Application of untargeted LC/MS techniques (Flavoromics) to identify changes related to freshness of food

Freshness in food is a highly desirable attribute that has proven difficult to chemically characterize using traditional targeted methods. This work focuses on applying untargeted chemometric techniques to investigate differences in the chemical composition of orange extracts as they age as a strategy to identify compounds that contribute to the 'fresh' flavor character. Ethanol extracts of oranges products were aged and sampled every 48 hours. RP-UPLC-MS (ESI-NEG) was used for data collection and two modeling techniques including the projection to latent variables (PLS) and Random Forest analysis were utilized for data analysis. Random forest and PLS provide different modeling criteria and identified common as well as unique features in the data set. Future work will focus on the compound identification and further sensory characterization of the selected markers. In summary, a method was developed to chemically profile the changes in a food product during aging to provide a unique basis to investigate changes in flavor profiles, identifying chemical attributes that may relate to freshness perception in food.