Application Fourier transform near infrared spectrometer in rapid estimation of soluble solids content of intact citrus fruits.
- Author:
Hui-shan LU
1
;
Hui-rong XU
;
Yi-bin YING
;
Xia-ping FU
;
Hai-yan YU
;
Hai-qing TIAN
Author Information
1. School of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310029, China.
- Publication Type:Journal Article
- MeSH:
Biochemistry;
methods;
Calibration;
Citrus;
metabolism;
Least-Squares Analysis;
Light;
Models, Statistical;
Regression Analysis;
Reproducibility of Results;
Scattering, Radiation;
Spectroscopy, Fourier Transform Infrared;
methods;
Spectroscopy, Near-Infrared
- From:
Journal of Zhejiang University. Science. B
2006;7(10):794-799
- CountryChina
- Language:English
-
Abstract:
Nondestructive method of measuring soluble solids content (SSC) of citrus fruits was developed using Fourier transform near infrared reflectance (FT-NIR) measurements collected through optics fiber. The models describing the relationship between SSC and the NIR spectra of citrus fruits were developed and evaluated. Different spectra correction algorithms (standard normal variate (SNV), multiplicative signal correction (MSC)) were used in this study. The relationship between laboratory SSC and FT-NIR spectra of citrus fruits was analyzed via principle component regression (PCR) and partial least squares (PLS) regression method. Models based on the different spectral ranges were compared in this research. The first derivative and second derivative were applied to all spectra to reduce the effects of sample size, light scattering, instrument noise, etc. Different baseline correction methods were applied to improve the spectral data quality. Among them the second derivative method after baseline correction produced best noise removing capability and yielded optimal calibration models. A total of 170 NIR spectra were acquired; 135 NIR spectra were used to develop the calibration model; the remaining spectra were used to validate the model. The developed PLS model describing the relationship between SSC and NIR reflectance spectra could predict SSC of 35 samples with correlation coefficient of 0.995 and RMSEP of 0.79 degrees Brix.
