Data Fusion for Food Authentication. Combining near and Mid Infrared to Trace the Origin of Extra Virgin Olive Oils

Abstract

Introduction I n recent years, food authentication and food traceability have emerged as issues of primary and common concern for both consumers and producers. Because of this, the number of researchers who tackle these problems by combining chemometrics coupled with a fingerprinting technique continues to increase. This kind of approach, indeed, has the undeniable advantage of allowing, in many cases, the use of rapid and relatively inexpensive analytical techniques that can, nonetheless, lead to reliable and accurate results. Among these analytical methods, an important role is played by the spectroscopic techniques and in particular in the infrared wavelength ranges. These are often chosen as the ideal analytical methods for the development of food quality control methodologies because of their inherent characteristics of non-destructivity, speed and cheapness of analysis, as well as not needing any sample pre-treatment. However, food quality control, in particular when traceability and authentication are concerned, is a complex problem for the chemist, and sometimes the acquisition of a single fingerprinting signal and the subsequent construction of a chemometric classification model is not enough to develop a methodology reliable enough for the intended purpose. In such cases, it is often possible to rely on the possibility of acquiring more than one single signal for each sample, and then to use the combined information from the two (or more) techniques to develop the final chemometric model. In this way, it is possible, sometimes, to benefit from the specific advantages and characteristics of the different techniques to create a more reliable and stable final model, in particular whenever there is complementarity between the information provided by the techniques employed. In these cases, however, the problem of how to combine the different information coming from the various analytical methods, namely the data fusion issue, is of major importance for the accuracy and reliability of the final results of the proposed methodology. In this context, the use of near infrared (NIR) and mid infrared (MIR) spectroscopy to solve authentication or traceability issues has already been described by many researchers, showing the great potential that both these techniques have in the field of food quality control analysis. Moreover, the peculiar characteristics of NIR and MIR, being different from one another, make them perfectly adaptable to being used together. Due to its greater molecular selectivity, the use of MIR spectroscopy often provides easier spectral interpretation than NIR, and it can sometimes be more related to some compound that is typical of the investigated food. NIR spectroscopy is more useful for its peculiarity of giving an overall fingerprint of the entire sample and it is commonly applied for the analysis of foods with excellent results. In this work, the problem of the traceability of extra virgin olive oils coming from the PDO Sabina (Italy), already tackled by the same authors by means of MIR and NIR spectroscopy separately, is handled by means of different strategies of data fusion, in order to improve the results obtained from the two techniques and to demonstrate the synergistic effect of coupling information obtained from the two wavelength regions.