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应用红外光谱结合化学计量学方法检测阿拉伯胶产地和蛋白质含量

邹小波 石吉勇 Mel HOLMES

食品科学2017,Vol.38Issue(20):229-234,6.
食品科学2017,Vol.38Issue(20):229-234,6.DOI:10.7506/spkx1002-6630-201720033

应用红外光谱结合化学计量学方法检测阿拉伯胶产地和蛋白质含量

Determination of Geographical Origin and Protein Content of Acacia Gums Using Infrared Spectroscopy and Chemometrics

邹小波 1石吉勇 1Mel HOLMES2

作者信息

  • 1. 江苏大学食品与生物工程学院,江苏镇江 212013
  • 2. 利兹大学食品科学与营养学院,英国利兹 LS1 3AB
  • 折叠

摘要

Abstract

The feasibility of using Fourier transform infrared (FTIR) spectroscopy and chemometrics as a rapid and non-invasive technique to determine the geographical origin and protein content of Sudanese Acacia gums was investigated.Seventy-two samples of Acacia gums were collected from six different regions (12 samples from each region).Linear discriminant analysis (LDA) was used to discriminate the geographical origin of Acacia gums,and backward interval partial least squares (Bi-PLS) was applied to build a prediction model for the protein content of Acacia gums.The results showed that the recognition rates of LDA for calibration set (48 samples) and prediction set (24 samples) were both 100% when the first 6 principal components were used.In addition,Bi-PLS yielded a good prediction model (Rp =0.937 3 and RMSEP =0.173%) for protein content by using the optimal combination of 4 out of 20 spectral intervals.Hence,FTIR spectroscopy coupled with chemometrics can be considered as a valid approach for the determination of the geographical origin and protein content of Acacia gums.

关键词

阿拉伯胶/傅里叶红外光谱/产地/蛋白质含量/线性判别分析/反向区间偏最小二乘法

Key words

Acacia gums/Fourier transform infrared (FTIR) spectroscopy/geographical origin/protein content/linear discriminant analysis (LDA)/backward interval partial least squares (Bi-PLS)

分类

轻工纺织

引用本文复制引用

邹小波,石吉勇,Mel HOLMES..应用红外光谱结合化学计量学方法检测阿拉伯胶产地和蛋白质含量[J].食品科学,2017,38(20):229-234,6.

基金项目

“十二五”国家科技支撑计划项目(2015BAD17B04) (2015BAD17B04)

“十三五”国家重点研发计划重点专项(2016YFD0401104) (2016YFD0401104)

国家自然科学基金面上项目(31671844) (31671844)

国家自然科学基金青年科学基金项目(31601543) (31601543)

中国博士后科学基金项目(2014T70483 ()

2016M590422) ()

江苏省自然科学基金项目(BK20160506 ()

BE2016306) ()

江苏省国际科技合作项目(BZ2016013) (BZ2016013)

苏州市科技发展计划项目(SNG201503) (SNG201503)

江苏高校优势学科建设工程资助项目(PAPD) (PAPD)

食品科学

OA北大核心CSCDCSTPCD

1002-6630

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