Page Banner

United States Department of Agriculture

Agricultural Research Service


item Kim, Moon
item Cho, Byoung Kwan
item Yang, Chun-chieh
item Chao, Kuanglin - Kevin Chao
item Lefcourt, Alan
item Chen, Yud

Submitted to: Proceedings of SPIE
Publication Type: Proceedings
Publication Acceptance Date: 10/6/2006
Publication Date: 11/12/2006
Citation: Kim, M.S., Cho, B., Yang, C., Chao, K., Lefcourt, A.M., Chen, Y.R. 2006. Hyperspectral reflectance and fluorescence line-scan imaging system for online detection of fecal contamination on apples. Proceedings of SPIE. 6831:1-8.

Interpretive Summary: Researchers at the ISL developed a new online machine vision system to rapidly inspect apples for animal fecal contamination. The inspection system is based on hyperspectral line-scan imaging techniques utilizing visible/near-infrared reflectance and fluorescence methods. We integrated the prototype hyperspectral line-scan imaging system with a commercial apple-sorting machine and evaluated the system for detection of apples contaminated with animal fecal matter at the processing line speed of three apples per second. Preliminary results showed that hyperspectral fluorescence imaging, using two-band ratio as a multispectral fusion methods, allowed detection of fecal contaminated spots on apples at a 100 % accuracy rate with no false positives. Presented sensing systems and methodologies are useful to food scientists, engineers, regulatory government agencies (FSIS and FDA), and food processing industries.

Technical Abstract: Scientists at the Instrumentation and Sensing Lab, USDA have developed nondestructive opto-electronic imaging techniques for rapid assessment of safety and wholesomeness of foods. A recently developed fast hyperspectral line-scan imaging system integrated with a commercial apple-sorting machine was evaluated for rapid detection of animal feces matter on apples. Apples obtained from a local orchard were artificially contaminated with cow feces. For the online trial, hyperspectral images with 60 spectral channels, reflectance in the visible to near infrared regions and fluorescence emissions with UV-A excitation, were acquired from apples moving at a processing sorting-line speed of three apples per second. Reflectance and fluorescence imaging required a passive light source, and each method used independent continuous wave (CW) light sources. In this paper, integration of the hyperspectral imaging system with the commercial apple-sorting machine and preliminary results for detection of fecal contamination on apples, mainly based on the fluorescence method, are presented.

Last Modified: 06/22/2017
Footer Content Back to Top of Page