4.5 Article

Real-Time Measurement of Moisture Content of Paddy Rice Based on Microstrip Microwave Sensor Assisted by Machine Learning Strategies

期刊

CHEMOSENSORS
卷 10, 期 10, 页码 -

出版社

MDPI
DOI: 10.3390/chemosensors10100376

关键词

microstrip microwave sensor; microwave attenuation; phase shift; moisture content; random forest

资金

  1. National Key R&D Program of China [2019YFE0124600]

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This study developed a portable moisture measuring device based on microwave microstrip sensors. By optimizing sample thickness and incorporating environmental temperature and humidity, and using different prediction models, high accuracy moisture content prediction was achieved. The device has the advantages of real-time measurement, simple structure, convenient operation, low cost, and portability, and holds great significance for real-time measurement of agricultural products and the development of intelligent agricultural equipment.
Moisture content is extremely imoprtant to the processes of storage, packaging, and transportation of grains. In this study, a portable moisture measuring device was developed based on microwave microstrip sensors. The device is composed of three parts: a microwave circuit module, a real-time measurement module, and software to display the results. This work proposes an improvement measure by optimizing the thickness of paddy rice samples (8-13 cm) and adding the ambient temperatures and the moisture contents (13.66-27.02% w.b.) at a 3.00 GHz frequency. A random forest, decision tree, k-nearest neighbor, and support vector machine were applied to predict the moisture content in the paddy rice. Microwave characteristics, phase shift, and temperature compensation were selected as the input variables to the prediction models, which have achieved high accuracy. Among those prediction models, the random forest model yielded the best performance with highest accuracy and stability (R-2 = 0.99, RMSE = 0.28, MAE = 0.26). The device showed a relatively stable performance (the maximum average absolute error was 0.55%, the minimum absolute error was 0.17%, the mean standard deviation was 0.18%, the maximum standard deviation was 0.41%, and the minimum standard deviation was 0.08%) within the moisture content range of 13-30%. The instrument has the advantages of real-time, simple structure, convenient operation, low cost, and portability. This work is expected to provide an important reference for the real-time in situ measurement of agricultural products, and to be of great significance for the development of intelligent agricultural equipment.

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