The Pear Acidity Quantified Analysis Using PLS Methods and Fourier Transform Near-Infrared Spectroscopy
LIU Yan-de1, 2,YING Yi-bin1
1. College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310029, China 2. College of Engineering, Jiangxi Agricultural University, Nanchang 330045, China
Abstract：Fourier transform near infrared(FT-NIR) spectrum of intact Xueqing pear was obtained by diffusion reflectance. Partial least squares (PLS) regression was carried out, describing the relationships between the data sets of laboratory data and the FT-NIR spectra. Different wave number ranges were chosen for regression and spectral information abstraction. The 3D-curves were shown for different factors, root mean square errors of cross validation (RMSECV), and prediction residual sum of squares (PRESS). Analysis results show that the best calibration model gave the relative high correlation coefficient of 0.79 and the low standard errors of prediction of 0.019 when the best wave number range was 5 452-12 285 cm-1 and the best factor was 7. The method of selecting advantageous wavelength ranges is feasible to obtain high prediction precision.
Key words：Fourier transform near infrared;Intact pear;Nondestructive measurement;PLS mothods;Acidity
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