CLC number: S666; TN219
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 0000-00-00
Cited: 21
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LU Hui-shan, XU Hui-rong, YING Yi-bin, FU Xia-ping, YU Hai-yan, TIAN Hai-qing. Application Fourier transform near infrared spectrometer in rapid estimation of soluble solids content of intact citrus fruits[J]. Journal of Zhejiang University Science B, 2006, 7(10): 794-799.
@article{title="Application Fourier transform near infrared spectrometer in rapid estimation of soluble solids content of intact citrus fruits",
author="LU Hui-shan, XU Hui-rong, YING Yi-bin, FU Xia-ping, YU Hai-yan, TIAN Hai-qing",
journal="Journal of Zhejiang University Science B",
volume="7",
number="10",
pages="794-799",
year="2006",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.2006.B0794"
}
%0 Journal Article
%T Application Fourier transform near infrared spectrometer in rapid estimation of soluble solids content of intact citrus fruits
%A LU Hui-shan
%A XU Hui-rong
%A YING Yi-bin
%A FU Xia-ping
%A YU Hai-yan
%A TIAN Hai-qing
%J Journal of Zhejiang University SCIENCE B
%V 7
%N 10
%P 794-799
%@ 1673-1581
%D 2006
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.2006.B0794
TY - JOUR
T1 - Application Fourier transform near infrared spectrometer in rapid estimation of soluble solids content of intact citrus fruits
A1 - LU Hui-shan
A1 - XU Hui-rong
A1 - YING Yi-bin
A1 - FU Xia-ping
A1 - YU Hai-yan
A1 - TIAN Hai-qing
J0 - Journal of Zhejiang University Science B
VL - 7
IS - 10
SP - 794
EP - 799
%@ 1673-1581
Y1 - 2006
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.2006.B0794
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 °Brix.
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