A Predictive Model to Correlate Amino Acids and Aromatic Compounds in Calabrian Honeys

Abstract

To better understand the biochemistry of the organoleptic properties of honey influencing its commercial value, a predictive model for correlating amino acid profiles to aromatic compounds was built. Because the amino acid composition of different varieties of honey plays a key role as a precursor of specific aroma bouquets, it is necessary to relate the amino acid typesetting to aromatic molecules. A selection of unifloral honeys produced in Calabria, South Italy, were used, and a new methodology based on the use of HILIC-UHPLC-ESI-MS/MS and HS-SPME-GC-MS combined with multivariate processing has been developed. This study, carried out for the first time on honey, shows its excellent potential as a modern analytical tool for a rapid multicomponent analysis of food-quality indicators. Data obtained showed strong positive linear correlations between aldehydes and isoleucine, valine, leucine, and phenylalanine. Furans are correlated with isoleucine, leucine, and phenylalanine; hydrocarbons with serine, glutamic acid, and aspartic acid; and ketones with serine, alanine, glutamine, histidine, asparagine, and lysine. Alcohols were more associated with tyrosine than esters with arginine. Proline, tryptophan, and threonine showed poor correlations with all the classes of aroma compounds.