B. Zion - Institute of Agricultural Engineering, Agricultural Research Organization, The Volcani Center, P.O. Box 6 Bet Dagan 50250 (Israel) and Department of Biological and Agricultural Engineering, University of California, Davis, CA 95616 (U.S.A.)
M.J. McCarthy - Institute of Agricultural Engineering, Agricultural Research Organization, The Volcani Center, P.O. Box 6 Bet Dagan 50250 (Israel) and Department of Biological and Agricultural Engineering, University of California, Davis, CA 95616 (U.S.A.)
P. Chen - Institute of Agricultural Engineering, Agricultural Research Organization, The Volcani Center, P.O. Box 6 Bet Dagan 50250 (Israel) and Department of Biological and Agricultural Engineering, University of California, Davis, CA 95616 (U.S.A.)

A simulation of one-dimensional magnetic resonance projections of cherries, showed a significant difference between projections of cherries with and without pits. Projections of cherries in a 2-T magnetic field and a 100 mm Birdcage coil were used for detection of hidden pits. When cherries were randomly oriented 45 of 51 (88%) brined cherries with pits and 19 of 30 (63%) pitted cherries were correctly classified. A great improvement was achieved with oriented cherries: 29 out of 30 cherries with pits and 29 out of 30 pitted cherries were correctly classified. Detection rate may reach hundreds of cherries per second. This method could be applicable to detection of pits in olives and dates.