The relationship between electrical capacitance-based dielectric constant and soil water content

Wu, Shi Yan; Zhou, Qi; Wang, Gang; Yang, Lei; Ling, Cheng

doi:10.1007/s12665-010-0585-4

Cited by 25 publications

(18 citation statements)

References 29 publications

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“…The next equation comes from [25], which is using coaxial transmission system and using soil samples with wide range of soil textures: θ ¼À0:0286 þ 0:02435ε À 0:0003421ε 2 þ 0:00000237ε 3 (13) Equations (5)- (8) are used for measurement at a frequency of 100 MHz. [13] proposed an empirical model where permittivity measurement was measured based on capacitance. This experiment used a type of quartz sand with a range of particle sizes between 0.15 and 0.9 mm:…”

Section: Model With One Parametermentioning

confidence: 99%

“…Various techniques in the measurement of contamination and water content of soil have been discussed in literatures (e.g., [7][8][9][10][11][12]). Based on previous studies, soil water content measurement techniques are widely used as an electromagnetic method [13] such as time domain reflectometry [14], ground-penetrating radar (GPR) [8], and electrical capacitance [15]. These all methods measure the value of relative permittivity of soil to find soil moisture water content.…”

Section: Introductionmentioning

confidence: 99%

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Dielectric Analysis Model for Measurement of Soil Moisture Water Content Using Electrical Capacitance Volume Tomography

Mukhlisin¹,

Saputra²

2020

Modern Applications of Electrostatics and Dielectrics

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Electromagnetic methods have been widely used in the measurement of the water content of the soil. These methods utilize the permittivity as electrical properties of the soil, to determine the moisture content of the soil. Since the measurements are carried out indirectly, a calibration between permittivity and the water content of the soil is needed. Generally, the calibration method is generated by using an empirical and mixing model. This study presents a proposed model of calibration by using a normalization approach to calibrate the value of the permittivity of the water content of the soil. Then the model was applied using electrical capacitance volume tomography (ECVT) to image soil water content during infiltration of water in a soil column. Granular and silty sand were used as soil material in the experiments. The result showed that the model for measuring moisture water content can be seen in each layer during soil water infiltration in the soil column.

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Section: Model With One Parametermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Dielectric Analysis Model for Measurement of Soil Moisture Water Content Using Electrical Capacitance Volume Tomography

Mukhlisin¹,

Saputra²

2020

Modern Applications of Electrostatics and Dielectrics

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“…Dielectric detection technology is based on the interaction of external electric field to the internal physiological and chemical changes of the sample (Hamed, Zorrig, & Hamzaoui, ; Wu, Zhou, Wang, Yang, & Ling, ; Zhang, Zhou, Ling, & Wang, ). It could represent the whole sample information, and mainly described by the relative dielectric constant, dielectric loss factor, and dielectric loss angle tangent (Davis, Matovic, & Pollard, ; Pan, McDonald, Via, Fulton, & Hung, ).…”

Section: Introductionmentioning

confidence: 99%

Nondestructive detection for moisture content in green tea based on dielectric properties and VISSA‐GWO‐SVR algorithm

Sun

Tian

et al. 2020

J Food Process Preserv

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Moisture content was an important indicator to measure quality of green tea. In order to detect moisture content in green tea effectively and accurately, nondestructive detection for moisture content in green tea based on dielectric technology was proposed in this paper. Inductance-capacitance-resistance (LCR) measuring instrument and coaxial-line cylinder capacitor were used to collect dielectric data. The characteristic frequency points were extracted by successive projection algorithm (SPA) and variable iterative space shrinkage approach (VISSA). Support vector regression (SVR) was used to establish prediction models based on full frequency points and characteristic frequency points. The model results demonstrated that VISSA-SVR model based on dielectric loss factor ε″ performed best among all the prediction models, but the prediction accuracy was not enough, so the gray wolf optimization (GWO) algorithm was introduced to optimize the parameters (c and g) in SVR model. Furthermore, the best prediction performances for detecting moisture content in green tea was obtained, with the determination coefficient and root mean square errors (RMSEs) for prediction were 0.9695 and 0.0602, respectively. Therefore, dielectric technology combined with VISSA-GWO-SVR model is feasible for nondestructive determination of the moisture content in tea, which will provide a promising tool for the moisture content detection of other agricultural products. Practical applicationsWell understanding moisture content in tea is great importance. The practical application of this paper is to develop a novel method for moisture content detection in tea using dielectric technology. Compared with traditional methods, dielectric technology can be used to detect moisture content in tea nondestructively and accurately. Characteristic frequency selection algorithms are used to remove the redundant information in the data, and optimization algorithm is used to improve the performance of the model. Thus, dielectric technology combined with the optimal model is considered the most promising method for detecting the moisture content in green tea.How to cite this article: Sun J, Tian Y, Wu X, et al.Nondestructive detection for moisture content in green tea based on dielectric properties and VISSA-GWO-SVR algorithm. J Food Process Preserv. 2020;44:e14421.

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“…Through comparative analysis of various methods and theories, we concluded that the dielectric method was the most promising one. Among the dielectric methods, capacitance method has unique advantages compared with other dielectric methods, including (1) the ability to measure dynamic conditions [13]; (2) low cost of the measurement instruments and minimal site disturbance [14]; and (3) the adaptivity of the sensor geometry, facilitating the development of a variety of configurations [15]. It can be seen that the capacitance method may have great potential in dynamically capturing soil/soilless substrate water content practically.…”

Section: Introductionmentioning

confidence: 99%

“…Hence, based on equation (11)-(13), we can derive the sensor in air and water are U 0 and U 1 respectively; equation(14) results in…”

mentioning

confidence: 99%

Design and Calibration of the Unilateral Sensitive Soil Moisture Sensor

Sheng

Zhang

et al. 2015

IEEE Sensors J.

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Abstract-Reliable and affordable moisture sensors with a simplified calibration process for obtaining the water content information of soil/soilless substrates were limited. In this paper, an unilateral sensitive capacitive soil moisture sensor, based on the improved ECH2O sensor probe structure, was presented. Through simulating the relationship between the ratio of plate space and plate width (a/b) and probe sensitivity, sensitive depth respectively, the size of the sensor was determined with ANSYS firstly. Capacitance measurement circuit based on resonant principle was then designed. The relationship between the output of the sensor and the soil water content calibration model (β parameter model), was investigated. As a result, we proposed a two-step calibration β method. Experimental results showed that β parameter model appropriately described the relationship between the output and the soil water content, the minimum correlation coefficient R 2 =0.9554 in the soil, peat, perlite, vinegar residue. The measurement error of β parameter model was less than 0.025 units except in perlite. The error caused by the change of bulk density was less than 0.025 units in peat and vinegar residue. Therefore, the two-step calibration β method is suitable for calibrating the sensor.

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The relationship between electrical capacitance-based dielectric constant and soil water content

Cited by 25 publications

References 29 publications

Dielectric Analysis Model for Measurement of Soil Moisture Water Content Using Electrical Capacitance Volume Tomography

Dielectric Analysis Model for Measurement of Soil Moisture Water Content Using Electrical Capacitance Volume Tomography

Nondestructive detection for moisture content in green tea based on dielectric properties and VISSA‐GWO‐SVR algorithm

Design and Calibration of the Unilateral Sensitive Soil Moisture Sensor

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