Measurements and analysis of water content in winter wheat leaf based on terahertz spectroscopy
作者机构：Beijing Research Center for Information Technology in AgricultureBeijing 100097China Beijing Key Laboratory of Digital PlantBeijing 100097China Beijing Research Center of Intelligent Equipment for AgricultureBeijing 100097China Key Laboratory of Quantitative Remote Sensing in Agriculture of Ministry of AgricultureBeijing 100097China
出 版 物：《International Journal of Agricultural and Biological Engineering》 (国际农业与生物工程学报（英文）)
年 卷 期：2018年第11卷第3期
页 面：178-182页
核心收录：
基 金：This work was supported in part by the National Key Research and Development Project Fund Project(Grant No.2016YFD0702002) Beijing Academy of Agriculture and Forestry Innovation team Project(Grant No.JNKYT201604) Construction Project of Scientific Research and Innovation Platform of Beijing Academy of Agricultural and Forestry Sciences for 2018(Grant No.PT2018-23) Beijing Academy of Agriculture and Forestry International Cooperation Fund(Grant No.GJHZ2017-7)
主 题：terahertz spectroscopy winter wheat gravimetric water content(GWC) partial least squares method
摘 要：Wheat is a major grain crop in *** is one of the most important factors which influence the lifecycle and yield of *** is of great significance to study the water content at the key stages of wheat growth in order to make irrigation decision to raise its *** Terahertz(THz)spectroscopy is a brand new sensing technology and sensitive to water absorption,the relationship between terahertz spectra and water content in winter wheat leaf was investigated and a preliminary result was presented in this *** winter wheat leaves samples with diverse range of water content(42.8%-72.5%)were *** Terahertz time domain spectra(THz-TDS)were first obtained and then transformed into Frequency-domain amplitude with the Fast Fourier Transformation(FFT)*** absorption and refractive index spectra were then *** spectra were linearly fitted to obtain the slope and intercept used for building a calibration *** partial least squares(PLS)method and linear regression were employed to establish models to determine leaf water content in the winter *** predicted correlation coefficient and the root mean square error of the optimal model established with the Frequency-domain amplitude parameter at 0.3 THz by linear regression were 0.812%and 4.4%,*** results showed that terahertz spectroscopy performed well in water content prediction and could be an effective and potential method for leaf water content measurement in winter wheat.
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