Edible olive drupes (from Olea europaea L.) are a high-value food commodity with an increasing production trend over the past two decades. In an attempt to prevent fraud issues and ensure quality, the International Olive Council (IOC) issued guidelines for their sensory evaluation. However, certain varieties, geographical origins and processing parameters are omitted. The aim of the present study was the development of a method for the quality assessment of edible olives from the Konservolia, Kalamon and Chalkidikis cultivars from different areas of Greece processed with the Spanish or Greek method. A rapid NMR-based untargeted metabolic profiling method was developed along with multivariate analysis (MVA) and applied for the first time in edible olives’ analysis complemented by the aid of statistical total correlation spectroscopy (STOCSY). Specific biomarkers, related to the classification of olives based on different treatments, cultivars and geographical origin, were identified. STOCSY proved to be a valuable aid towards the assignment of biomarkers, a bottleneck in untargeted metabolomic approaches.

Extra virgin olive oil (EVOO) possesses a high-value rank in the food industry, thus making it a common target for adulteration. Hence, several methods have been essentially made available over the years. However, the issue of authentication remains unresolved with national and food safety organizations globally struggling to regulate and control its market. Over the course of this study, the aim was to determine the origin of EVOOs suggesting a high-throughput, state-of-the-art method that could be easily adopted. A rapid, NMR-based untargeted metabolite profiling method was applied and complemented by multivariate analysis (MVA) and statistical total correlation spectroscopy (STOCSY). STOCSY is a valuable statistical tool contributing to the biomarker identification process and was employed for the first time in EVOO analysis. Market samples from three Mediterranean countries of Spain, Italy, and Greece, blended samples from these countries, as well as monocultivar samples from Greece were analyzed. The NMR spectra were collected, with the help of chemometrics acting as “fingerprints” leading to the discovery of certain chemical classes and single biomarkers that were related to the classification of the samples into groups based on their origin.

Honey is a natural, healthy commodity and is probably among the most complex foods produced by nature. It is the oldest recorded and certainly the only natural sweetener that can be used by humans without any further processing. Nowadays, the increase in honey’s value, along with its growing list of healthy attributes, has made the present raw material a prime target for adulteration. In the current study, NMR-based metabolite profiling in combination with chemometrics was applied in the quality control of Greek honeys from northeastern Aegean islands. Moreover, statistical total correlation spectroscopy (STOCSY) was employed for the first time as a dereplication and structural elucidation tool in the honey biomarker identification process. A total of 10 compounds were successfully identified in honey total extracts via ¹H NMR spectroscopy. Compounds such as 5-(hydroxymethyl)furfural, methyl syringate, a mono-substituted glycerol derivative and 3-hydroxy-4-phenyl-2-butanone, among others, were identified as potential biomarkers related to the botanical and geographical origin of the samples. High-Resolution Mass Spectrometry (HRMS) was used as an additional verification tool on the identified compounds.