Evaluation of ultraviolet, visible, and near infrared spectroscopy for the analysis of wine compounds

Spectroscopy of UV-VIS-NIR combined with chemometric analyses was used as a non-destructive technique to build models for the quantitative characterisation of the main compounds of wine. The work in mixtures can give insight into how interferences affect the performance of calibrations in wines. Ethanol, glycerol, glucose, tartaric acid, malic acid, lactic acid, and acetic acid were evaluated as pure compounds and in mixtures. Different pre-treatments for the spectra and modelling strategies such as partial least squares (PLS) regression or Principal Component Regression (PCR) were evaluated. All pure compounds studied showed a good relationship between spectra and concentrations. However, interferences were observed in the mixtures and only good models for ethanol, tartaric acid, and malic acid were obtained. The best model was obtained in the NIR region for ethanol and in the UV region for tartaric acid and malic acid. The results indicate that NIR spectroscopy could be used as an alternative to conventional chemical methods for ethanol determination and UV spectroscopy for the determination of tartaric acid and malic acidS

Aplicación de redes neurales artificiales acopladas a la espectroscopía UV–VIS–NIR para la rápida cuantificación de compuestos del vino en mezclas acuosas

Ultraviolet–visible (UV–VIS) and near-infrared (NIR) spectroscopy coupled to artificial neural networks (ANNs) was used as a nondestructive technique to quantify ethanol, glucose, glycerol, tartaric acid, malic acid, acetic acid and lactic acid in aqueous mixtures. Spectral data were obtained for 152 samples. Differing pre-treatments were applied to the spectra and ANN models were obtained using raw and pre-treated data to evaluate several spectral wavelength groupings and ANN training conditions. Feasible calibration models were obtained for ethanol, malic acid and tartaric acid. To validate the process, 120 new samples were measured using the best ANN models. The determination coefficients for the three compounds using this validation set were above 0.9. The results showed the importance of good parameter selection when training the ANN to obtain reliable models. Coupling UV–VIS–NIR spectroscopy to ANN could provide an alternative to conventional chemical methods for determining ethanol, tartaric acid and malic acid in winesSe utilizó la espectroscopía ultravioleta-visible (UV–VIS) e infrarroja cercana (NIR) acopladas a redes neurales artificiales (ANN) como técnica no destructiva para cuantificar varias mezclas acuosas de: etanol, glucosa, glicerol, ácido tartárico, ácido málico, ácido acético y ácido láctico. Se obtuvieron datos espectrales de 152 muestras. Se aplicaron distintos tratamientos previos a los espectros resultantes, obteniéndose los modelos ANN a través del uso de datos brutos y de datos tratados previamente para evaluar varios agrupamientos de bandas espectrales y varias condiciones de entrenamiento de las ANN. De esta manera, se obtuvieron modelos de calibración viables para el etanol, el ácido málico y el ácido tartárico. Con el fin de validar el proceso, se midieron 120 muestras adicionales utilizando los mejores modelos de las ANN. Se constató que, usando este conjunto de validación, los coeficientes de determinación de los tres compuestos superaron 0,9. Los resultados demostraron la importancia de contar con una buena selección de parámetros durante el entrenamiento de las ANN con el fin de obtener modelos confiables. La vinculación de la espectroscopía UV–VIS–NIR a las ANN podría ser una alternativa a los métodos químicos convencionales para la determinación de la presencia de etanol, ácido tartárico y ácido málico en los vinosS

Desarrollo de métodos rápidos basados en espectroscopía UV-VIS-NIR para el análisis de vinos

