Across our research portfolio, we combine advanced instrumentation, expertise, and creativity to analytically characterize flavor in order to better understand what drives flavor perception and ultimately food choice. We have built a holistic analytical platform to identify what compounds contribute to the flavor of food. The breadth and versatility of our instrumentation platform provides us with the ability to investigate and address unique and challenging aspects of flavor, and thus develop solutions spanning raw ingredients to finished products.
Targeted:
The Flavor Center uses systematic approaches that allow us to tackle the complexity of food by identifying important flavor information. It is the combination of these analytical methods that provides us the tools to address flavor challenges.
LC Platform:
-
Liquid chromatography-mass spectrometry (LC-MS): single quadrupole, triple quadrupole and quadrupole-time of flight (Q-ToF) mass spectrometers for quantification and structural elucidation - Multi-dimensional liquid chromatography-gustometry for identification of taste active and modulating components
- 1D and 2D nuclear magnetic resonance (NMR) for positive identification of compounds of interest
- Sensory recombination experiments
GC Platform:
-
1D and 2D gas chromatography-mass spectrometry (with and without olfactometry): single quadrupole, triple quadrupole and quadrupole-time of flight (Q-ToF) mass spectrometers for quantification and structural elucidation - Fraction collection: heart-cutting 2D GC-MS-PFC
- Real time aroma analysis (SIFT-MS, APCI-MS)
- Sensory recombination experiments
Untargeted Methods:
The Flavor Research and Education Center also uses data-driven research to address complex flavor challenges. Our untargeted flavoromic approach allows us to investigate flavor challenges holistically. We combine state-of-the-art chemical profiling techniques (LC and GC), with cutting edge modeling approaches to interpret unique flavor information. Our expertise extends from analytical chemistry to machine learning, and is grounded in producing results that lead to actionable insights.
