Comparative assessment of software for non-targeted data analysis in the study of volatile fingerprint changes during storage of a strawberry beverage

Application of untargeted volatile profiling and data driven approaches in wine flavoromics research

Traditional flavor chemistry research usually makes use of targeted approaches by focusing on the detection and quantification of key flavor active metabolites that are present in food and beverages. In the last decade, flavoromics has emerged as an alternative to targeted methods where non-targeted and data driven approaches have been used to determine as many metabolites as possible with the aim to establish relationships among the chemical composition of foods and their sensory properties. Flavoromics has been successfully applied in wine research to gain more insights into the impact of a wide range of flavor active metabolites on wine quality. In this review, we aim to provide an overview of the applications of flavoromics approaches in wine research based on existing literature mainly by focusing on untargeted volatile profiling of wines and how this can be used as a powerful tool to generate novel insights. We highlight the fact that untargeted volatile profiling used in flavoromics approaches ultimately can assist the wine industry to produce different wine styles and to market existing wines appropriately based on consumer preference. In addition to summarizing the main steps involved in untargeted volatile profiling, we also provide an outlook about future perspectives and challenges of wine flavoromics research.

Volatile Profiling of Strawberry Fruits Cultivated in a Soilless System to Investigate Cultivar-Dependent Chemical Descriptors

Volatile compounds are essential for food organoleptic characteristics and of great utility for the food industry as potential markers for authenticity purposes (e.g., variety, geographical origin, adulteration). The aim of this study was to determine the characteristic volatile compounds of strawberry samples grown in a soilless system by using headspace solid phase micro-extraction coupled with gas chromatography and to investigate the influence of cultivar (Festival, Candonga, Camarosa) on this volatile profile. We observed that Festival and, to a lesser extent, Candonga varieties were characterized by the richest aroma-related profiles, including higher levels of esters, furanones and terpenes. In particular, methyl butyrate, hexyl hexanoate, linalool, geraniol and furaneol were the most abundant aromatic compounds detected in the three varieties of strawberries. Complementarily, the application of pattern recognition chemometric approaches, including principal component analysis and linear discriminant analysis, demonstrated that concentrations of specific volatiles can be employed as chemical descriptors to discriminate between strawberry cultivars. Accordingly, geraniol and hexyl hexanoate were found to be the most significant volatiles for the discrimination of strawberry varieties.

Nontargeted Detection Methods for Food Safety and Integrity

Nontargeted workflows for chemical hazard analyses are highly desirable in the food safety and integrity fields to ensure human health. Two different analytical strategies, nontargeted metabolomics and chemical database filtering, can be used to screen unknown contaminants in food matrices. Sufficient mass and chromatographic resolutions are necessary for the detection of compounds and subsequent componentization and interpretation of candidate ions. Analytical chemistry–based technologies, including gas chromatography–mass spectrometry (GC-MS), liquid chromatography–mass spectrometry (LC-MS), nuclear magnetic resonance (NMR), and capillary electrophoresis–mass spectrometry (CE-MS), combined with chemometrics analysis are being used to generate molecular formulas of compounds of interest. The construction of a chemical database plays a crucial role in nontargeted detection. This review provides an overview of the current sample preparation, analytical chemistry–based techniques, and data analysis as well as the limitations and challenges of nontargeted detection methods for analyzing complex food matrices. Improvements in sample preparation and analytical platforms may enhance the relevance of food authenticity, quality, and safety.