Multiway Processing of Data Generated with a Potentiometric Electronic Tongue in a SIA System

Bioelectronic tongues: New trends and applications in water and food analysis

Over the last years, there has been an increasing demand for fast, highly sensitive and selective methods of analysis to meet new challenges in environmental monitoring, food safety and public health. In response to this demand, biosensors have arisen as a promising tool, which offers accurate chemical data in a timely and cost-effective manner. However, the difficulty to obtain sensors with appropriate selectivity and sensitivity for a given analyte, and to solve analytical problems which do not require the quantification of a certain analyte, but an overall effect on a biological system (e.g. toxicity, quality indices, provenance, freshness, etc.), led to the concept of electronic tongues as a new strategy to tackle these problems. In this direction, to improve the performance of electronic tongues, and thus to spawn new application fields, biosensors have recently been incorporated to electronic tongue arrays, leading to what is known as bioelectronic tongues. Bioelectronic tongues provide superior performance by combining the capabilities of electronic tongues to derive meaning from complex or imprecise data, and the high selectivity and specificity of biosensors. The result is postulated as a tool that exploits chemometrics to solve biosensors' interference problems, and biosensors to solve electronic tongues' selectivity problems. The review presented herein aims to illustrate the capabilities of bioelectronic tongues as analytical tools, especially suited for screening analysis, with particular emphasis in water analysis and the characterization of food and beverages. After briefly reviewing the key concepts related to the design and principles of electronic tongues, we provide an overview of significant contributions to the field of bioelectronic tongues and their future perspectives.

A combination of dynamic measurement protocol and advanced data treatment to resolve the mixtures of chemically similar analytes with potentiometric multisensor system

Data processing techniques and measuring protocol are very important parts of the multisensor systems methodology. Complex analytical tasks like resolving the mixtures of two components with very similar chemical properties require special attention. We report on the application of non-linear (artificial neural networks, ANNs) and linear (projections on latent structures, PLS) regression techniques to the data obtained from the flow cell with potentiometric multisensor detection of neighouring lanthanides in the Periodic System of the elements (samarium, europium and gadolinium). Quantification of individual components in mixtures is possible with reasonable precision if dynamic components of the response are incorporated thanks to the use of an automated sequential injection analysis system. The average absolute error in prediction of lanthanides with PLS was around 1 × 10(-4)mol/L, while the use of ANNs allows the lowering of prediction errors down to 2 × 10(-5)mol/L in certain cases. The suggested protocol seems to be useful for other analytical applications where simultaneous determination of chemically similar analytes in mixtures is required.

A solid-contact ion selective electrode for copper(II) using a succinimide derivative as ionophore

All-solid-state sensors with polyvinyl chloride (PVC)-based membranes using off-the-shelf N-hydroxysuccinimide (NHS) and succinimide (Succ) ionophores were prepared using DOP (dioctyl phthalate) and NPOE (ortho-nitrophenyloctyl ether) as plasticizers. Good responses were obtained when NHS was used. The potentiometric response of the proposed electrode is independent of pH over the range 2-6. The electrode shows a fast response time of 0.25 s. The electrode exhibits a Super-Nernstian response, with 37.5 mV/decade, with a potentiometric detection limit of 4.4 µM. The proposed sensor revealed good selectivity towards a group of transition metal ions.