Analysis of Volatiles in Food Products

Abstract

The evaluation of volatiles in food is an important aspect of food production. It gives knowledge about the quality of foods and their relationship to consumers’ choices. Alcohols, aldehydes, acids, esters, terpenes, pyrazines, and furans are the main chemical groups that are involved in aroma formation. They are products of food processing: thermal treatment, fermentation, storage, etc. Food aroma is a mixture of varied molecules. Because of this, the analysis of aroma composition can be challenging. The four main steps can be distinguished in the evaluation of the volatiles in the food matrix as follows: (1) isolation and concentration; (2) separation; (3) identification; and (4) sensory characterization. The most commonly used techniques to separate a fraction of volatiles from non-volatiles are solid-phase micro-(SPME) and stir bar sorptive extractions (SBSE). However, to study the active components of food aroma by gas chromatography with olfactometry detector (GC-O), solvent-assisted flavor evaporation (SAFE) is used. The volatiles are mostly separated on GC systems (GC or comprehensive two-dimensional GCxGC) with the support of mass spectrometry (MS, MS/MS, ToF–MS) for chemical compound identification. Besides omics techniques, the promising part could be a study of aroma using electronic nose. Therefore, the main assumptions of volatolomics are here described.

Foods and Contaminants Analysis Using Multidimensional Gas Chromatography: An Update of Recent Studies, Technology, and Applications

“…The principles, procedures, and applications of some of these common sample preparation techniques were discussed elsewhere 23 in the context of MDGC. 24,25 Injection Techniques. Although the most common injector for capillary GC still employs split/splitless injection, other techniques such as programmable temperature vaporization (PTV) and on-column techniques are available (see ref 26 for characteristics of each technique).…”

“…Common broadly applicable derivatizations in food analysis include methyl esters of fatty acids using reagents such as KOH-methanol and BF 3 -methanol and silylation using N , O -bis­(trimethylsilyl) trifluoroacetamide (BSTFA, usually with 1% trimethylchlorosilane (TMCS)). The principles, procedures, and applications of some of these common sample preparation techniques were discussed elsewhere in the context of MDGC. , …”

Effect of Scents on Gazing Behavior and Choice

“…Several different techniques have been used to measure volatiles in foods. Starowitz [49] stated that the most commonly used techniques for fraction separation are solid-phase microextractions (SPME) and stir bar sorptive extractions (SBSE), while the analysis of active compounds is usually conducted using gas chromatography with olfactometry detectors (GC-O) or solvent-assisted flavor evaporation (SAFE). Volatiles are mostly separated on GC systems, while detection is done by mass spectrometry for chemical compound identification.…”

Application of an Electronic Nose and HS-SPME/GC-MS to Determine Volatile Organic Compounds in Fresh Mexican Cheese

“…All cheeses have a unique aroma that may involve more than 600 volatile organic compounds (VOCs), such as short-or medium-chain fatty acids, alcohols, aldehydes, ketones, esters, or sulfur, which creates a characteristic smell and flavor of each cheese [5,6]. The VOCs have been reported as essential biomarkers to describe foods' taste and shelf life [7]. Determining VOCs in dairy products may be critical to understanding their origins, evaluating differences in the aroma profile among similar cheeses, and ensuring dairy product safety and quality [8].…”

“…Nevertheless, there is little information on how VOCs are related to dairy breeds, milk, cheesemaking, and potential benefits to consumer health [10][11][12]. Most of the information in the literature reports an abundance of VOCs in vastly varying concentrations since determining the volatile profile in complex food matrices is considered problematic due to different equipment and existing methods [7,12].…”