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This study addresses the challenge of performing fast and accurate titrations with end points that are difficult to identify. In this sense, the combination of digital movies (DMs) with a flow-batch analyzer (FBA) has shown to be a promising analytical tool. In a digital movie-based automatic titrator (DMB-AT), a DM is recorded by a webcam as the titrant is added in the mixing chamber (MC). The DM is then decompiled into frames that are ordered sequentially. In the first frame, the region of interest (ROI) of 257 × 255 pixels is defined. The red (R) component is used to calculate the Pearson's correlation coefficient (r) between the first frame and each subsequent one. The titration curve is obtained in real time by plotting r values and the opening time of the titrant valve. The experimental titration curve is fitted in a sigmoidal regression, and the new titration curve is used to estimate the end point by means of the second derivative method. A software program written in Adobe AIR for a desktop platform programmed in ActionScript 3.0 controlled the opening time of the solenoid valves, gathered the analytical signal and carried out the analytical procedure in real time. The feasibility of the method was confirmed by determining the total hardness and the total alkalinity in mineral waters. The results were compared with classical batch titration and did not exhibit statistically significant differences when the paired t-test at the 95% confidence level was applied. The proposed method is able to process approximately 67 and 86 samples h− 1 for total hardness and total alkalinity, respectively. Its precision was confirmed by overall relative standard deviation (RSD) values of less than 1.0% in both applications.

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 paper introduces for the first time the combination of digital images taken with a webcam and a micro-flow-batch analyzer as a novel strategy for implementing quantitative chemical analysis. The digital image-based micro-flow-batch analyzer (DIB-μFBA) was formed using urethane-acrylate resin, glass slides and ultraviolet lithography. The glass slides were used as sealant layers on both sides of the substrate urethane-acrylate and provide the necessary transparency to the microsystem to conduct studies using digital images. DIB-μFBA uses digital images obtained from a webcam with CCD sensor, based on the RGB (red–green–blue) color model. The analyzer was used for determining the tannins in green tea employing the well-known ferrous tartrate method. All standard solutions were prepared in-line, and all analytical processes were completed by simply changing the operational parameters in DIB-μFBA control software. The paired t test, at a 95% confidence level, showed no statistically significant differences between results obtained by DIB-μFBA and the spectrophotometric reference method. The proposed microsystem presented satisfactory physical and chemical properties while keeping the flexibility, versatility, robustness and multi-task characteristics of conventional flow-batch analysis. Therefore, it was possible to build a low-cost device with high sample throughput (about 190 h− 1) and reduced reagent consumption (about 300 times less than the reference method), contributing to the basic principles of green chemistry and the advancement of micro-analytical procedures.

A novel strategy to evaluation of adulteration in alcoholic beverages based on the measurement of the Schlieren effect using an automated FIA system with photometric detection is proposed. The assay is based on the Schlieren effect produced when beverage samples are injected in a single-line FIA system that uses water as carrier stream and a light-emitting diode–phototransistor photometer controlled by microcomputer as detector. The flow system presents limited mixing conditions which make possible to create gradients of refractive index (Schlieren effect) in the injected sample zone. These gradients are reproducible, characteristic of each alcoholic beverage and undergo specific modifications when adulterations with water or ethanol are imposed. Schlieren effect data of brandies, cachacas, rums, whiskies and vodkas were treated by SIMCA to elaborate class models applied in the evaluation of alcoholic beverages adulteration. Samples of the original matrix of each sort of beverages were adulterated in laboratory by adding water, methanol and ethanol in levels of 5% and 10% (v/v). These samples were used as test set to validate SIMCA class models. The verification of authenticity using Schlieren effect measurements presented good results making possible to identify 100% of the beverages samples adulterated in laboratory and 93% of the actual adulterated alcoholic beverages with confidence levels of 95%. As principal advantage, the automated system does not use reagents to carry out the analysis.