Detecting pits in tart cherries by hyperspectral transmission imaging

Proceedings of SPIE - The International Society for Optical Engineering

Volumn 5587, Issue , 2004, Pages 153-162

  Qin, Jianwei ^a   Lu, Renfu ^a  

^a MICHIGAN STATE UNIVERSITY   (United States)

Author keywords

Cherry; Fruit; Hyperspectral imaging; Near infrared; Neural networks; Nondestructive sensing; Pit detection

Indexed keywords

CHERRY; HYPERSPECTRAL IMAGING; NEAR-INFRARED; NONDESTRUCTIVE SENSING; PIT DETECTION;

COLOR; IMAGING TECHNIQUES; INFRARED IMAGING; LIGHT SCATTERING; NEURAL NETWORKS; NONDESTRUCTIVE EXAMINATION; PITTING; WEIGHING;

FRUITS;

EID: 16644377077     PISSN: 0277786X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1117/12.571359     Document Type: Conference Paper

References (19)

1. Allen, K. M., L. H. Vandyke, Jr., and R. L. Brunsbach. 1966. Apparatus for detecting seeds in fruit. U.S. Patent No. 3,275,136.
2. Canadian Food Inspection Agency. 2002. Consumer Alert - Potential Presence of Cherry Pits in DOLE® Lots-o-Cherries™Products - Voluntary Precautionary Recall. Available at http://www.inspection.gc.ca/english/corpaffr/ recarapp/2002/20021206e.shtml. Accessed on Mav 21, 2004.
3. Gillespie, R. M. and J. R. Ricks. 1987. Pit detecting. U.S. Patent No. 4,666,045.
4. Kim, M. S., Y. R. Chen, and P. M. Mehl. 2001. Hyperspectral reflectance and fluorescence imaging system for food quality and safety. Transactions of the ASAE 44(3): 721-729.
5. Kong, S. G, Y. R. Chen, I. Kim, and M. S. Kim. 2004. Analysis of hyperspectral fluorescence images for poultry skin tumor inspection. Applied Optics. 43(4): 824-833.
6. Law, S. E. 1973. Scatter of near-infrared radiation by cherries as a means of pit detection. Journal of Food Science. 38:102-107.
7. Lawrence, K. C., W. R. Windham, B. Park, and R. J. Buhr. 2001. Hyperspectral imaging system for identification of fecal and ingesta contamination on poultry carcasses. ASAE Paper #013076. ASAE, St. Joseph, MI.
8. Lu, R. and Y. R. Chen. 1998. Hyperspectral imaging for safety inspection of food and agricultural products. SPIE: 3544: 121-133.
9. Lu, R., Y. R. Chen, B. Park, and K. H. Choi. 1999, Hyperspectral imaging for detecting bruises in apples. ASAE Paper No. 993120. ASAE, St. Joseph, MI.
10. Lu, R. 2003a. Detection of bruises on apples using near-infrared hyperspectral imaging. Transactions of the ASAE 46(2): 523-530.
11. Lu, R. 2003b. Imaging spectroscopy for assessing internal quality of apple fruit. ASAE Paper No. 036012. ASAE, St Joseph, MI.
12. Martinsen, P. and P. Schaare. 1998. Measuring soluble solids distribution in kiwifruit using near-infrared imaging spectroscopy. Postharvest Biology and Technology 14: 271-281.
13. Mehl, P. M., Y. R. Chen, M. S. Kim, and D. E. Chan. 2004. Development of hyperspectral imaging technique for the detection of apple surface defects and contaminations. Journal of Food Engineering. 61(1): 67-81.
14. Park, B., K. C. Lawrence, W. R. Windham, and R. J. Buhr. 2002. Hyperspectral imaging for detecting fecal and ingesta contaminants on poultry carcasses. Transactions of the ASAE 45(6): 2017-2026.
15. Peirs, A., N. Scheerlinck, J. De Baerdemaeker, and B. M. Nicolai. 2003. Starch index determination of apple fruit by means of a hyperspectral near infrared reflectance imaging system. Journal of Near Infrared Spectroscopy 11: 3709-389.
16. Rogers, J. E. 1994. Pit detector and method. U.S. Patent No. 5,345,081.
17. Timm, E. J., P. V. Gilliland, G. K. Brown, and H. A. Affeldt, Jr. 1991. Potential methods for detecting pits in tart cherries. Applied Engineering in Agriculture 7(1): 103-109.
18. USDA Agricultural Marketing Service. 1976. United States Standards for Grades of Canned Red Tart Pitted Cherries. U.S. Government Printing Office, Washington, D.C.
19. Zion, B., M. J. McCarthy, and P. Chen. 1994. Real-time detection of pits in processed cherries by magnetic resonance projections. Lebensmittel- Wissenschaft und-Technologie. 27(5): 457462.