The use of dyes at an industrial level has become problematic, since the discharge of dye effluents into water disturbs the photosynthetic activity of numerous aquatic organisms by reducing the penetration of light and oxygen, in addition to causing carcinogenic diseases and mutagenic effects in humans, as well as alterations in different ecosystems. Chitosan (CS) is suitable for removing anionic dyes since it has favorable properties, such as acquiring a positive charge and a typical macromolecular structure of polysaccharides. In this study, the optimization of CS beads crosslinked with glutaraldehyde (GA) for the adsorption of reactive blue dye 4 (RB4) in an aqueous solution was carried out. In this sense, the response surface methodology (RSM) was applied to evaluate the concentration of CS, GA, and sodium hydroxide on the swelling degree in the GA-crosslinked CS beads. In the same way, RSM was applied to optimize the adsorption process of the RB4 dye as a function of the initial pH of the solution, initial concentration of the dye, and adsorbent dose. The crosslinking reaction was investigated by scanning electron microscopy (SEM), Fourier transformed infrared spectroscopy (FTIR), and X-ray diffractometry (XRD). The design described for the swelling degree showed an R2 (coefficient of determination) adjusted of 0.8634 and optimized concentrations (CS 3.3% w/v, GA 1.7% v/v, and NaOH 1.3 M) that were conveniently applied with a concentration of CS at 3.0% w/v to decrease the viscosity and facilitate the formation of the beads. In the RB4 dye adsorption design, an adjusted R2 (0.8280) with good correlation was observed, where the optimized conditions were: pH = 2, adsorbent dose 0.6 g, and initial concentration of RB4 dye 5 mg/L. The kinetic behavior and the adsorption isotherm allowed us to conclude that the GA-crosslinked CS beads’ adsorption mechanism was controlled mainly by chemisorption interactions, demonstrating its applicability in systems that require the removal of contaminants with similar structures to the model presented.
The sensorial properties of Colombian coffee are renowned worldwide, which is reflected in its market value. This raises the threat of fraud by adulteration using coffee grains from other countries, thus creating a demand for robust and cost-effective methods for the determination of geographical origin of coffee samples. Spectroscopic techniques such as Nuclear Magnetic Resonance (NMR), near infrared (NIR), and mid-infrared (mIR) have arisen as strong candidates for the task. Although a body of work exists that reports on their individual performances, a faithful comparison has not been established yet. We evaluated the performance of 1H-NMR, Attenuated Total Reflectance mIR (ATR-mIR), and NIR applied to fraud detection in Colombian coffee. For each technique, we built classification models for discrimination by species (C. arabica versus C. canephora (or robusta)) and by origin (Colombia versus other C. arabica) using a common set of coffee samples. All techniques successfully discriminated samples by species, as expected. Regarding origin determination, ATR-mIR and 1H-NMR showed comparable capacity to discriminate Colombian coffee samples, while NIR fell short by comparison. In conclusion, ATR-mIR, a less common technique in the field of coffee adulteration and fraud detection, emerges as a strong candidate, faster and with lower cost compared to 1H-NMR and more discriminating compared to NIR.
In a previous work using 1H-NMR we reported encouraging steps towards the construction of a robust expert system for the discrimination of coffees from Colombia versus nearby countries (Brazil and Peru), to assist the recent protected geographical indication granted to Colombian coffee in 2007. This system relies on fingerprints acquired on a 400 MHz magnet and is thus well suited for small scale random screening of samples obtained at resellers or coffee shops. However, this approach cannot easily be implemented at harbour's installations, due to the elevated operational costs of cryogenic magnets. This limitation implies shipping the samples to the NMR laboratory, making the overall approach slower and thereby more expensive and less attractive for large scale screening at harbours. In this work, we report on our attempt to obtain comparable classification results using alternative techniques that have been reported promising as an alternative to NMR: GC-MS and GC-C-IRMS. Although statistically significant information could be obtained by all three methods, the results show that the quality of the classifiers depends mainly on the number of variables included in the analysis; hence NMR provides an advantage since more molecules are detected to obtain a model with better predictions.
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