Moisture Content Detection of Tomato Leaves Based on Electrical Impedance Spectroscopy

被引:2
|
作者
Tang, Lin [1 ]
Gao, Shengdong [1 ]
Wang, Wei [1 ]
Xiong, Xiufang [1 ]
Han, Wenting [1 ,2 ]
Li, Xingshu [1 ,2 ]
机构
[1] Northwest A&F Univ, Coll Mech & Elect Engn, Xianyang, Peoples R China
[2] Northwest A&F Univ, Inst Water Saving Agr Arid Areas China, Xianyang, Peoples R China
关键词
Electrical impedance spectroscopy; equivalent circuit model; leaf moisture content; random forest; WATER-CONTENT; STRESS; LEAF; DIAGNOSIS;
D O I
10.1080/00103624.2023.2274046
中图分类号
S3 [农学(农艺学)];
学科分类号
0901 ;
摘要
The rapid detection of moisture content in tomato leaves can provide an important basis for tomato cultivation. Compared with spectroscopy technology, image technology, and dielectric detection technology, electrical impedance spectroscopy (EIS) has the potential to analyze the internal components of leaf microstructure qualitatively and quantitatively, and the characteristics of fast detection and low cost. The moisture content in tomato leaves was detected effectively and accurately at the anthesis of the first inflorescence using the EIS method. The influence of reduction of moisture content on the impedance characteristics and equivalent circuit parameters was analyzed. The frequencies of different impedance characteristics were selected based on the out-of-bag (OOB) importance. Different regression algorithms, including partial least square regression (PLSR), back-propagation neural network (BPNN), and random forest (RF), were used for estimating the leaf moisture content (LMC). The LMC models based on different impedance characteristics and different methods were established and compared. The results demonstrated that the impedance modulus in the low-frequency region, the extracellular resistance (Re), and the intracellular resistance (Ri) increased first and then decreased with the decrease in the moisture content of the tomato leaves. The RF model established with the combination data had the best performance, with the coefficient of determination (R2), normalized root-mean-square error (NRMSE), and the ratio of performance of deviation (RPD) for prediction being 0.8861, 6.02%, and 2.95, respectively. Therefore, the EIS method combined with RF was a feasible and effective method to predict LMC, providing a promising tool for moisture content detection.
引用
收藏
页码:609 / 623
页数:15
相关论文
共 50 条
  • [31] Estimation of Chlorophyll Content in Apple Leaves Based on Imaging Spectroscopy
    Yu, Ruiyang
    Zhu, Xicun
    Cao, Shujing
    Xiong, Jingling
    Wen, Xin
    Jiang, Yuanmao
    Zhao, Gengxing
    JOURNAL OF APPLIED SPECTROSCOPY, 2019, 86 (03) : 457 - 464
  • [32] Correlation between near infrared spectroscopy and electrical techniques in measuring skin moisture content
    Mohamad, M.
    MSabbri, A. R.
    MatJafri, M. Z.
    Omar, A. F.
    9TH NATIONAL SEMINAR ON MEDICAL PHYSICS (NSMP2014), 2014, 546
  • [33] Research on vehicle-mounted soil electrical conductivity and moisture content detection system based on current-voltage six-terminal method and spectroscopy
    Wang, Dong
    Yang, Wei
    Meng, Chao
    Cao, Yongyan
    Li, Minzan
    COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2023, 205
  • [34] PREDICTION OF MOISTURE CONTENT IN CORN LEAVES BASED ON HYPERSPECTRAL IMAGING AND CHEMOMETRIC ANALYSIS
    Sun, Y.
    Chen, S. S.
    Ning, J. F.
    Han, W. T.
    Weckler, P. R.
    TRANSACTIONS OF THE ASABE, 2015, 58 (03) : 531 - 537
  • [35] Estimation models for water content of walnut leaves based on spectral moisture index
    Hu Z.
    Pan C.
    Pan X.
    Zhu B.
    Pan, Cunde, 1600, Chinese Society of Forestry (52): : 39 - 49
  • [36] Study on the Characteristic of Electrical Impedance Spectroscopy of Soybean Seeds and the Detection of Seed Viability
    Zhang, Qiong
    Zhu, Dazhou
    Hou, Ruifeng
    Pan, Dayu
    Wang, Xiaodong
    Sun, Zhihui
    Wang, Cheng
    INFORMATION AND AUTOMATION, 2011, 86 : 631 - +
  • [37] Evaluation of total flavonoid content of Labisia pumila leaves based on impedance measurements
    Jamaludin, D.
    Abd Aziz, S.
    Ahmad, D.
    Jaafar, H. Z. E.
    III INTERNATIONAL CONFERENCE ON AGRICULTURAL AND FOOD ENGINEERING, 2017, 1152 : 203 - 210
  • [38] Electrical impedance Spectroscopy of prostatic tissues
    Halter, R. J.
    Schned, A.
    Heaney, J.
    Hartov, A.
    Paulsen, K. D.
    13TH INTERNATIONAL CONFERENCE ON ELECTRICAL BIOIMPEDANCE AND THE 8TH CONFERENCE ON ELECTRICAL IMPEDANCE TOMOGRAPHY 2007, 2007, 17 : 126 - +
  • [39] Deep learning-based electrical impedance spectroscopy analysis for malignant and potentially malignant oral disorder detection
    Zhicheng Lin
    Zi-Qiang Lang
    Lingzhong Guo
    Dawn C Walker
    Malwina Matella
    Mengxiao Wang
    Craig Murdoch
    Scientific Reports, 15 (1)
  • [40] Glucose detection based on low-cost electrical impedance spectroscopy (EIS) using genetic algorithm.
    Guerra, Crystian
    Davey, Sebastian
    Fonthal, Faruk
    Cesar Calvo, Paulo
    2018 IEEE ANDESCON, 2018,