Overview of Analytical Techniques Associated with Pattern Recognition Methods in Sugarcane Spirits Samples

The Spirit of Cachaça Production: An Umbrella Review of Processes, Flavour, Contaminants and Quality Improvement

This review provides a comprehensive analysis of the production, classification, and quality control of cachaça, a traditional Brazilian sugarcane spirit with significant cultural importance. It explores the fermentation and distillation of sugarcane juice, the ageing process in wooden containers, and the regulatory aspects of cachaça labelling. It emphasises the role of quality control in maintaining the spirit's integrity, focusing on monitoring copper levels in distillation stills. Ethyl carbamate (EC), a potential carcinogen found in cachaça, is investigated, with the study illuminating factors influencing its formation and prevalence and the importance of its vigilant monitoring for ensuring safety and quality. It also underscores the control of multiple parameters in producing high-quality cachaça, including raw material selection, yeast strains, acidity, and contaminants. Further, the impact of ageing, wood cask type, and yeast strains on cachaça quality is examined, along with potential uses of vinasse, a cachaça by-product, in yeast cell biomass production and fertigation. A deeper understanding of the (bio)chemical and microbiological reactions involved in cachaça production is essential to facilitate quality control and standardisation of sensory descriptors, promoting global acceptance of cachaça. Continued research will address safety concerns, improve quality, and support the long-term sustainability and success of the cachaça industry.

A green method for the authentication of sugarcane spirit and prediction of density and alcohol content based on near infrared spectroscopy and chemometric tools

Cachaça is a Brazilian beverage obtained from the fermentation of sugarcane juice (sugarcane spirit) and is considered one of the most consumed alcoholic beverages in the world with a strong economic impact on the northeastern Brazil, more specifically in the Brejo. This microregion produces sugarcane spirits with high quality associated to edaphoclimatic conditions. In this sense, analysis for sample authentication and quality control that uses solvent-free, environmentally friendly, rapid and non-destructive methods is advantageous for cachaça producers and production chain. Thus, in this work commercial cachaça samples using near-infrared spectroscopy (NIRS) were classified based on geographical origin using one-class classification Data-Driven in Soft Independent Modelling of Class Analogy (DD-SIMCA) and One-Class Partial Least Squares (OCPLS) and predicted quality parameters of alcohol content and density based on different chemometric algorithms. A total of 150 sugarcane spirits samples were purchased from the Brazilian retail market being 100 from Brejo and 50 from other regions of Brazil. The one-class chemometric classification model was obtained with DD-SIMCA using the Savitzky-Golay derivative with first derivative, 9-point window and 1st degree polynomial as preprocessing algorithm and sensibility was 96.70 % and specificity 100 % in the spectral range 7,290-11,726 cm^-1. Satisfactory results were obtained in the model constructs for density and the chemometric model, iSPA-PLS algorithm with baseline offset as preprocessing, obtained root mean square errors of prediction (RMSEP) of 0.0011 mg/L and Relative Error of Prediction (REP) of 0.12 %. The chemometric model for alcohol content prediction used the iSPA-PLS algorithm with Savitzky-Golay derivative with first derivative, 9-point window and 1st degree polynomial as algorithm as preprocessing obtaining RMSEP and REP of 0.69 and 1.81 % (v/v), respectively. Both models used the spectral range from 7,290-11,726 cm^-1. The results reflected the potential of vibrational spectroscopy coupled with chemometrics to build reliable models for identifying the geographical origin of cachaça samples for predicting quality parameters in cachaça samples.

Using a biphasic system and digital imaging analysis with chemometric tools for simultaneous determination of Cu2+ and furfural in cachaça

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.

A fast and low-cost approach for the discrimination of commercial aged cachaças using synchronous fluorescence spectroscopy and multivariate classification

BACKGROUND

Cachaça is the distilled beverage typical of Brazil and can be subjected to the aging process in wooden barrels. In addition to oak barrels, cachaça is also aged in barrels of different Brazilian native woods, resulting in a wide variety of its sensory characteristics. In this work, 172 cachaças aged in bálsamo, jequitibá, oak, and umburana barrels were analyzed by synchronous fluorescence spectroscopy and by the classification methods of principal component analysis and partial least squares discriminant analysis. Spectra were preprocessed by the first derivative by Savitzky-Golay smoothing, using a filter width and polynomial order determined through face-centered central composite designs. Multivariate analysis was realized using the spectra recorded at different wavelength differences, and models were compared by the classification errors in the test sets.

