J P Schirle-Keller

Identification of Odor-Impact Compounds in Red Table Wines Produced from Frontenac Grapes

Frontenac (Vitis spp. MN 1047) is a recently introduced, cold-hardy red winegrape that is currently the most-planted cultivar in much of the Upper Midwest. Through descriptive analysis, a set of aroma attributes common to red Frontenac table wines has been described, but the volatile compounds responsible for the characteristic sensory notes of the product have not been investigated. In order to identify these odor active compounds, eight Frontenac table wines were evaluated using stir bar sorptive extraction (SBSE) combined with concurrent gas chromatography/olfactometry-mass spectrometry (GC/O-MS). Eight panelists evaluated GC/O effluent using qualitative detection frequency analysis. Twenty-four volatiles were identified in odor regions perceived by panelists, including five alcohols, 14 esters, one lactone, two acids, and two volatile phenols. Twenty-three of these were confirmed by linear retention index data in separate GC-MS analyses, and 23 were quantified in runs using a known concentration of internal standard. Similar analyses of wines produced from V. riparia clone #89, a parent of Frontenac, found 16 volatiles common to Frontenac wines. A brief study of Frontenac juice with two days of skin contact suggested that four volatiles found in the wine may originate in the fruit.

Determining specific food volatiles contributing to PTR-MS ion profiles using GC-EI-MS.

This work focused on developing a method to determine the volatile compounds that contribute to individual masses observed by PTR-MS in the headspace of a food product (e.g., cheese crackers). The process of interfacing a PTR-MS with a GC-MS (electron impact) through an existing sniffing port is outlined, and the problems faced in doing so are discussed. For the interface developed, linearity for both detectors working online for a wide range of concentrations of a selected compound (hexanal) was good (R(2) = 0.88). There was also a good correlation between the responses for both instruments (confidence interval for the slope between 0.56 and 1.18) over a range in concentrations despite the different ionization processes taking place. The application of our system (PTR-MS/GC-MS interface) to a real food system (cheese crackers) in which volatiles were isolated via purge and trap allowed the assignments of most of the PTR-MS masses to major volatile compounds in the samples. However, in this interface it is important to consider some limitations related to GC resolution, compound identification by EI-MS, PTR-MS sensitivity (and overloading), PTR-MS inlet requirements (ca. 20 mL/min), ion chemistry in the PTR-MS, and potentially changing sample composition over time, altering the contribution of a given compound to a specific ion. These issues are discussed.