Moisture determination with an artificial neural network from microwave measurements on wheat

An artificial neural network (ANN) was used to determine the moisture content of hard red winter wheat. The ANN was trained to recognize moisture content in the range from 10.6% to 19.2% (wet basis) from transmission coefficient measurements on samples of wheat placed between two radiating elements. The measurements were made at 8 microwave frequencies (10 to 18 GHz) on wheat samples of varying bulk densities (0.72 to 0.88 g/cm/sup 3/) at 24/spl deg/C. The trained network predicted moisture content (%) with a mean absolute error of 0.135.