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Prediction of Edible-oil Iodine Values Based on Raman and near Infrared Spectroscopy

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成果类型:
会议论文
作者:
Wang, Jie;Wu, Shuang;Yu, Ya-ru;Zheng, Xiao*;He, Dong-ping
通讯作者:
Zheng, Xiao
作者机构:
[Zheng, Xiao; Wu, Shuang; Yu, Ya-ru; Wang, Jie] Wuhan Polytech Univ, Coll Mech Engn, Wuhan, Hubei, Peoples R China.
[He, Dong-ping] Wuhan Polytech Univ, Food Sci Engn, Wuhan, Hubei, Peoples R China.
通讯机构:
[Zheng, Xiao] W
Wuhan Polytech Univ, Coll Mech Engn, Wuhan, Hubei, Peoples R China.
语种:
英文
关键词:
Raman;Near infrared;Chemometrics;Edible oil;Iodine value
期刊:
2017 2ND INTERNATIONAL CONFERENCE ON COMPUTATIONAL MODELING, SIMULATION AND APPLIED MATHEMATICS (CMSAM)
ISSN:
2475-8841
年:
2017
页码:
257-261
会议名称:
2017 2nd International Conference on Computational Modeling, Simulation and Applied Mathematics (CMSAM)
会议论文集名称:
DEStech Transactions on Computer Science and Engineering
会议时间:
OCT 22-23, 2017
会议地点:
Beijing, PEOPLES R CHINA
会议主办单位:
[Wang, Jie;Wu, Shuang;Yu, Ya-ru;Zheng, Xiao] Wuhan Polytech Univ, Coll Mech Engn, Wuhan, Hubei, Peoples R China.^[He, Dong-ping] Wuhan Polytech Univ, Food Sci Engn, Wuhan, Hubei, Peoples R China.
出版地:
439 DUKE STREET, LANCASTER, PA 17602-4967 USA
出版者:
DESTECH PUBLICATIONS, INC
ISBN:
978-1-60595-499-8
基金类别:
Key Projects in the National Science&Technology Pillar Program during the Eleventh Five–Year Plan Period(NO.2009BADB9B08);Nutrition and Food Safety major projects nurture special of Wuhan Polytechnic University(NO.2011Z06);Wuhan Polytechnic University graduate innovation fund(NO.2014cx005);Transformational projects of technological innovation and achievements about food in Hubei at 2016--Study on Identification Technology and Instrument for Rapid Detection of Edible Oil Quality and Variety by Near Infrared Spectroscopy(NO.20165104)
机构署名:
本校为第一且通讯机构
院系归属:
机械工程学院
摘要:
Based on Raman and near infrared spectroscopy (NIR), the modeling of edible-oil iodine value was conducted following chemometrics and support vector machine regression (SVR). The Raman and NIR spectral data of 44 oil samples were collected and preprocessed. The preprocessed spectral data at characteristic wavelengths were extracted with CARS and iPLS methods. Parameter optimization was performed following the grid search algorithm (GS), for the SVR iodine value prediction models. The results show that all the models built could predict the iodine values to some extent. An NIR-MSC-iPLS-SVR mode...

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