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Real-Time Detection of Pits in Processed Cherries by Magnetic Resonance Projections
Year:
1994
Source of publication :
LWT - Food Science and Technology
Authors :
Chen, Pictiaw
;
.
Zion, Boaz
;
.
Volume :
27
Co-Authors:

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.)

 

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Total pages:
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Abstract:

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.

Note:
Related Files :
Cherry
Cherry's pits
Magnetic Resonance Projections
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Related Content
More details
DOI :
10.1006/fstl.1994.1092
Article number:
0
Affiliations:
Database:
Publication Type:
article
;
.
Language:
English
Editors' remarks:
ID:
49910
Last updated date:
02/03/2022 17:27
Creation date:
13/09/2020 14:59
Scientific Publication
Real-Time Detection of Pits in Processed Cherries by Magnetic Resonance Projections
27

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.)

 

Real-Time Detection of Pits in Processed Cherries by Magnetic Resonance Projections

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.

Scientific Publication
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