La verificación de la autenticidad de los alimentos en general, y del vino en particular, es una de las aplicaciones potenciales más importantes de la espectroscopía UV-VIS-NIR. Las adulteraciones del vino pueden ser de muchos tipos (adición de azúcar, ácidos o aceites volátiles, redilución de concentrados, adición de zumo de otras frutas, y mezcla con vinos de peor calidad). Algunas de las aplicaciones de la espectroscopía UV-VIS-NIR en vinos que se están estudiando en los últimos años son el análisis de composición de uvas, el análisis de composición de los vinos, verificación de la calidad de los vinos y la verificación de la autenticidad y origen de los vinos. No existe ningún estudio sobre aplicaciones de la espectroscopía UV-VIS-NIR en vinos de las variedades de vid que se cultivan para la elaboración de los vinos gallegos. El objetivo principal de esta tesis fue desarrollar métodos rápidos de análisis que permitan autentificar el origen de vinos gallegos mediante la obtención de espectros UV-VIS-NIR a modo de “huella dactilar” para cada Denominación de Origen (Rías Baixas, Ribeiro, Monterrei, Ribeira Sacra y Valdeorras). Como objetivo secundario se trató de obtener un método rápido de análisis global de la composición de los vinos para etanol, glucosa, glicerol, ácidos orgánicos y compuestos fenólicos basado en los espectros UV-VIS-NIR. Además, se ha obtenido un método para identificar la subzona dentro de una denominación de origen y la composición del vino en cuanto a variedades de vid que se utilizaron en su elaboración. Los resultados obtenidos demuestran la posibilidad de cuantificar la composición de los vinos, clasificar en función de la denominación de origen a la que pertenecen, clasificar en función de la subzona dentro de una misma denominación y clasificar en función de la variedad de uva, utilizando espectroscopía UV-VIS-NIR, combinada con técnicas quimiométricas de clasificación y cuantificación, como técnicas rápidas y de bajo coste

Food Authentication: Techniques, Trends and Emerging Approaches

Multiple factors can directly influence the chemical composition of foods and, consequently, their organoleptic, nutritional, and bioactive properties, including their geographical origin, the variety or breed, as well as the conditions of cultivation, breeding, and/or feeding, among others. Therefore, there is a great interest in the development of accurate, robust, and high-throughput analytical methods to guarantee the authenticity and traceability of foods. For these purposes, a large number of sensorial, physical, and chemical approaches can be used, which must be normally combined with advanced statistical tools. In this vein, the aim of the Special Issue “Food Authentication: Techniques, Trends, and Emerging Approaches” is to gather original research papers and review articles focused on the development and application of analytical techniques and emerging approaches in food authentication. This Special Issue comprises 12 valuable scientific contributions, including one review article and 11 original research works, dealing with the authentication of foods with great commercial value, such as olive oil, Iberian ham, and fruits, among others

The impact of chemometrics on food traceability

In the last decades, mankind has become totally aware about the importance of food quality: nowadays authentication and traceability are words of general use. Food authentication verifies how much a food is in accordance with its label description and law and it could be considered a further guarantee for the quality and safety of a foodstuff. The traceability of food could be considered an essential element in ensuring safety and high quality of food. The synergistic use of instrumental analytical techniques and chemometrics represents a promising way to obtain trustworthy results in the development of authenticity and traceability models. This chapter deals with the potentialities of chemometrics tools in resolving some real issues related to food traceability and authenticity. Particular attention will be paid to the use of some exploratory, classification and discrimination techniques. In the first part of this chapter, a briefly description of European regulations (Authenticity and Traceability: the European Union point of view), and traceability and authenticity markers (Authenticity and Traceability: a scientific point of view) is reported. The second part is split into two sections: namely Food Authenticity and Food Traceability applications, where the main features and advantages of some chemometrics approaches are presented

Detection of adulterations in fruit juices using machine learning methods over FT-IR spectroscopic data

Fruit juices are one of the most adulterated beverages, usually because of the addition of water, sugars, or less expensive fruit juices. This study presents a method based on Fourier transform infrared spectroscopy (FT-IR), in combination with machine learning methods, for the correct identification and quantification of adulterants in juices. Thus, three types of 100% squeezed juices (pineapple, orange, and apple) were evaluated and adulterated with grape juice at different percentages (5%, 10%, 15%, 20%, 30%, 40%, and 50%). The results of the exploratory data analysis revealed a clear clustering trend of the samples according to the type of juice analyzed. The supervised learning analysis, based on the development of models for the detection of adulteration, obtained significant results for all tested methods (i.e., support-vector machines or SVM), random forest or RF, and linear discriminant analysis or LDA) with an accuracy above 97% on the test set. Regarding quantification, the best results are obtained with the support vector regression and with partial least square regression showing an R2 greater than 0.99 and a root mean square error (RMSE) less than 1.4 for the test setPeer ReviewedPostprint (published version

