Determining peanut moisture content by scattering coefficient

Ma, Fangyan; Wang, Dongwei; Yin, Yanlong; Yin, Hang; Song, Chao; Xu, Xin; Sun, Yun-Ming; Xue, Yiwei; Zhao, Liqing

doi:10.1016/j.jfoodeng.2022.111398

Cited by 5 publications

(4 citation statements)

References 19 publications

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“…where , , , A B C D are the elements of the matrix; ε is the effective dielectric constant of the transmission line medium; f is the frequency; c is the speed of light; j is an imaginary unit; α is the attenuation due to the loss mechanism of the transmission line itself; and = Ω According to the cascading characteristics of the transmission line, the transmission matrix of the entire network is the product of each transmission matrix, as shown in Equation (6). The relationship between the port scattering parameter 11 S and the transmission matrix ( ) T ABCD of the stripline detection device is shown in Equation (7).…”

Section: Principle Of Dielectric Constant Measurementmentioning

confidence: 99%

“…The reflection coefficient 11 S of the stripline is measured using the vector network analyzer, and then the dielectric constant of the wheat to be measured is calculated. According to the cascading characteristics of the transmission line, the transmission matrix of the entire network is the product of each transmission matrix, as shown in Equation (6). The relationship between the port scattering parameter S 11 and the transmission matrix T(ABCD) of the stripline detection device is shown in Equation (7).…”

Section: Principle Of Dielectric Constant Measurementmentioning

confidence: 99%

“…At present, the methods employed to measure the moisture content of wheat mainly include the capacitance method [2,3], coaxial probe method, resonant cavity method [4], free space method [5][6][7][8], and so on. These methods have their limitations when performing actual detection [9][10][11][12][13].…”

Section: Introductionmentioning

confidence: 99%

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Design and Evaluation of Wheat Moisture Content Detection Device Based on a Stripline

Song,

Zhang,

et al. 2024

Agriculture

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The detection of the moisture content of wheat is an important index used to measure the quality and preservation of wheat. In order to rapidly and non-destructively detect the moisture content of wheat, in this study, we designed a stripline detection device that measures 151 frequency points in the 50–200 MHz frequency range with a vector network analyzer. Random forest (RF), extreme learning machine (ELM), and BP neural network prediction models were established, using the frequency, temperature, volume density and dielectric constant as input and the water content as output. It was shown that, in the frequency range 50–200 MHz, the permittivity of wheat decreases as the frequency increases, and that this is negatively correlated. The dielectric constant of wheat increases as the moisture content, temperature, and bulk density increase, and these are positively correlated. The random forest (RF) prediction model, which uses the frequency, temperature, effective dielectric constant εeff. and volume density as inputs and the wheat moisture content as the output, demonstrates the best performance. The determination coefficient (R2) = 0.99977, the mean absolute error (MAE) = 0.044368, the mean square error (MAE) = 0.0053011, and the root mean square error (RMSE) = 0.072809. This study provides a new device and method for the detection of the moisture content of wheat. The device is small and is not easily disturbed by the external environment. It can be measured in a variety of conditions and is important for the development of low-cost, high-precision, and portable devices for the detection of the moisture content of wheat.

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Section: Principle Of Dielectric Constant Measurementmentioning

confidence: 99%

Section: Principle Of Dielectric Constant Measurementmentioning

confidence: 99%

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Design and Evaluation of Wheat Moisture Content Detection Device Based on a Stripline

Song,

Zhang,

et al. 2024

Agriculture

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“…Due to higher quality penetration and the advantages of nondestructive and rapid detection, the microwave measurement method is gradually being applied in crop MC detection [11][12][13][14][15]. Shivling et al [16] developed a patch antenna based on microwave resonance technology.…”

Section: Introductionmentioning

confidence: 99%

Establishing a Prediction Model for Tea Leaf Moisture Content Using the Free-Space Method’s Measured Scattering Coefficient

Yin

Wang

et al. 2023

Agriculture

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The rapid and nondestructive detection of tea leaf moisture content (MC) is of great significance to processing tea with an automatic assembly line. This study proposes an MC detection method based on microwave scattering parameters (SPs). Through the established free-space electromagnetic measurement device, 901 different frequency points are taken between 2.45 and 6 GHz using a vector network analyzer (VNA). The SPs of tea leaves with different moisture contents (5.72–55.26%) at different bulk density and different sample thicknesses were measured. The relationship between frequency, S21 amplitude and moisture content, thickness, and bulk density of tea was analyzed using correlation coefficients, significance analysis, and model construction. Back propagation (BP) neural network, decision tree (DT), and random forest (RF) MC prediction models were established with the frequency, amplitude, and phase of the SPs, thickness, and bulk density of the samples as inputs. The results showed that the RF-based model had the best performance, with determination coefficient (R2) = 0.998, mean absolute error (MAE) = 0.242, and root mean square error (RMSE) = 0.614. Compared to other nondestructive testing processes for tea, this method is simpler and more accurate. This study provides a new method for the detection of tea MC, which may have potential applications in tea processing.

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