A different approach for the analysis of grapes: Using the skin as sensing element

Abstract

In this work, an alternative method to monitor the phenolic maturity of grapes was developed. In this approach, the skins of grapes were used to cover the surface of carbon paste electrodes and the voltammetric signals obtained with the skin-modified sensors were used to obtain information about the phenolic content of the skins. These sensors could easily detect differences in the phenolic composition of different Spanish varieties of grapes (Mencía, Prieto Picudo and Juan García). Moreover, sensors were able to monitor changes in the phenolic content throughout the ripening process from véraison until harvest. Using PLS-1 (Partial Least Squares), correlations were established between the voltammetric signals registered with the skin-modified sensors and the phenolic content measured by classical methods (Glories or Total Polyphenol Index). PLS-1 models provided additional information about Brix degree, density or sugar content, which usually used to establish the harvesting date. The quality of the correlations was influenced by the maturation process and the structural and mechanical skin properties. Thus the skin sensors fabricated with Juan García and Prieto Picudo grapes (that showed faster polyphenolic maturation and a higher amount of extractable polyphenols than Mencía), showed good correlations and therefore could be used to monitor the ripening.

Analysis of red wines using an electronic tongue and infrared spectroscopy. Correlations with phenolic content and color parameters

“…Thus, this increase is well correlated to the decrease of the phenolic content observed in TPI and Folin-Cioacalteu, (as well as in the "red parameters" of Glories and CIELab analysis) that occurs during the aging process in oak barrels where micro-oxygenation reduces the total content of low molecular weight phenolic compounds as a result of condensation reactions and increases the polymeric polyphenols which stabilize wine color (Behrends & Weber, 2017). This effect has already been observed in e-tongues used to analyze grape skins (Muñoz et al, 2018).…”

“…Data pre-processing has been done based on a compression method described by Gutierrez-Osuna & Nagle (1999). Voltammogram curves were multiplied by 10 smooth and bell-shaped windowing function (8) while infrared spectra were multiplied by 30 smooth and bell-shaped windowing function (8) (Gutierrez-Osuna & Nagle, 1999, Medina-Plaza et al, 2016Muñoz et al, 2018). ( 8) where a i , b i and c i define the width, shape and center of the different windowing functions K i , x j is the x-variable, for voltammetric data is the voltage while for infrared spectra is the frequency in wavenumbers.…”

Discrimination of Milks with a Multisensor System Based on Layer-by-Layer Films

“…The multivariate data analysis was performed by using MATLAB R2014b (The Mathworks Inc., Natick, MA, USA). The principal component analysis (PCA) was carried out using, as input data source, pre-processed voltammograms obtained by the adaptation of a data reduction technique based on predefined response “bell-shaped-windowing” curves called “kernels” [ 38 , 39 ]. Using this method, voltammograms were multiplied by 10 smooth, bell-shaped windowing functions, defined as where a i , b i , and c i define the width, shape, and center of the different windowing functions, K i .…”

Multisensor System Based on Layer by Layer Films. Discrimination of Milks

“…The multivariate data analysis was performed by using MATLAB R2014b (The Mathworks Inc., Natick, MA, USA). The Principal Component Analysis (PCA) was carried out using as input data source pre-processed voltammograms obtained by the adaptation of a data reduction technique based on predefined response "bell-shaped-windowing" curves called "kernels" [33,34]. Using this method, voltammograms were multiplied by 10 smooth, bell-shaped windowing functions defined as:…”