DocumentCode :
2448747
Title :
Measurement of lettuce leaf chlorophyll content by means of VIS-NIR spectroscopy
Author :
Zhu, Yongli ; Mao, Hanping ; Li, Pingping ; Wu, Yanyou
Author_Institution :
Key Lab. of Modern Agric. Equip. & Technol., Jiangsu Univ., Zhenjiang, China
fYear :
2011
fDate :
24-26 June 2011
Firstpage :
2250
Lastpage :
2253
Abstract :
Time and fast diagnosis for nitrogen nutrition in vegetables is useful for fertilization management and improving the product quality. In order to develop a method for rapid detection of leaf nitrogen content in lettuce, visible and near infrared (Vis-NIR) spectroradiometer was used to collect the spectral data, and the leaf chlorophyll content were obtained by chlorophyll meter (SPAD 502). Different spectra preprocessing techniques, which included moving average filter (MAF), Savitzky-Golay filter (SGF), first derivative (FD),second derivative (SD), normal normalization (NM) and their combination, were used for select the best chlorophyll content prediction model. And stepwise regression (SWR) and partial least squares regression (PLS) were applied to choose the characteristic wavelengths. It was confirmed that the characteristic wavelength was at 368 nm, 694 nm, 744 nm and 825 nm, respectively. Based on these wavelengths, a linear regression model was performed with correlation coefficient 0.9583 and root mean squared error of prediction (RMSEP) 2.695. Therefore, it was concluded that the Vis-NIR technique could be an available method for rapid detection of lettuce leaf chlorophyll content.
Keywords :
agricultural products; least squares approximations; nitrogen; quality management; regression analysis; Savitzky-Golay filter; VIS-NIR spectroscopy; chlorophyll meter; fertilization management; first derivative; leaf nitrogen content; lettuce leaf chlorophyll content; linear regression model; moving average filter; near infrared spectroradiometer; nitrogen nutrition; normal normalization; partial least squares regression; product quality; second derivative; stepwise regression; vegetables; Nitrogen; Presses; Soil; Solids; Spectroradiometers; Spectroscopy; Sun; Vis-NIR spectroscopy; characteristic band; chlorophyll content; lettuce; nondestructive measurement;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Remote Sensing, Environment and Transportation Engineering (RSETE), 2011 International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4244-9172-8
Type :
conf
DOI :
10.1109/RSETE.2011.5964758
Filename :
5964758
Link To Document :
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