Authors: Reiner Jedermann, Javier Palafox-Albarrán, Pilar Barreiro, Luis Ruiz-García, Jose Ignacio Robla, Walter Lang
A better control of food transport, storage and processing is achieved if single-point temperature measurements are replaced by spatial monitoring. The statistical temperature distribution inside a room is described by a Variogram model. The temperature for any point in space can be interpolated by the Variogram based Kriging method. The accuracy of the Kriging method was tested on 14 experimental data sets recorded in cold-storage rooms, delivery trucks, and containers. The interpolation error can be reduced by up to 68% compared to an average measurement. Kriging showed also a clear advantage over the Inverse- Distance-Weighting interpolation method, with a higher reduction of the error by 20% except for 4 data sets with an insufficient spatial sensor density. Different approaches for automated estimation of the Variogram model parameters were compared. The influence range of temperature deviations was evaluated to values between 1.1 and 4.7 meter, depending on the air- permeability of the food packing.