## 1 Introduction  
A major concern of the food sector and research community nowadays is to find the most appropriate strategy to authenticate foods. The term authentication is rather complicated. It involves the botanical and geographical origin determination of foods using specific compositional criteria and properties [1]. Products with a specific composition and origin demand a higher price in the international market. For example, there are over 6500 scientific papers dealing with honey worldwide [2; 3; 4; 5; 6]. _Apis mellifera_ honeybees produce citrus honey when beekeepers place the beehives in citrus grows during the blossom period. The citrus nectariferous species involved dynamically in the production of citrus honey are ranges (_Citrus sinensis_ L.), followed by bitter orange (_Citrus bigaradia_ L.), tangerines (_Citrus tangerina_ or _Citrus reticulata_), and lemons (_Citrus limon_ L.). This type of honey has some special characteristics. These include its intense aroma, mild flavor, light amber color, and quick crystallization. Some statistics about the production rate show that this type of honey accounts for 10% of the annual honey production in Greece. Important amounts of citrus honey are also produced in Italy, Spain, Mexico, France, the USA, Israel, Egypt, and Morocco [5]. The percentage of pollen grains in citrus honey is often under-represented, and therefore is practically impossible to use only pollen data as a measure of the typification of citrus honey. This is supported by a wide range of pollen grain percentage reported for European and Mediterranean citrus honey (ca. 2-42%) [2; 5; 6]. In this context, physicochemical parameter analysis (electrical conductivity, pH, ash, acidity, minerals, sugars, volatile compounds, flavonoids, etc. ), especially in the form of \"physicochemical markers\", identified using multivariate statistics, sensory analysis, or the correlation of citrus pollen grains with volatile compounds, are adopted by the research community to deeper characterize this type of honey [3; 4; 5; 6; 7; 8; 9; 10; 11]. The solid-phase microextraction (SPME) technique was first introduced by [PERSON] [12]. Until then, numerous studies were carried out on foods regarding determination of volatile compounds, including honey, which is rather a complicated matrix. The technical nature of SPME is that it is a sample preparation technique, which combines the usage of a fused-silica fiber that is coated on the outside with an appropriate stationary phase. The analyte in the sample is directly extracted to the coating of the fiber. The SPME technique can be applied, in fact routinely, in combination with other analytical techniques such as gas chromatography (GC), gas chromatography-mass spectrometry (GC-MS), high-performance liquid chromatography (HPLC), or high-performance liquid chromatography coupled to mass spectrometry (LC-MS) [13]. SPME can be recognized as a \"green\" technique that, in combination with analytical chemical techniques, can rapidly provide adequate data regarding the volatile pattern of foods. The volatile markers of citrus honey that have been associated previously with its typicity include methyl anthranilate, isomers of lilac aldehydes, hotrienol, \(\alpha\),4-dimethyl-3-cyclohex-1-acetaldehyde, dill ether, nerolidol, 1-para-menthen-9-al, linalool, DL-limonene, (E)-limonene oxide, ethyl linalool, etc. [3; 4; 5; 6; 7]. Taking the aforementioned into consideration, the scope of the current study was to characterize and discriminate citrus honey from different countries using semi-quantitative data of volatile compounds in combination with machine learning algorithms. The obtained multivariate discriminating models were further evaluated using a set of honey samples containing other nectar honey types such as flower and thyme honey. Finally, an effort was made to establish a new metric for citrus honey authentication using the selected volatile compounds from the multivariate analysis and producing specific ratios.