Array of biosensors for discrimination of grapes according to grape variety, vintage and ripeness

Abstract

A bioelectronic tongue based on nanostructured biosensors specific for the simultaneous detection of sugars and phenols has been developed. The array combined oxidases and dehydrogenases immobilized on a lipidic layer prepared using the Langmuir-Blodgett technique where Glucose oxidase, D-Fructose dehydrogenase, Tyrosinase or Laccase were imbibed. A phthalocyanine was co-immobilized in the sensing layer and used as electron mediator. The array thus formed has been used to analyze grapes and provides global information about the samples while providing specific information about their phenolic and their sugar content. Using Principal Component Analysis (PCA) the array of voltammetric biosensors has been successfully used to discriminate musts prepared from different varieties of grapes (Tempranillo, Garnacha, Cabernet-Sauvignon, Prieto Picudo and Mencía). Differences could be also detected between grapes of the same variety and cultivar harvested in two successive vintages (2012 and 2013).Moreover, the ripening of grapes could be monitored from veraison to maturity due to the changes in their phenolic and sugar content. Using Partial Least Squares (PLS-1) analysis, excellent correlations have been found between the responses provided by the array of biosensors and classical parameters directly related to phenols (total polyphenol index, TPI) and sugar concentration (degree Brix) measured by chemical methods with correlation coefficients close to 1 and errors close to 0. It is also worthy to notice the good correlations found with parameters associated with the pH and acidity that can be explained by taking into account the influence of the pH in the oxidation potentials of the phenols and in the enzymatic activity. This bioelectronic tongue can assess simultaneously the sugar and the phenolic content of grapes and could be used to monitor the maturity of the fruit and could be adapted easily to field analysis.