# A Predictive Model to Correlate Amino Acids and Aromatic Compounds in Calabrian Honeys
###### Abstract
These amino acids play a vital role in enhancing the nutraceutical value of substances and contributing to the flavor of foods by serving as the precursors for aroma compounds [14]. Volatile compounds, in fact, are formed when catabolic processes prevail over metabolic ones [15; 16]. Within fruits and vegetables, amino acids serve as precursors for the development of volatile aromatic compounds, which encompass aldehydes, alcohols, acids, and esters. These amino acids can be linked to distinct aromatic characteristics. For instance, specific amino acids such as alanine, glycine, and serine are linked to a sweet taste, whereas aspartic and glutamic acids are commonly associated with acidic and umami taste profiles [17; 18]. Amino acids constitute approximately 1% (_w/w_) of the components present in honey, with their relative proportions being contingent on the source of the honey, whether from nectar or honeydew [19; 20]. The most prevalent amino acid in both honey and pollen is proline [21]. Alongside proline, various other amino acids are identified within honey, including glutamic acid, aspartic acid, glutamine, histidine, glycine, threonine, alanine, arginine, tyrosine, valine, methionine, cysteine, isoleucine, leucine, tryptophan, phenylalanine, lysine, serine, and asparagine [22]. Since honey amino acids could drive the honey aromatic profile, it is necessary to find a relationship between the amino acids and volatile and semi-volatile compounds to better evidence the nutraceutical and aromatic characteristics of honey linked to territoriality. Therefore, the aim of this paper was to build a predictive model to study the behavior and correlation of amino acid profiles with aromatic compounds. The key objectives were (1) to trace the amino acid profile of 25 different honey belonging to different species through a new HILIC-UPLC-ESI-MS/MS method; (2) to trace the aromatic profile using HS-SPME-GC-MS; (3) to investigate the possible correlation between different amino acids and aromatic compound families using a Pearson test; and (4) to trace a method for predicting a correlation between various types of honey, their amino acid profiles, and aroma characteristics by PLS analysis [23]. A novel approach has been developed, employing hydrophilic interaction chromatography coupled with a triple quadrupole mass spectrometry detector operating in multiple reaction monitoring mode (HILIC-UPLC-ESI-MS/MS), for the analysis of amino acid profiles [24; 25]. Additionally, for the assessment of volatile profiles, headspace-solid phase micro-extraction (HS-SPME) combined with gas chromatography mass spectrometry (GC-MS) has been utilized. Both sets of data are subjected to multivariate processing. The utilization of the SPME technique in conjunction with GC-MS to generate fingerprint profiles for classifying unifloral honeys is of significant interest. Solid-phase microextraction (SPME) stands as a straightforward, cost-effective, and versatile solvent-free technique. It serves the purpose of sampling, extracting, and concentrating volatile compounds prior to GC-MS analysis. This approach has been recognized as a valuable tool in characterizing the aroma of honey [26; 27]. Also, HILIC offers distinct advantages, particularly for small polar molecules, including amino acids [5; 6; 28; 29]. Finally, a partial least squares (PLS) regression analysis was conducted. PLS regression offers notable advantages over classic regression, largely due to the availability of charts that facilitate the comprehension of the data structure. Correlation and loading plots enable the exploration of relationships among variables. The score plot provides insight into sample proximity and dataset structure. Furthermore, the biplot encapsulates all these aspects within a single visualization. In this work, a selection of unifloral honeys produced in the Calabria region was studied. Due to the particular pedo-climatic conditions, that includes both mountainous and hilly areas and coastal areas with different flora.