ABSTRACT
In the present work, we report the development of a novel cotton thread-based colorimetric sensor modified by carboxymethylcellulose (CMC) and cuprizone (CPZ) with smartphone detection and its application for the quantitative determination of cupric ions in water and cachaça. The cotton thread/smartphone detection-based colorimetric method is an easily affordable, low-cost technique which allows one to perform real-time and on-field determination analyses, especially with limited financial resources. The method involves the complexation of Cu(II) with CPZ, which causes a change in the coloration of the cotton thread from a shade of white to blue in the detection zone of the colorimetric sensor. The immobilization of CPZ on CMC in the cotton thread leads to the pre-concentration of Cu(II) via a complexation mechanism with colorimetric reaction. The application of the colorimetric sensor allows the quantification of copper in the range from 1 to 12 mg L-1, with a low limit of detection of 0.21 mg L-1. In addition, the recovery assays conducted in samples of water and cachaça resulted in recovery percentages ranging from 84.9% to 107%, which is indicative of a precise method. To validate the precision of the proposed colorimetric method, the values obtained from the quantification analysis were compared with those of the flame atomic absorption spectrometry and a good agreement at the 95% confidence level was obtained.
ABSTRACT
The present study reports, for the first time, the development and application of a highly efficient method based on digital imaging analysis for the simultaneous determination of Cu2+ and furfural in cachaça samples using a two-phase system and chemometrics tools. Furfural reacts with aniline in an acidic medium to form a Schiff base, which exhibits a pink color. On the other hand, Cu2+ reacts with cuprizone in a basic medium to form a blue complex. The two reactions were performed on a porcelain plate, and a smartphone was used to capture the colorimetric images. Partial least squares (PLS) regression was used to construct the prediction models for Cu2+ and furfural contents in cachaça samples. After finding the best PLS models, the ordered predictor selection (OPS) analysis was performed in order to select the most predictive variables. The method developed was found to be effective in estimating the amounts of Cu2+ and furfural in cachaça samples, with a mean absolute error of 0.2 mg L-1 for the Cu2+ model, and 0.3 mg per 100 mL of anhydrous alcohol for the furfural model. The method proposed in this study is simple and straightforward; it does not require complex technical knowledge and can be used by the producers themselves in the cachaça manufacturing process.
ABSTRACT
In this work we propose for the first time, a paper-based test strip to analyse Cu2+ content in sugar cane spirits, which, due to its simplicity, high portability and fast analytical response (3 min), can be easily applied to in situ analyses by producers. The test strip was developed aiming: i) identify qualitatively the Cu2+ content in sugar cane spirits, and, ii) determine quantitatively the Cu2+ content using a digital image method employing a smartphone. The paper-based test strip was functionalized with cuprizone and optimized through a Box-Behnken, an experimental design for obtaining the best reaction conditions. Based on qualitative method with naked eyes approach performed by six volunteers analyst untrained, the method present a percentage of accuracy of 93%. For the quantitative analysis, it was determined the metal content at a level of statistical agreement with the reference method, as well as it was obtained the dynamic linear range from 2 to 13 mg L-1 with limits of detection and quantification of 0.034 and 0.103 mg L-1, respectively. Furthermore, the quantitative method showed a reliable precision with an RSD of 4.3% (n = 10) and the recovery of Cu2+ ranged from 80 to 103.8%.