Online Non-destructive Detection of Jujuble to Classify Infested and Intact Groups Based on NearInfrared Diffuse Reflection Spectra Analysis Technique

被引：0
|
作者：
Zhang Cuixia [1 ,2 ]
Ma Yue [1 ]
机构：
[1] Chinese Acad Sci, Shenyang Inst Automat, Shenyang 110016, Peoples R China
[2] Univ Chinese Acad Sci, Beijing 100049, Peoples R China
来源：
2016 2ND INTERNATIONAL CONFERENCE ON MECHANICAL, ELECTRONIC AND INFORMATION TECHNOLOGY ENGINEERING (ICMITE 2016) | 2016年
关键词：
Non-destructive detection; Near infrared spectrometry; Date pretreatment; De-noising; Wavelet transform; Derivative; Mahalanobis distance discriminant; NIR; SPECTROSCOPY;
D O I：
暂无
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
Near-infrared reflectance spectroscopy (NIR) is an emerging kind of non-destructive detection method and become increasing popularity in the food industry. This work uses diffuse reflectance spectrum of NIR as sample to study the qualitative analysis of jujube, and try to find if it can classify infested and intact jujubes efficiently. Mahalanobis distance discriminant is used to build qualitative analysis model. The date of near infrared spectrum usually has a series of noise. The effects of different spectral pretreatment methods on the results of spectral analysis are studied for de-noising and resolution enhancement. The correctness of classification of original spectrum is 87.08%, and it is improved by 2-8% after date pretreatment in both calibration and prediction set. The best result is 96.67%. NIR is illustrated could be applied to classify jujubles.
引用
收藏
页码：45 / 50
页数：6
相关论文
共 33 条
1234