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Proceedings Paper

Development of VIS/NIR spectroscopic system for real-time prediction of fresh pork quality
Author(s): Haiyun Zhang; Yankun Peng; Songwei Zhao; Akira Sasao
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Paper Abstract

Quality attributes of fresh meat will influence nutritional value and consumers' purchasing power. The aim of the research was to develop a prototype for real-time detection of quality in meat. It consisted of hardware system and software system. A VIS/NIR spectrograph in the range of 350 to 1100 nm was used to collect the spectral data. In order to acquire more potential information of the sample, optical fiber multiplexer was used. A conveyable and cylindrical device was designed and fabricated to hold optical fibers from multiplexer. High power halogen tungsten lamp was collected as the light source. The spectral data were obtained with the exposure time of 2.17ms from the surface of the sample by press down the trigger switch on the self-developed system. The system could automatically acquire, process, display and save the data. Moreover the quality could be predicted on-line. A total of 55 fresh pork samples were used to develop prediction model for real time detection. The spectral data were pretreated with standard normalized variant (SNV) and partial least squares regression (PLSR) was used to develop prediction model. The correlation coefficient and root mean square error of the validation set for water content and pH were 0.810, 0.653, and 0.803, 0.098 respectively. The research shows that the real-time non-destructive detection system based on VIS/NIR spectroscopy can be efficient to predict the quality of fresh meat.

Paper Details

Date Published: 29 May 2013
PDF: 6 pages
Proc. SPIE 8721, Sensing for Agriculture and Food Quality and Safety V, 87210N (29 May 2013); doi: 10.1117/12.2015878
Show Author Affiliations
Haiyun Zhang, China Agricultural Univ. (China)
Shandong Univ. of Technology (China)
Yankun Peng, China Agricultural Univ. (China)
Songwei Zhao, China Agricultural Univ. (China)
Akira Sasao, Tokyo Univ. of Agriculture and Technology (Japan)

Published in SPIE Proceedings Vol. 8721:
Sensing for Agriculture and Food Quality and Safety V
Moon S. Kim; Shu-I Tu; Kuanglin Chao, Editor(s)

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