediction values of 0.09% (w/w) and 1.6% (w/w) for the acidity index and TPM, respectively. The simultaneous determination of the acidity index and TPM showed SEP values of 0.17% (w/w) and 1.6% (w/w), respectively. The results demonstrate that infrared spectroscopy combined with multivariate calibration techniques can be servant used in routine soybean oil quality control in industrial frying processes. Practical applications Foods prepared by the frying process are strongly influenced by the oil used in the process, since the product tends to absorb part of the oil during its cooking. This oil when used for a long period and exposed to high temperatures, end up suffering oxidation reactions, and can greatly reduce your shelf life. In this way the industries that use these processes for the manufacture of their products, apply a series of chemical analyzes in order to validate the quality of the oil used, these analyzes use a high amount of solvents and time. As an alternative to the use of these traditional analyzes, methods have been developed through the use of infrared spectroscopy combined with multivariate analysis tools, for the creation of partial least squares calibration models for the prediction of quality parameters of oils used in frying.

O objetivo principal deste estudo foi desenvolver um modelo multivariado de calibração por quadrados parciais (PLS) para quantificação do teor de etanol anidro em amostras comerciais de gasolina, utilizando um software de quimiometria gratuito. Para isso, espectros de infravermelho médio das amostras foram adquiridos em uma atividade experimental de estudantes de graduação em Química da UNISC, para melhorar a compreensão dos métodos de calibração multivariada. O modelo de calibração PLS apresentou resultados semelhantes aos obtidos pelo método de referência (NBR:13992) (p > 0,05), com valores de exatidão entre 97,8 e 108,2%. Além disso, a metodologia desenvolvida neste estudo se destaca por consumir até 25 vezes menos amostra (2 mL), o que resulta em menor geração de resíduos e maior frequência de análise (>30 amostras por hora), baixo consumo de energia (340 Wh-1) e na dispensa do uso de reagentes.