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This worlk proposes a rapid, sensitive and accurate flow-batch digital image colorimetric (FB-DIC) system to zinc oxid determination in ointments. The method was based on the reaction between Zn(II) ions and zincon at pH = 9.0. The Zn(II)-zincon complex was formed and detected in the mixing chamber. It was designed with two opposite glass windows: one for the webcam and other for the ultra-bright LED. Absorbance was calculated by the norm of the vector in the RGB space. The method had a linear range between 1.0-8.2 mg L–1 with R2 = 0.9998 (n=8) and limit of detection estimated as 5.7 mg L–1. The relative standard deviation (RSD) and sample throughput were estimated at 0.06% and 109 samples h-1, respectively. Ointment commercial samples were analyzed by FB-DIC and the refference method. The results shown no statistically significant difference between them, when was applied the paired t-test at the 95% confidence level. According to green analytical chemistry (GAC) principles the FB-DIC system can be considered eco-driendly due to its low samples and reagents consumption as its low waste generation.

In this paper, we propose a new methodology to identify adulterations in ground roasted coffees (due to the presence of husks and sticks) using digital images and the successive projections algorithm for variable selection in association with linear discriminant analysis (SPA-LDA). A simple document scanner was used for capturing the images, and a Petri dish support with eight circular holes (one for each sample) to be scanned was employed. Color histograms in the hue-luminosity-saturation (HLS) channels extracted from the digital images were used as input data and statistically evaluated using supervised pattern recognition techniques. For comparison with SPA-LDA, soft independent modeling by class analogy (SIMCA) and partial least squares discriminant analysis (PLS-DA) were also used. In general, SPA-LDA provided significantly better performance than the other classification models, reaching a mean accuracy of 92.5 % for both the training and test sets, while SIMCA and PLS-DA attained only 71.5 and 85.5 %, respectively. More specifically, all of the models presented high rates (above 90 %) for sensitivity and specificity (in the test set samples classification), except SIMCA, which presented a specificity rate of 76 %. Moreover, the SPA-LDA model generally showed the lowest classification error rates. As such, it is a more adequate chemometric tool for discriminating pure coffee samples and adulterated by husks and sticks. The proposed strategy avoided laborious sample preparation, and additional operational costs, assessing coffee adulteration by husks and sticks.

This paper proposes combining Multiple Linear Regression (MLR) and Digital Image-Based Flame Emission Spectrometry (DIB-FES) to overcome the inherent spectral interference in Flame Emission Spectrometry (FES) when sodium and calcium are present in the same sample. Metals in the air–butane flame emit radiation which is revealed in the digital images captured by a webcam (detector), on the basis of the Red-Green-Blue (RGB) color system. MLR calibration models for sodium and calcium were both developed and validated. In order to illustrate the feasibility of this proposal, the validated models were applied for the determination of sodium and calcium in powder milk. The results were compared with those obtained using Flame Atomic Absorption Spectrometry (FAAS) as the reference method. No statistically significant difference was observed between the results for both metals by using the paired t-test at a 95% confidence level. The accuracy of the models was also attested to by their recovery factors which fell between 97 and 103% for both metals. The results confirm the models' discriminating power in isolating each analyte's information from a single digital image, even with spectral interference.

This study proposes a digital image-based flow-batch analyzer (DIB-FBA) for aluminum (III) and chromium (VI) determinations in natural water. A webcam with a CCD sensor and RGB data are used. The method for determining aluminum is based on an Al(III) ion, quercetin, and cetyltrimethylammonium bromide (CTAB) reaction which yields a yellow colored complex in an acetate buffer medium (pH 5.5). The determination of chromium is based on a Cr(VI) ion with 1,5-diphenylcarbazide (DPC) reaction whose product is a violet colored complex. Digital images present the color of the emergent (complementary) radiation to that absorbed by the complexes formed in each analysis. RGB data were employed to build the analytical curves. All standard solutions were prepared in-line, and all analytical processes were completed by simply changing the operational parameters in the DIB-FBA control software. The working ranges were from 10 to 600 μg L − 1 for Al(III) with r = 0.9994 (n = 5), and 10 to 300 μg L − 1 for Cr(VI) with r = 0.999 (n = 5), the limits of detection were 3.97 and 2.65 μg L − 1 respectively for Al(III) and Cr(VI). The relative standard deviation (RSD %) and sampling rate were estimated at 1.5% and 137 h − 1 and at 1.7% and 134 h − 1 for Al(III) and Cr(VI), respectively. Comparing with the reference method, no statistically significant differences were observed when applying the paired t -test at a 95% confidence level.

