Determination of wet gluten in wheat based on wavelet de-noising and PLS

Author

Hexiao, Liu ; Laijun, Sun ; Mingliang, Liu ; Haibo, Qian ; Wenbo, Li ; Lekai, Wang ; Changjun, Dai ; Naixin, Zhao ; LanJin

Author_Institution

Key Lab. of Electron. Eng., Heilongjiang Univ., Harbin, China

fYear

2011

fDate

27-29 May 2011

Firstpage

958

Lastpage

962

Abstract

NIRS (Near Infrared Transmittance Spectroscopy) is a new analytic technique in analytical chemistry which is developing very quickly in recent years. It has quick, simple, and nondestructive characteristic. This study is based on the analysis of wheat by near infrared spectroscopy to predict the wet gluten in wheat. Using the wavelet transform to de-noise the spectrum firstly, on the basis of which, the partial least squares model of wheat wet gluten is established. The experimental results indicate that the R, MSE and Er are 0.9711, 1.155 and 3.371% respectively, which certificate that this model could predict the wet gluten in wheat accurately.

Keywords

chemical technology; crops; infrared spectra; least squares approximations; mean square error methods; nondestructive testing; signal denoising; wavelet transforms; MSE; NIRS; PLS; analytic technique; analytical chemistry; near infrared spectroscopy; near infrared transmittance spectroscopy; nondestructive characteristic; partial least squares model; wavelet denoising; wavelet transform; wet gluten determination; wheat wet gluten; Calibration; Mathematical model; Noise reduction; Predictive models; Spectroscopy; Wavelet transforms; PLS; Wavelet Transform De-noising; Wet Gluten; Wheat;

fLanguage

English

Publisher

ieee

Conference_Titel

New Technology of Agricultural Engineering (ICAE), 2011 International Conference on

Conference_Location

Zibo

Print_ISBN

978-1-4244-9574-0

Type

conf

DOI

10.1109/ICAE.2011.5943947

Filename

5943947