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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.

The advantages of chemiluminescence, digitally captured movies, magnetic solid-phase extraction (MSPE) and a robotized Flow-batch system were united to develop a new automated luminometer. This digital movie-based robotized Flow-batch luminometer was successfully applied for in-line MSPE, and sensitive, selective determination of Cu2+ in Cachaca (a distilled spirit made from fermented sugarcane juice). Magnetic Fe3O4@Al2O3 nanoparticles immobilized with 1-(2-pyridylazo)-2-naphthol and sodium dodecyl sulfate were employed as magnetic adsorbents. The catalytic effect of Cu2+ on luminol oxidation using H2O2 in alkaline medium was employed to generate the chemiluminescent signals, which were measured via digital movies. The method presented satisfactory analytical features when compared with previous studies, yielding: LOD = 7 μg L−1, recovery rates = 94.8–106.5%, RSD

In this paper, a flow-batch analysis (FBA) system, hydride generation (HG), and atomic fluorescence spectrometry (AFS) are coupled for the first time to develop a fast and sensitive FBA–HG–AFS method for automated inorganic antimony speciation in waters, whether from the sea, mineral water, tap water, or lakes. Unlike previous automated flow methods that use confluent fluids and complex devices, the main advantage of the proposed FBA-HG-AFS method is an innovative use of a simple laboratory made flow-batch chamber to simultaneously perform mixing, homogenization, reactions, antimony hydride formation, and gas–liquid separation. The FBA-HG-AFS method was optimized using two–level full factorial and Box–Behnken designs, and validated on the basis of real repeated measurements and analysis of variance, yielding a satisfactory working range (100–2000 ng L−1), precision (RSD = 4%), sensitivity, and limit of detection (6 ng L−1) for the water samples analyzed. Accuracy was evaluated by recovery tests and analysis of a standard reference material (SRM 1643e) of trace elements in water (NIST, USA), resulting in recovery rates of from 90 to 114%, and relative error = 0.7%. The high sampling throughput (54 speciations h−1), together with low waste generation, low costs, low reagent and sample consumption make this FBA-HG-AFS method an interesting proposal for fast large-scale analysis in routine laboratoy according to the principles of green analytical chemistry.

The pleasant taste and flavor of coffee are responsible for making it one of the most preferred and consumed beverages around the world. Industrial coffee plants usually roast both coffee and adulterants together, which affects directly the quality of the product, specially the sensorial characteristics of the drink. Therefore, this work aims the identification of adulterations in ground roasted coffees (due to the presence of husks and sticks) using ultraviolet–visible spectroscopy and the Successive Projections Algorithm for variable selection in association with Linear Discriminant Analysis (SPA-LDA). For this purpose, extracts of ground roasted coffees prepared in hot water alone (representing the final product as ingested by the consumers) were then analyzed. The proposed methodology obtained a 100% classification in both training and test sets, providing a simple and fast analysis of the aqueous extracts of ground roasted coffees. Moreover, it can also afford security to coffee consumers and regulatory agencies, preventing the fraudulent labeling.

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.

The traditional flow chemiluminescence (CL) systems typically use flow cells in spiral shape mounted in front of a photomultiplier tube (PMT). The sample is transported by using carrier fluids, undergoes dispersion, and mixes with reagents and CL reaction occurs before reaching the flow cell. As a consequence, the maximum of the chemiluminescence intensity is not exploited and the sensitivity is significantly diminished. In this work, these drawbacks were overcome by using a flow–batch approach and a large area silicon photodiode instead of PMT in order to build a simple and automatic luminometer for CL measurements. The feasibility of the proposed flow–batch luminometer was demonstrated in the determination of vitamin B 12 in injection ampoules, yielding limits of detection and quantification (0.11 and 0.36 μg L − 1 , respectively), recovery rates (between 97.8 and 102.1%), relative standard deviations (RSD − 1 ). Thus, it was possible to both project and build a simple, flexible, versatile and automatic luminometer, while keeping the excellent characteristics of the previous flow–batch analyzer such as: low reagent and sample consumption and minimal waste generation.

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.