Technique for Measuring Dielectric Loss Tangent

Burdick, Glenn A.; Hickman, Travis G.

doi:10.1063/1.1720413

Cited by 1 publication

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“…In recent years, researchers have put forward several indirect methods for rapid and non-destructive measurement of rice grain moisture or other cereal crops [6][7][8][9]. Commonly used methods include the resistance method, capacitance method, spectroscopic method and dielectric loss angle method.…”

Section: Introductionmentioning

confidence: 99%

Rapid-Detection Sensor for Rice Grain Moisture Based on NIR Spectroscopy

Lin

Xiao

et al. 2019

Applied Sciences

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Rice grain moisture has a great impact on th production and storage storage quality of rice. The main objective of this study was to design and develop a rapid-detection sensor for rice grain moisture based on the Near-infrared spectroscopy (NIR) characteristic band, aiming to realize its accurate and on-line measurement. In this paper, the NIR spectral information of grain samples with different moisture content was obtained using a portable NIR spectrometer. Then, the partial least squares (PLS) and competitive adaptive reweighted squares (CARS) were applied to model and analyze the spectral data to find the rice grain moisture NIR spectroscopy. As a result, the 1450 nm band was sensitive to the rice grain moisture and a rapid-detection sensor was developed with a 1450 nm light emitting diode (LED) light source, InGaAs photodiode, lens and filter, whose basic principle is to establish the relationship between the rice grain moisture and the measured voltage signal. To evaluate the sensor performance, rice grain samples with 13–30% moisture content were detected, the coefficient of determination R2 was 0.936, and the sum of squares for error (SSE) was 23.44. It is concluded that this study provides a spectroscopic measuring method, as well as developing an effective and accurate sensor for the rapid determination of rice grain moisture, which is of great significance for monitoring the quality of rice grain during its production, transportation and storage process.

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Section: Introductionmentioning

confidence: 99%