Share Email Print

Proceedings Paper

Prediction of Chufa MT-firmness using FT-NIR spectroscopy
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

Chufa (Eleocharis tuberose Schult) is a special local product in south China. It is both vegetable and fruit. Near infrared spectroscopy was widely used for fruit and vegetable quality evaluation. The objective of this research was to study whether Chufa MT-firmness can be nondestructively measured by NIR technology and chemometrics methods. Two hundreds and thirty-nine samples were collected from two different cultivate regions and in each region three plots were chosen. NIR spectral data were acquired in the spectral region between 800 nm and 2500 nm using Nicolet FT-NIR spectrometer. Firmness was detected by a biomaterial universal testing machine. Chemometrics methods of PLS, PCR and SMLR were applied to establish statistical models for establishing the relationship between Chufa NIR spectra and MT-firmness in three different spectral regions of 800-2500 nm, 830-1250 nm and 860-1090 nm. The PLS model educed better results than PCR and SMLR models. And for the three spectral regions, the full spectral region of 800-2500 nm was better than other two. The correlation coefficient (r), root mean square error of calibration (RMSEC), root mean square error of prediction (RMSEP) and root mean square error of cross validation (RMSECV) of the PLS model in the range of 800-2500 nm were 0.74, 4.96 N, 5.63 N and 5.38 N respectively.

Paper Details

Date Published: 8 November 2005
PDF: 8 pages
Proc. SPIE 5996, Optical Sensors and Sensing Systems for Natural Resources and Food Safety and Quality, 59960K (8 November 2005); doi: 10.1117/12.630984
Show Author Affiliations
Guang Ma, Zhejiang Univ. (China)
Jinhua College of Profession and Technology (China)
Yibin Ying, Zhejiang Univ. (China)
Xiaping Fu, Zhejiang Univ. (China)
Huishan Lu, Zhejiang Univ. (China)
Haiyan Yu, Zhejiang Univ. (China)
Yande Liu, Zhejiang Univ. (China)

Published in SPIE Proceedings Vol. 5996:
Optical Sensors and Sensing Systems for Natural Resources and Food Safety and Quality
Yud-Ren Chen; George E. Meyer; Shu-I Tu, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?