Detection of Water Content in Rapeseed Leaves Using Terahertz Spectroscopy

Pengcheng Nie; Fangfang Qu; Lei Lin; Tao Dong; Yong He; Yongni Shao; Yi Zhang

doi:10.3390/s17122830

Detection of Water Content in Rapeseed Leaves Using Terahertz Spectroscopy

Sensors (Basel). 2017 Dec 6;17(12):2830. doi: 10.3390/s17122830.

Authors

Pengcheng Nie^{1

2}, Fangfang Qu³, Lei Lin⁴, Tao Dong⁵, Yong He⁶, Yongni Shao⁷, Yi Zhang⁸

Affiliations

¹ College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, China. npc2012@zju.edu.cn.
² State Key Laboratory of Modern Optical Instruments, Zhejiang University, Hangzhou 310027, China. npc2012@zju.edu.cn.
³ College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, China. ffqu@zju.edu.cn.
⁴ College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, China. linlei2016@zju.edu.cn.
⁵ College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, China. dt2016@zju.edu.cn.
⁶ College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, China. yhe@zju.edu.cn.
⁷ Shanghai Key Lab of Modern Optical System, University of Shanghai for Science and Technology No. 516, Jungong Road, Shanghai 200093, China. ynshao@zju.edu.cn.
⁸ Daheng Scitech Mansion, No. 3 Suzhou Street, Haidian District, Beijing 10080, China. zhangyi@cdhcorp.com.cn.

Abstract

The terahertz (THz) spectra of rapeseed leaves with different water content (WC) were investigated. The transmission and absorption spectra in the range of 0.3-2 THz were measured by using THz time-domain spectroscopy. The mean transmittance and absorption coefficients were applied to analyze the change regulation of WC. In addition, the Savitzky-Golay method was performed to preprocess the spectra. Then, the partial least squares (PLS), kernel PLS (KPLS), and Boosting-PLS were conducted to establish models for predicting WC based on the processed transmission and absorption spectra. Reliable results were obtained by these three methods. KPLS generated the best prediction accuracy of WC. The prediction coefficient correlation (Rval) and root mean square error (RMSEP) of KPLS based on transmission were Rval = 0.8508, RMSEP = 0.1015, and that based on absorption were Rval = 0.8574, RMSEP = 0.1009. Results demonstrated that THz spectroscopy combined with modeling methods provided an efficient and feasible technique for detecting plant physiological information.

Keywords: Boosting-PLS; kernel PLS; rapeseed leaf; terahertz spectroscopy; water content.