Title :
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
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;
Conference_Titel :
New Technology of Agricultural Engineering (ICAE), 2011 International Conference on
Conference_Location :
Zibo
Print_ISBN :
978-1-4244-9574-0
DOI :
10.1109/ICAE.2011.5943947
