New insights into non-extractable phenolic compounds analysis

Most of the studies regarding phenolic compounds (PC) have been focused only on one fraction of PC, named extractable phenolic compounds (EPC). As the name suggests, EPC can be directly extracted from the food matrix by using an appropriate solvent. Otherwise, non-extractable phenolic compounds (NEPC) remain in the food matrix after the conventional extraction, and their analysis depends on a hydrolysis process. NEPC is a relevant fraction of PC that acts in the colon, where they are extensively fermented by the action of the microbiota. To understand the health effects associated with the NEPC intake, it is necessary to know which types of compounds are present and their content in foods. In this review, 182 studies published in the last five years about NEPC in foods were evaluated, focusing on critical points of the NEPC analysis. First, EPC exhaustive extraction should be performed before the hydrolysis processes to avoid overestimation of the NEPC fraction. NEPC hydrolysis by aggressive methods modifies their original structure and makes their complete elucidation difficult. These methods must be optimized considering the research objective, as different conditions may result in different amounts and profiles of compounds. Concerning quantification, the widely used spectrophotometric Folin-Ciocalteu method should be avoided as it leads to overestimation. Liquid chromatography coupled to a diode array detector is the most appropriate technique for this purpose. Although pure standard compounds are unavailable in most cases, standards representative of a PC family can be used, and results can be expressed as equivalent. The best approach for NEPC identification is liquid chromatography coupled to a diode array detector and tandem high-resolution mass spectrometry, which generates information regarding chromatographic behavior, UV-vis absorption, accuracy mass and fragmentation pattern. The identification process should associate manual data handling with the bioinformatics-assisted approach.