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Journal of Zhejiang University SCIENCE B 2005 Vol.6 No.3 P.158~164

http://doi.org/10.1631/jzus.2005.B0158


Prediction of valid acidity in intact apples with Fourier transform near infrared spectroscopy


Author(s):  LIU Yan-de, YING Yi-bin, FU Xia-ping

Affiliation(s):  School of Biosystems Engineering & Food Science, Zhejiang University, Hangzhou 310029, China; more

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

Key Words:  Apples, Nondestructive prediction, FT-NIR, Valid acidity, Multivariate analysis


LIU Yan-de, YING Yi-bin, FU Xia-ping. Prediction of valid acidity in intact apples with Fourier transform near infrared spectroscopy[J]. Journal of Zhejiang University Science B, 2005, 6(3): 158~164.

@article{title="Prediction of valid acidity in intact apples with Fourier transform near infrared spectroscopy",
author="LIU Yan-de, YING Yi-bin, FU Xia-ping",
journal="Journal of Zhejiang University Science B",
volume="6",
number="3",
pages="158~164",
year="2005",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.2005.B0158"
}

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%T Prediction of valid acidity in intact apples with Fourier transform near infrared spectroscopy
%A LIU Yan-de
%A YING Yi-bin
%A FU Xia-ping
%J Journal of Zhejiang University SCIENCE B
%V 6
%N 3
%P 158~164
%@ 1673-1581
%D 2005
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.2005.B0158

TY - JOUR
T1 - Prediction of valid acidity in intact apples with Fourier transform near infrared spectroscopy
A1 - LIU Yan-de
A1 - YING Yi-bin
A1 - FU Xia-ping
J0 - Journal of Zhejiang University Science B
VL - 6
IS - 3
SP - 158
EP - 164
%@ 1673-1581
Y1 - 2005
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.2005.B0158


Abstract: 
To develop nondestructive acidity prediction for intact Fuji apples, the potential of Fourier transform near infrared (FT-NIR) method with fiber optics in interactance mode was investigated. Interactance in the 800 nm to 2619 nm region was measured for intact apples, harvested from early to late maturity stages. Spectral data were analyzed by two multivariate calibration techniques including partial least squares (PLS) and principal component regression (PCR) methods. A total of 120 Fuji apples were tested and 80 of them were used to form a calibration data set. The influences of different data preprocessing and spectra treatments were also quantified. Calibration models based on smoothing spectra were slightly worse than that based on derivative spectra, and the best result was obtained when the segment length was 5 nm and the gap size was 10 points. Depending on data preprocessing and PLS method, the best prediction model yielded correlation coefficient of determination (γ2) of 0.759, low root mean square error of prediction (RMSEP) of 0.0677, low root mean square error of calibration (RMSEC) of 0.0562. The results indicated the feasibility of FT-NIR spectral analysis for predicting apple valid acidity in a nondestructive way.

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

Reference

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