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Xiaping Fu

Researcher at Zhejiang University

Publications -  57
Citations -  973

Xiaping Fu is an academic researcher from Zhejiang University. The author has contributed to research in topics: Partial least squares regression & Diffuse reflectance infrared fourier transform. The author has an hindex of 14, co-authored 53 publications receiving 860 citations. Previous affiliations of Xiaping Fu include Agricultural Research Service.

Papers
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Variable selection in visible and near-infrared spectra: Application to on-line determination of sugar content in pears

Huirong Xu, +4 more
- 01 Mar 2012 - 
TL;DR: The results derived by these techniques were then compared as discussed by the authors, and the calibration model built using GA-SPA-MLR on 18 selected wavelengths (2% of the total number of variables) exhibited higher coefficient of determination (R 2 ) = 0.880 and root mean square error of prediction (RMSEP) − 0.459°Brix for the validation set.
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Detection of melamine in milk powders based on NIR hyperspectral imaging and spectral similarity analyses

Xiaping Fu, +9 more
- 01 Mar 2014 - 
TL;DR: In this paper, a combination of NIR hyperspectral imaging technique and spectral similarity analyses was used for detecting low levels (1.0%) of melamine particles in milk powders.
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Variable selection for partial least squares analysis of soluble solids content in watermelon using near-infrared diffuse transmission technique

Dengfei Jie, +4 more
- 01 Oct 2013 - 
TL;DR: In this paper, the variable selection in building the partial least squares (PLS) regression model of soluble solids content (SSC) was used to evaluate quality grading of watermelon.
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Comparison of diffuse reflectance and transmission mode of visible-near infrared spectroscopy for detecting brown heart of pear

Xiaping Fu, +3 more
- 01 Dec 2007 - 
TL;DR: In this paper, the authors compared the transmission and reflectance modes of VIS/NIR spectroscopy for detecting brown heart in pears and showed that the transmission mode is better than reflectance mode for internal disorder detection.
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Detection of melamine in milk powders using near-infrared hyperspectral imaging combined with regression coefficient of partial least square regression model.

Jongguk Lim, +8 more
- 01 May 2016 - 
TL;DR: NIR hyperspectral imaging technique and the PLSR model can be regarded as an effective tool to detect melamine particles in milk powders easily and quickly.