Authentication of tequilas using pattern recognition and supervised classification

Abstract

Sales of reputed, Mexican tequila grown substantially in last years and, therefore, counterfeiting is increasing steadily. Hence, methodologies intended to characterize and authenticate commercial beverages are a real need. They require a combination of analytical characterization and chemometric tools. This work reports concisely on the former and focus on the chemometric tools employed so far in connection with them. Further, a practical case study presents the classification capabilities of nine supervised classification methods to differentiate white, rested, aged and extra-aged tequilas. The largest set of certified tequilas employed so far was considered. In general, non linear methods performed best than linear ones (accuracy higher than 94% in both training and validation). The case study demonstrates that it is possible to develop fast, cheap, easy to implement and reliable analytical methodologies to authenticate and classify samples of tequilas.

Trends in Chemometrics: Food Authentication, Microbiology, and Effects of Processing

“…The new object x belongs to a class which encompasses most of the k empirically chosen neighbors. An increase in the value of k reduces the impact of errors, whereas its decrease worsens classification (Pérez‐Caballero et al., ; Reinholds, Bartkevics, Silvis, van Ruth, & Esslinger, ). This value is related to the number of neighbors (“votes”) to poll for future classifications, such that k = 1 provides a good classification rule.…”

“…Pérez‐Caballero et al. () applied other techniques to classify different types of tequilas (white, rested, aged, and extra‐aged), using data from UV‐Vis and CG‐MS. They concluded that nonlinear models were best able to classify the tequilas samples.…”

Peer Review #3 of "Visual complexity modelling based on image features fusion of multiple kernels (v0.3)"

“…Machine learning is widely used in several completely different fields; detection of regions of interests, image editing, texture analysis, visual aesthetic and quality assessment (Datta et al, 2006;Marchesotti et al, 2011;Romero et al, 2012;Fernandez-Lozano et al, 2015;Mata et al, 2018) and more recently in Carballal et al (2019b) or for microbiome analysis (Liu et al, 2017;Roguet et al, 2018), authentication of tequilas (Pérez-Caballero et al, 2017;Andrade et al, 2017), pathogenic point mutations (Rogers et al, 2018) or forensic identification (Gómez et al, 2018). Finally, with regard to the extraction of characteristics from images, some recently published works have been revised (Xu et al, 2018;Ali et al, 2016b;Wang et al, 2018;Sun et al, 2018;Zafar et al, 2018b).…”

Identification of Tequila with an Array of ZnO Thin Films: A Simple and Cost-Effective Method

“…Many researchers have reported sophisticated methods that include multiple steps as extraction (e.g., headspace sampling), separation, quantification, high performance liquid chromatography, isotope ratio mass spectrometry, nuclear magnetic resonance coupled with gas chromatography or electronic nose, or Fourier transform infrared spectroscopy (HPLC, IRMS, NMR GC and FTIR respectively), followed by data analysis [ 2 , 3 , 4 , 5 , 6 ]. Other molecular spectrometric analytical techniques such as UV-Vis and Raman spectrometry or chemiluminescence have been applied to tequila analysis [ 7 ]. Less frequently, fluorescence spectroscopy and photoacoustics have also been employed for discriminating fake from real Tequilas [ 7 ].…”

“…Other molecular spectrometric analytical techniques such as UV-Vis and Raman spectrometry or chemiluminescence have been applied to tequila analysis [ 7 ]. Less frequently, fluorescence spectroscopy and photoacoustics have also been employed for discriminating fake from real Tequilas [ 7 ]. Most of these techniques are performed by highly specialized technicians employing bulky and very expensive equipment.…”