RESULTS

The principal component analysis applied to the synchronous fluorescence spectra presented a tendency of separation by the wood used in the aging process, and the partial least squares discriminant analysis model constructed using the fluorescence spectra recorded at a wavelength difference of 30 nm provided better performance parameters (efficiency 91-97%, sensitivity 81-100%, and specificity 91-100%).

CONCLUSION

Synchronous fluorescence spectroscopy offers a promising approach for the classification of cachaças aged in bálsamo, oak, jequitibá, and umburana barrels, and the discriminant model can be used for routine analysis as a screening method. © 2022 Society of Chemical Industry.

Synchronous fluorescence spectroscopy and multivariate classification for the discrimination of cachaças and rums

Although cachaça and rum are distilled beverages obtained from the same raw material, they present differences in their chemical compositions. In this study, synchronous fluorescence spectroscopy was used combined with supervised classification models based on the partial least squares discriminant analysis to develop a rapid and low-cost model for discriminating between 50 cachaça and 40 rum samples. Partial least squares discriminant analysis models were constructed using synchronous fluorescence spectra recorded at wavelength differences of 10-100 nm. Initially, spectra were preprocessed by the first derivative with the Savitzky-Golay smoothing, and filter width and polynomial order were selected through face-centered central composite designs. For the construction and validation models, the spectra data were split into two datasets: the training and the test sets containing 60 (C, n = 33; R, n = 27) and 30 (C, n = 17; R, n = 13) samples, respectively. The best discrimination was achieved using fluorescence spectra recorded at wavelength difference 10 nm, allowing the discrimination of cachaça and rum with a classification efficiency of 98%. These results indicate that synchronous fluorescence spectroscopy offers a promising approach for the authentication of cachaças and rums.

Kurtosis-based projection pursuit analysis to evaluate South American rapadura

Rapadura is an artisanal candy obtained from concentrated sugarcane juice. In this study, a differentiation between South American rapadura producers has been tried using a Kurtosis-based projection pursuit analysis (kPPA) concerning essential minerals, acrylamide, moisture contents, pH, and color. These parameters revealed significant inter- and intra-country differences. Based on the employed measurements, a multivariate exploration with kPPA extracted information from rapadura even though it is a very artisanal product and was effective in separating classes, especially Brazilian and Ecuadorian rapadura, where principal component analysis failed. Moreover, ellipse confidence regions showed significant differences between non-organic and organic rapadura from Colombia and Peru in granulated form. From a chemometric point of view, the application of kPPA can be used in cases when other metrics (as based on the variance) fail and can be useful in the exploratory analysis of complex multivariate chemical data.

Multidimensional capillary liquid chromatography-tandem mass spectrometry for the determination of multiclass pesticides in "sugarcane spirits" (cachaças)

Cachaça or "sugarcane spirit" is a Brazilian beverage considered the third most consumed beverage worldwide. Sugarcane, its raw material, is one of the main crops developed in the country, placing Brazil as the largest producer of this commodity on a global scale. Considering the growth in sugarcane production, many farmers use pesticides in their crops. However, excess pesticides can be accumulated in products derived from sugarcane, creating an environmental and public health concern. In this context, the development of analytical methods capable of identifying residues of pesticides in cachaças and other sugarcane-derived products is essential to ensure the beverage's quality. This work presents a method to quantify multiclass pesticides in Brazilian sugarcane spirits (cachaças) through an automated multidimensional system. The first dimension consists of an extraction column packed with a graphene-silica phase, followed by a capillary liquid chromatography-tandem mass spectrometry system as the second dimension. The method was optimized by an experimental design, in which the influence of three variables was evaluated on the extraction process: percentage of acetonitrile, loading flow, and loading time. Afterward, twenty-two cachaças were analyzed to ascertain the applicability of the proposed method. The analyses reported five samples containing clomazone (a type of herbicide widely used in sugarcane production). The method showed good linearity under optimized conditions, with correlation coefficients greater than 0.981, and limits of detection and quantification of 5 μg L^-1 and 10 μg L^-1, respectively. The herein discussed results suggest that the proposed method could be a practical option for identifying pesticides in beverages. Graphical Abstract.