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Received: 2008-09-23

Revision Accepted: 2009-01-19

Crosschecked: 2009-04-28

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Journal of Zhejiang University SCIENCE B 2009 Vol.10 No.6 P.465~471


Use of near-infrared spectroscopy and least-squares support vector machine to determine quality change of tomato juice

Author(s):  Li-juan XIE, Yi-bin YING

Affiliation(s):  College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310029, China

Corresponding email(s):   ybying@zju.edu.cn

Key Words:  Near-infrared (NIR) spectroscopy, Least squares-support vector machine (LS-SVM), Quality change, Tomato juice

Li-juan XIE, Yi-bin YING. Use of near-infrared spectroscopy and least-squares support vector machine to determine quality change of tomato juice[J]. Journal of Zhejiang University Science B, 2009, 10(6): 465~471.

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journal="Journal of Zhejiang University Science B",
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%T Use of near-infrared spectroscopy and least-squares support vector machine to determine quality change of tomato juice
%A Li-juan XIE
%A Yi-bin YING
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%DOI 10.1631/jzus.B0820299

T1 - Use of near-infrared spectroscopy and least-squares support vector machine to determine quality change of tomato juice
A1 - Li-juan XIE
A1 - Yi-bin YING
J0 - Journal of Zhejiang University Science B
VL - 10
IS - 6
SP - 465
EP - 471
%@ 1673-1581
Y1 - 2009
PB - Zhejiang University Press & Springer
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DOI - 10.1631/jzus.B0820299

Near-infrared (NIR) transmittance spectroscopy combined with least-squares support vector machine (LS-SVM) was investigated to study the quality change of tomato juice during the storage. A total of 100 tomato juice samples were used. The spectrum of each tomato juice was collected twice: the first measurement was taken when the tomato juice was fresh and had not undergone any changes, and the second measurement was taken after a month. Principal component analysis (PCA) was used to examine a potential capability of separating juice before and after the storage. The soluble solid content (SSC) and pH of the juice samples were determined. The results show that changes in certain compounds between tomato juice before and after the storage period were obvious. An excellent precision was achieved by LS-SVM model compared with discriminant partial least-squares (DPLS), soft independent modeling of class analogy (SIMCA), and discriminant analysis (DA) models, with 100% of a total accuracy. It can be found that NIR spectroscopy coupled with LS-SVM, DPLS, SIMCA, and DA can be used to control the quality change of tomato juice during the storage.

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article


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