Quality assessment of apple chips based on data fusion processing and NIRS method

Authors

GUAN Xiao, School of Medical Instruments and Food Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
RAO Li, School of Medical Instruments and Food Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
LIU Jing, College of Information Engineering, Shanghai Maritime University, Shanghai 200135, China
KUANG Jingyun, School of Medical Instruments and Food Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China

Abstract

In this study, five quality indicators, i.e. moisture, soluble solid content, total sugar content, titratable acid content and hardness, of apple chips during processing period were analyzed by analytic hierarchy process, and quality scores was obtained. Near infrared spectroscopy (NIRS) combined with partial least-squares discriminant analysis (PLS-DA) was applied for the prediction of quality scores of apple chips. The results showed that the correlation coefficients between predicted category variable of calibration and the measured category variable were 0.84, 0.63 and 0.89, and the root mean square error of cross validation were 0.26, 0.34 and 0.22 for each quality category, respectively. The discrimination accuracy for this model were found 83.33%, 80% and 93.33%. Thus, this suggested that NIRS combined with PLS-DA method was a potential way to assess quality of apple chips processing period.

Publication Date

12-28-2016

First Page

45

Last Page

49

DOI

10.13652/j.issn.1003-5788.2016.12.010

Recommended Citation

Xiao, GUAN; Li, RAO; Jing, LIU; and Jingyun, KUANG (2016) "Quality assessment of apple chips based on data fusion processing and NIRS method," Food and Machinery: Vol. 32: Iss. 12, Article 10.
DOI: 10.13652/j.issn.1003-5788.2016.12.010
Available at: https://www.ifoodmm.cn/journal/vol32/iss12/10

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