Czech J. Food Sci., 2011, 29(6):595-602 | DOI: 10.17221/69/2010-CJFS

Vis/NIR hyperspectral imaging for detection of hidden bruises on kiwifruits

Qiang Lü^1,2, Ming-jie Tang¹, Jian-rong Cai¹, Jie-wen Zhao¹, Saritporn Vittayapadung³

¹ School of Food and Biological Engineering, Jiangsu University, Zhenjiang, Jiangsu, P.R. China

² School of Information Science and Engineering, Henan University of Technology, Zhengzhou, Henan, P.R. China

³ FAME Laboratory, Department of Mechanical Engineering, Chiang Mai University, Chiang Mai, Thailand$2

It is necessary to develop a non-destructive technique for kiwifruit quality analysis because the machine injury could lower the quality of fruit and incur economic losses. Bruises are not visible externally owing to the special physical properties of kiwifruit peel.We proposed the hyperspectral imaging technique to inspect the hidden bruises on kiwifruit. The Vis/NIR (408-1117 nm) hyperspectral image data was collected. Multiple optimal wavelength (682, 723, 744, 810, and 852 nm) images were obtained using principal component analysis on the high dimension spectral image data (wavelength range from 600 nm to 900 nm). The bruise regions were extracted from the component images of the five waveband images using RBF-SVM classification. The experimental results showed that the error of hidden bruises detection on fruits by means of hyperspectral imaging was 12.5%. It was concluded that the multiple optimal waveband images could be used to constructs a multispectral detection system for hidden bruises on kiwifruits.

Keywords: Actinidia deliciosa; principal component analysis; support vector machine

Published: December 31, 2011  Show citation