Abstract
This article investigates the possibility of using non-contact interactance as a method for profiling the temperature in a processed meat product (liver pâté) as it comes out of the oven. The application was defined by an industrial partner, Nortura SA, Tønsberg, Norway, where more control of the cooking process was desired. The optical system employs low spectral resolution to achieve high enough signal-to-noise ratio (SNR) to depths of 2 cm into the product. The partial least squares (PLS) method was applied to interactance spectra in the region 760–1040 nm and a root mean square error of 1.52 °C was obtained. The model was tested on five different validation sets spread over 18 months and a root mean square error of prediction of 2.66 °C was achieved. The output of this model was based on the weighted average of two temperatures in the first 2 cm of the liver pâté, one of which is the core temperature. A comparison was also made with two other models: a model based on the core temperature alone and a model based again on the weighted temperature but using the shorter wavelength range of 905.5–1047 nm. These two models gave less favorable prediction errors.