Chemical Typification of the Sugarcane Spirits Produced in São Paulo State

Serafim, Felipe Augusto Thobias; Reche, Roni Vicente; Franco, Douglas Wagner

doi:10.1111/1750-3841.13013

Cited by 3 publications

(1 citation statement)

References 32 publications

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“…Chemometric approaches e.g., principal component analysis (PCA), 17 partial least squares (PLS), 18 linear discriminant analysis (LDA), 19 genetic algorithm, 20 and successive projections algorithm (SPA) 21 permit the processing of large amounts of spectroscopic data variables that subsequently require data reduction approaches in order to identify sources of variance across spectra and inter-class variation. Indeed, the NIR technique has been used to discriminate alcoholic beverages, e.g., wine produced in different geographic regions 22,23 and to predict and quantify chemical components in food, 24 the wine industry, [25][26][27] and in the beer industry. 28 Considering the possibilities of NIR spectroscopy, the objective of this study was to develop a non-destructive method using NIR spectroscopy and chemometric tools to validate the authenticity of sugarcane aguardentes produced in two geographic regions (São Paulo and Minas Gerais states), as well as to predict the ethanol content in both spirits, aiming for this method to be used as an analytical tool to evaluate fraud and validate the authenticity of these spirits.…”

Section: Introductionmentioning

confidence: 99%

Determination of the geographical origin and ethanol content of Brazilian sugarcane spirit using near-infrared spectroscopy coupled with discriminant analysis

et al. 2016

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18Aguardente is a typical Brazilian spirit produced by the distillation of sugarcane most. The 19 valorisation of this spirit can be attributed to its notoriety, related to the production origin which can 20 influence its quality. Therefore, the objective of this study was to use NIR spectroscopy coupled with 21 discriminant analysis as a non-destructive method to attribute authenticity of aguardentes produced 22 in two geographic regions and to predict the ethanol content. Some chemometric methods were used 23 to discriminate sugarcane aguardente, namely partial least squares-linear discriminant analysis 24 (PLS-LDA), principal component analysis-linear discriminant analysis (PCA−LDA), and variable 2 selection techniques such as successive projection algorithm (SPA−LDA) and genetic algorithm 26 (GA−LDA). NIR spectra were collected using a FT−NIR spectrometer (4,000-10,000 cm -1 ) at a 27 spectral resolution of 16 cm -1 , 8 cm -1 interval, and 64 scans. PCA results were not effective to classify 28 the aguardente samples, but with PLS−DA, PCA−LDA, SPA−LDA, GA−LDA and LDA it was 29 possible to get 87.2% prediction accuracy. Better results were obtained using PLS−DA on raw 30 spectra and GA-LDA using only six wavelengths (namely, 1,025 nm, 1,181 nm, 1,596 nm, 1,610 nm, 31 1,653 nm, 2,125 nm) which gave relatively good accuracy rate (up to 87.2 %). NIR spectroscopy and 32 chemometrics can be used as a non-destructive method to attribute authenticity, and PLSR combined 33 with NIR was a good non-destructive method to predict ethanol content in sugarcane aguardente. 34 35 while the Minas Gerais State is the main alembic producer, both representing 25% of the Brazilian 46 market 3 . In the alembic production of sugarcane spirit the product is divided into three fractions: 47 head, heart, and tail, while in column distillation there is no such separation into fractions and that 48 explains to a range extent the chemical differences produced by the two processes 4 . 49

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