UV-Vis spectroscopy method for authentication studies on olive oils and vinegars

This research project addresses three independent studies that are related to the authentication of olive oil and sherry wine vinegar through the usage of UV-Vis spectroscopy. In the first study, an adulteration study was carried out in olive oils by using colored vegetable oils with natural colorants.. Two different procedures were developed aiming at detecting the falsification. The second study presents a novel method based on the standard deviation of normalized spectra at adequate wavelengths. This method has provided an accurate resolution of spectra at individual components in a two-component system which can be used for multicomponent systems with bigger sizes. The method then was effectively applied to different olive oil sets. Finally, the third study was performed in order to determine the characterization of sherry wine vinegars. For the first time, chromatic parameters were used for characterizing sherry wine vinegar according to the type of the wine used and the acetification process followed during the elaboration process. Once again, the results were satisfactory. The UV-Vis spectroscopic technique has been proven to be a versatile tool for a rapid and nondestructive analysis in oil and vinegar samples based on the study of their spectra

Simplified method for the screening of technological maturity of red grape and total phenolic compounds of red grape skin: Application of the characteristic vector method to near-infrared spectra

Characteristic vector analysis has been applied to near-infrared spectra to extract the main spectral information from hyperspectral images. For this purpose, 3, 6, 9, and 12 characteristic vectors have been used to reconstruct the spectra, and root-mean-square errors (RMSEs) have been calculated to measure the differences between characteristic vector reconstructed spectra (CVRS) and hyperspectral imaging spectra (HIS). RMSE values obtained were 0.0049, 0.0018, 0.0012, and 0.0012 [log(1/R) units] for spectra allocated into the validation set, for 3, 6, 9, and 12 characteristic vectors, respectively. After that, calibration models have been developed and validated using the different groups of CVRS to predict skin total phenolic concentration, sugar concentration, titratable acidity, and pH by modified partial least-squares (MPLS) regression. The obtained results have been compared to those previously obtained from HIS. The models developed from the CVRS reconstructed from 12 characteristic vectors present similar values of coefficients of determination (RSQ) and standard errors of prediction (SEP) than the models developed from HIS. RSQ and SEP were 0.84 and 1.13 mg g−1 of skin grape (expressed as gallic acid equivalents), 0.93 and 2.26 °Brix, 0.97 and 3.87 g L−1 (expressed as tartaric acid equivalents), and 0.91 and 0.14 for skin total phenolic concentration, sugar concentration, titratable acidity, and pH, respectively, for the models developed from the CVRS reconstructed from 12 characteristic vector

Exploring 1H NMR relaxometry for wine traceability and authenticity assessment

Mestrado em Engenharia de Viticultura e Enologia (Double degree) / Instituto Superior de Agronomia. Universidade de Lisboa / Faculdade de Ciências. Universidade do PortoThe development of analytical methodologies for wine authenticity assessment is one of the most challenging issues for the scientific community. In this study, the potential analytical applications of 1H NMR relaxometry, in view to wine authenticity investigation, were explored. For that, proton longitudinal relaxation rate dispersions in the range 0.04-300 MHz were investigated in three white and three red varietal wines from Tapada da Ajuda (Lisbon), obtained from Vitis vinifera L. grape varieties, namely Alvarinho, Arinto, Cabernet Sauvignon, Moscatel Graúdo, Touriga Nacional and Trincadeira, from vintages 2008 and 2017 for a total of twelve bottles. To evaluate rain as an environmental source of variability pluviometric data were considered. Dispersions associable to the presence of paramagnetic ions were observed at low frequencies but the results for wine iron content cannot explain the effect. Correlations between the wine characters and the areas drawn by the most representative relaxometry models show an effect of alcoholic strength by volume, glycerol and total dry matter suggesting wine viscosity to modulate relaxivity. To the best of our knowledge, for the first time wine physical-chemical characteristics and glycerol content have been compared to NMR relaxation rate profiles. To investigate the paramagnetic relaxation and evaluate the relaxation associated to wine hydro-alcoholic matrix, water-ethanol mixtures were tested, and linear regressions were obtained. Comparing the results with bibliographic sources, the paramagnetic enhancement on relaxation profiles was associated to the presence of manganese(II), but no parameters have been fitted from the models. The dispersions highlighted possible cross relaxations in the 1.5-6 MHz frequency range. The presence of nitrogen diluted into the wine could explain this behaviour. To inspect how each physical-chemical parameter impacts on wine relaxation profiles the knowledge of manganese content is crucialN/