title: 2D bitmapping approach for identification and quantitation of common base flavor adulterants using surface acoustic wave arrays and artificial neural network data analysis.
abstract: Arrays of polymer-coated surface acoustic wave microsensors are used in conjunction with a variety of signal-processing algorithms known as artificial neural networks (ANN). This format of data analysis has the capability to characterize complex mixtures of volatile and semi-volatile organic compounds commonly found in base flavors. The approach described, which minimizes the number of training sets while retaining the robustness of an ANN, utilizes a 2D bitmap matrix. The matrix is obtained by converting the time domain kinetics of sensor response into a bitmap. The high data throughput of this approach enables quantitation on the order of ppm of common base flavor adulterants.
authors.affiliation: Department of Chemistry and Biochemistry, Northern Illinois University, DeKalb, IL 60115, United States.
authors.forename: Robert M
authors.initials: RM
authors.lastname: Sobel
authors.forename: David S
authors.initials: DS
authors.lastname: Ballantine
mesh_terms: D020001:1-Butanol / Q000737:chemistry; D000162:Acoustics; D000465:Algorithms; D002623:Chemistry Techniques, Analytical / Q000379:methods*; D005421:Flavoring Agents / Q000737:chemistry*; D007700:Kinetics; D008956:Models, Chemical; D016571:Neural Networks, Computer; D010363:Pattern Recognition, Automated; D011108:Polymers / Q000737:chemistry; D012044:Regression Analysis; D012997:Solvents; D013499:Surface Properties; D013696:Temperature
chemical_list: D005421:Flavoring Agents; D011108:Polymers; D012997:Solvents; D020001:1-Butanol