This work proposes the use of digital image-based method for determination of total acidity in red wines by means of acid-base titration without using an external indicator or any pre-treatment of the sample. Digital images present the colour of the emergent radiation which is complementary to the radiation absorbed by anthocyanines present in wines. Anthocyanines change colour depending on the pH of the medium, and from the variation of colour in the images obtained during titration, the end point can be localized with accuracy and precision. RGB-based values were employed to build titration curves, and end points were localized by second derivative curves. The official method recommends potentiometric titration with a NaOH standard solution, and sample dilution until the pH reaches 8.2-8.4. In order to illustrate the feasibility of the proposed method, titrations of ten red wines were carried out. Results were compared with the reference method, and no statistically significant difference was observed between the results by applying the paired t-test at the 95% confidence level. The proposed method yielded more precise results than the official method. This is due to the trivariate nature of the measurements (RGB), associated with digital images.

The exploitation of digital images obtained from a CCD camera (WebCam) as a novel instrumental detection technique for titration is proposed for the first time. Named of digital image-based (DIB) titration, it also requires, as a traditional titration (for example, spectrophotometric, potentiometric, conductimetric), a discontinuity in titration curves where there is an end point, which is associated to the chemical equivalence condition. The monitored signal in the DIB titration is a RGB-based value that is calculated, for each digital image, by using a proposed procedure based on the red, green, and blue colour system. The DIB titration was applied to determine HCl and H3PO4 in aqueous solutions and total alkalinity in mineral and tap waters. Its results were compared to the spectrophotometric (SPEC) titration and, by applying the paired t-test, no statistic difference between the results of both methods was verified at the 95% confidence level. Identical standard deviations were obtained by both titrations in the determinations of HCl and H3PO4, with a slightly better precision for DIB titration in the determinations of total alkalinity. The DIB titration shows to be an efficient and promising tool for quantitative chemical analysis and, as it employs an inexpensive device (WebCam) as analytical detector, it offers an economically viable alternative to titrations that need instrumental detection.

A digital image-based flame emission spectrometric (DIB-FES) method for the quantitative chemical analysis is proposed here for the first time. The DIB-FES method employs a webcam to capture the digital images which are associated to a radiation emitted by the analyte into an air-butane flame. Since the detection by webcam is based on the RGB (red-green-blue) colour system, a novel mathematical model was developed in order to build DIB-FES analytical curves and estimate figures of merit for the proposed method. In this approach, each image is retrieved in the three R, G and B individual components and their values were used to define a position vector in RGB three-dimensional space. The norm of this vector is then adopted as the RGB-based value (analytical response) and it has revealed to be linearly related to the analyte concentration. The feasibility of the DIB-FES method is illustrated in three applications involving the determination of lithium, sodium and calcium in anti-depressive drug, physiological serum and water, respectively. In comparison with the traditional flame emission spectrometry (trad-FES), no statistic difference has been observed between the results by applying the paired t-test at the 95% confidence level. However, the DIB-FES method has offered the largest sensitivities and precision, as well as the smallest limits of detection and quantification for the three analytes. These advantageous characteristics are attributed to the trivariate nature of the detection by webcam.

This paper proposes a digital image-based flame emission spectrometric (DIB-FES) method for indirect determination of sodium diclofenac, sodium dipyrone and calcium gluconate in injectable forms. The proposed DIB-FES method uses digital images obtained from a webcam, based on the RGB (Red-Green-Blue) system. It offers a simple and inexpensive way to quantify these organic substances using the radiation emitted by the alkaline and earth-alkaline metals present in their formulae. Analytical curves were constructed on the basis of the relationship between RGB values and calibration solution concentrations. The results showed no statistical difference between the proposed and reference methods when applying the paired t-test at a 95% confidence level. The proposed DIB-FES method also performed well in terms of the figures of merit LOD, LOQ, linear range, precision, and the accuracy as revealed by recovery tests.