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Determining moisture content of wheat with an artificial neural network from microwave transmission measurements

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4 Author(s)
Bartley, P.G. ; Georgia Univ., Athens, GA, USA ; Nelson, S.O. ; McClendon, R.W. ; Trabelsi, S.

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. The measurements were made at 8 microwave frequencies (10 GHz to 18 GHz) on wheat samples of varying bulk densities (0.72 g/cm3 to 0.88 g/cm3) at 24°C. The trained network predicted moisture content (%) with a mean absolute error of 0.135 (compared with oven-dried measurements)

Published in:

Instrumentation and Measurement, IEEE Transactions on  (Volume:47 ,  Issue: 1 )

Date of Publication:

Feb 1998

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