DocumentCode
2705416
Title
Detection of contraband food products with a hybrid chemical sensor system
Author
Pardo, M. ; Kwong, L.G. ; Sberveglieri, G. ; Schneider, J. ; Penrose, W.R. ; Stetter, J.R.
Author_Institution
INFM, Brescia Univ., Italy
Volume
2
fYear
2003
fDate
22-24 Oct. 2003
Firstpage
1073
Abstract
The U.S. Department of Agriculture (USDA) is responsible for the interdiction of agricultural products, especially fruits and meats, from abroad. They do this in order to prevent the importation of exotic pests and diseased or defective food products. At present, inspectors select passenger bags and shipping containers at random, and physically inspect them. Trained dogs are sometimes used, but little in the way of instrumentation has been exploited. We have begun preliminary work towards developing a sensor array (electronic nose) device specifically to detect meat and fruit in baggage under a USDA contract. The rational design of a sensor array-based instrument for detecting contraband agricultural products in airline freight involves (a) identification of specific vapors typically found in the headspace above various samples of meat and fruit, and (b) identification of a minimum set of sensors that will allow efficient detection. We present the results obtained in measuring diverse food products with the Moses II electronic nose (EN) equipped with three different classes of chemical sensors, namely quartz micro-balances (QMB), semiconductor sensors (S) and electrochemical cells (EC).
Keywords
agricultural products; chemical sensors; chemioception; Moses II electronic nose; airline freight; contraband agricultural products; contraband food products; electrochemical cells; electronic nose; hybrid chemical sensor system; quartz microbalances; semiconductor sensors; Agricultural products; Chemical sensors; Containers; Contracts; Dogs; Electronic noses; Food products; Instruments; Sensor arrays; US Department of Agriculture;
fLanguage
English
Publisher
ieee
Conference_Titel
Sensors, 2003. Proceedings of IEEE
Print_ISBN
0-7803-8133-5
Type
conf
DOI
10.1109/ICSENS.2003.1279108
Filename
1279108
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