Vector locus of an equivalent radius of the root in growing plants

Yamada, Masashi; Yamaura, Itsuo; Tanaka, Kyoko; Yajima, Masao; Takahashi, Nobuhide; Yamada, Kenta

doi:10.1109/imtc.2003.1207960

Cited by 3 publications

(3 citation statements)

References 5 publications

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“…Figure 3 shows the correlation coefficients between the actual and predicted moisture contents using the least-square method based on equations 2, 3, and 4 at different frequencies. The correlation was poor in the low-frequency range from 0.12 to 20 kHz, which might be because electric current at extremely low frequencies rarely passes through plant tissues (Zhang et al, 1990;Yamada et al, 2003). In the highfrequency range from 80 to 100 kHz, the correlation coefficients were all less than 0.68.…”

Section: Moisture Content Detection Modelmentioning

confidence: 95%

“…From the absolute values of the two coefficients, resistance had a higher effect on the prediction of moisture content than capacitance in the model. The reason might be that the measurements of capacitance and resistance were affected by different tissues in the leaves, causing different results (Yamada et al, 2003).Therefore, resistance can be considered a more important parameter than capacitance for the prediction of moisture content. Of course, compared with linear regression, the MLR analysis also had disadvantages, including high mathematical complexity, but this drawback did not affect the research.…”

Section: Moisture Content Detection Modelmentioning

confidence: 99%

“…Therefore, almost no current passes through the cell gap. However, with an increase of applied frequency, the electric current begins to flow through the extracellular and intracellular spaces because the plasma membrane and cell wall accumulate and release the electric charge in the same way as a capacitor (Zhang et al, 1990;Yamada et al, 2003).…”

Section: Verification Of Prediction Modelmentioning

confidence: 99%

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Electrical Properties Predict Wheat Leaf Moisture

Hao¹,

Hua²,

Xu³

et al. 2021

Transactions of the ASABE

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HighlightsA non-destructive prediction model for moisture content of wheat leaves was established based on electrical properties.The model based on a single property (capacitance or resistance) was improved by using both properties.The model accurately detected the moisture content of wheat leaves in real-time to avoid irrigation lag.The results provide a basis for real-time and targeted water-saving irrigation of winter wheat in an arid region.Abstract. In this study, we aimed to establish a non-destructive and rapid approach to monitor the moisture content of wheat leaves in Southern Xinjiang, China, and promptly acquire information on the physiological water demand of crops to guide precision irrigation. Wheat leaves were used as the research object. Using a custom-made clamped parallel-plate capacitor and LCR digital bridge meter, we determined the electrical properties (capacitance and resistance) of wheat leaves with various moisture contents within a frequency range from 0.12 to 100 kHz. Moreover, we explored the correlation between leaf moisture content and the electrical properties. Our data showed that leaf moisture exhibited the best correlation with the electrical properties at 50 kHz. Under these optimized conditions, a model for moisture measurement was established using a single-parameter method (capacitance or resistance). However, the estimated standard errors (RMSE) of this method were 3.29% (for resistance) and 3.49% (for capacitance), which were greater than the standard error of the measured moisture content (2%). Therefore, we developed an improved model using a two-parameter method (capacitance and resistance), and the estimated standard error was 2.68%, which was more feasible for predicting moisture content compared with the single-parameter method. The model was validated using eight groups of wheat leaf samples at the turning-green stage and the jointing stage, and the RMSE values were less than 2%. Our findings provide a scientific basis for real-time and targeted water-saving irrigation of wheat in arid areas of Southern Xinjiang. Keywords: Electrical property, Model, Moisture content, Precision irrigation, Wheat leaves.

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Section: Moisture Content Detection Modelmentioning

confidence: 95%

Section: Moisture Content Detection Modelmentioning

confidence: 99%

Section: Verification Of Prediction Modelmentioning

confidence: 99%

See 1 more Smart Citation

Electrical Properties Predict Wheat Leaf Moisture

Hao¹,

Hua²,

Xu³

et al. 2021

Transactions of the ASABE

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Moisture Content Measurement of Tea Leaves by Electrical Impedance and Capacitance

Mizukami

Sawai

Yamaguchi

2006

Biosystems Engineering

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Analysis of the Electrical Impedance of Tea Leaves During the Primary Drying Process

Mizukami¹,

Miyama²,

Sawai³

et al. 2006

J. Food Sci. Technol. Res.

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Frequency-dependent electrical impedance spectroscopy was used to characterize the intracellular and extracellular resistances, as well as the capacitance of the cell wall and cell membranes, of tea leaves during the primary drying process. At the beginning of the process, the extracellular resistance significantly decreased due to the leakage of electrolytes into the intracellular space as a result of pressurization by the spatula. When the drying process was prolonged, the extracellular resistance increased due to evaporation from the surface area of the tea leaves and the intracellular resistance also increased due to the decrease in the moisture content of the tea leaves. The capacitance of the cell wall and cell membranes decreased, with the assumptions that the temperature of the tea leaves had a negligible e#ect on the change in the capacitance and the cellular tissues were physical damaged. The deterioration and collapse of cellular tissues by pressurization was regarded as the main factor contributing to the decrease in the capacitance. These electrical behaviors observed in the primary drying process were a#ected by the material characteristics.

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Vector locus of an equivalent radius of the root in growing plants

Cited by 3 publications

References 5 publications

Electrical Properties Predict Wheat Leaf Moisture

Electrical Properties Predict Wheat Leaf Moisture

Moisture Content Measurement of Tea Leaves by Electrical Impedance and Capacitance

Analysis of the Electrical Impedance of Tea Leaves During the Primary Drying Process

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