Discrimination of Cheddar, Kefalotyri, and Halloumi cheese samples by the chemometric analysis of Fourier transform infrared spectroscopy and proton nuclear magnetic resonance spectra

Discrimination of dairy products can be carried out through a number of chemical methods. The aim of this study was to discriminate the samples of Cheddar, Kefalotyri, and Halloumi cheese by analyzing various samples, from different brands. In this way, we hoped to be able to underline the unique identity of Halloumi cheese, by building a robust model to determine any Halloumi cheese replacements in food products. A total of 102 samples were used, including 14 Cheddar samples, 14 samples of Kefalotyri cheese, and 74 Halloumi cheese samples. Two spectroscopic techniques proton nuclear magnetic resonance and Fourier transform infrared spectroscopy were chosen to obtain chemical analytical data. The data were analyzed using SIMCA software. OPLS-DA was the principal chemometric method applied, as well as multiblock orthogonal component analysis. In the context of data fusion, the spectroscopic techniques used here, along with chemometrics allow the discrimination of those three types of cheese. Both spectroscopic techniques employed are significant, since they provide information about good classification of the samples when they are combined together. Interpretation of results and classification by using chemometric methods confirmed the different recipe of the three types of cheese. Practical Applications Food adulteration is a significant issue even where there is no direct effect on public health as it affects the income of the manufacturers as well as of the source materials used in the production of the final product. Halloumi cheese is very popular not only in Cyprus, but also throughout Europe. Adulteration of the product by milk with species origin other than those in the standard in common. The analysis protocol we describe in this publication is fast and easy to use and provides a useful tool to detect adulteration for producers and competent supervising authorities.