A novel acoustic based moisture meter 1 has been designed with the specific purpose of measuring moisture in raw cashew nuts. The meter employs pattern matching techniques to determine the moisture content. The meter applies non-invasive, non-destructive methods and the techniques are easily scalable to perform online measurements suitable in an industrial set up. For test trials, a set 15-20 cashew nuts of varying size and weight were considered for our system training and testing. The feature vectors for our training algorithm were based on the acoustic signature of shell to shell impact of cashew nuts. Algorithmic implementation and the electronic and mechanical aspects of the system prototype are discussed. By this method, we were able to distinguish between the dry and wet cashew nuts with high correlation accuracy.