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An Infrared and Laser Range Imaging System for Realtime Estimation of Internal Temperature in Chicken Breast after Cooking

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan www.asabe.org

Citation:  Paper number  036183,  2003 ASAE Annual Meeting . (doi: 10.13031/2013.15420)
Authors:   Ling Ma, Yang Tao, Hansong Jing
Keywords:   Internal temperature, External temperature, Geometric variable, IR imaging, Laser 3D reconstruction system, Artificial Neural Network, Chicken breast, Food quality, Food safety.

This paper presents a system for the real-time estimation of the internal temperature of cooked chicken breasts. It is composed of three subsystems: an IR imaging system, Laser 3D reconstruction system, and Artificial Neural Network (ANN) modeling system. The IR imaging system is used to obtain the samples surface temperature information. The laser 3D reconstruction system is used to get the samples geometric information. The ANN system is for modeling the complicated nonlinear heating transfer process. The method is non-invasive and has no cross-contamination, which is suitable in automatically monitoring cooking processes. Our experiments show that geometric variables play important roles in internal temperature estimation, and using temperature with three lags gives the best performance. The accuracy achieved by our system was 1.54oC for mean absolute error, 2% for mean absolute percent error, and 3.08 for mean square error.

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