Multivariate Optimization of Electrochemical Biosensors for the Determination of Compounds Related to Food Safety-A Review.

We summarize the application of multivariate optimization for the construction of electrochemical biosensors. The introduction provides an overview of electrochemical biosensing, which is classified into catalytic-based and affinity-based biosensors, and discusses the most recent published works in each category. We then explore the relevance of electrochemical biosensors for food safety analysis, taking into account analytes of different natures. Then, we describe the chemometrics tools used in the construction of electrochemical sensors/biosensors and provide examples from the literature. Finally, we carefully discuss the construction of electrochemical biosensors based on design of experiments, including the advantages, disadvantages, and future perspectives of using multivariate optimization in this field. The discussion section offers a comprehensive analysis of these topics.

Development of a voltammetric electronic tongue for the simultaneous determination of synthetic antioxidants in edible olive oils.

A voltammetric electronic tongue (E-tongue) is "a multisensor system, which consists of a number of low-selective sensors and uses advanced mathematical procedures for signal processing based on pattern recognition and/or data multivariate analysis such as artificial neural networks (ANNs), principal component analysis (PCA), among others". Thus, E-tongues in combination with chemometrics tools result in more accurate and selective analytical methods. In this work, we report results of a simple and reliable electroanalytical method to determine butyl hydroxyanisole (BHA), butyl hydroxytoluene (BHT) and propyl gallate (PG) in edible olive oils (EOO). Therefore, the square wave voltammetry (SWV) was used on platinum and carbon fiber disk ultramicroelectrodes (E-tongue configuration) combined with chemometrics tools to perform these studies. On the other hand, two data fusion strategies were used in order to combine electrochemical data obtained for each working electrode in the E-tongue: low-level data fusion (LLDF) and mid-level data fusion (MLDF). In addition, to reduce the dimensionality of the dataset in MLDF, the discrete wavelet transform (DWT) was used. Finally, to assert the predictive capability of the method for BHA, BHT, and PG determination in real samples, a recovery study for the antioxidants in EOO samples was performed, demonstrating the analytical accuracy of the proposed method. Moreover, from the comparison between the proposed electrochemical method with the AOAC reference method and others found in the literature in terms of the quality of the model (REP %) and the percent recovery assays (%) in different samples, our results were better than other reported previously for the simultaneous determination of BHA, BHT, and PG in real samples. Moreover, the percent recovery assays obtained with the proposed electrochemical method were in good agreement with those obtained by the chromatographic method.