Establishing a Low-Temperature Maize Kernel Moisture Content Prediction Model Based on Dielectric Constant Measurement

Shuhao Wang, Songling Du, Yuanyuan Yin, Chao Song, Chuang Liu, Rui Qian and Liqing Zhao ()
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Shuhao Wang: College of Mechanical and Electrical Engineering, Qingdao Agricultural University, Qingdao 266109, China
Songling Du: College of Mechanical and Electrical Engineering, Qingdao Agricultural University, Qingdao 266109, China
Yuanyuan Yin: College of Mechanical and Electrical Engineering, Qingdao Agricultural University, Qingdao 266109, China
Chao Song: College of Mechanical and Electrical Engineering, Qingdao Agricultural University, Qingdao 266109, China
Chuang Liu: College of Mechanical and Electrical Engineering, Qingdao Agricultural University, Qingdao 266109, China
Rui Qian: College of Mechanical and Electrical Engineering, Qingdao Agricultural University, Qingdao 266109, China
Liqing Zhao: College of Mechanical and Electrical Engineering, Qingdao Agricultural University, Qingdao 266109, China

Agriculture, 2025, vol. 15, issue 5, 1-22

Abstract: Detecting the moisture content of stored maize kernels is critical for minimizing post-harvest losses. To measure the moisture content of maize kernels under low-temperature conditions, a small-strip transmission line device was employed to construct a non-destructive measurement platform. The dielectric constant of maize kernels with varying moisture content was measured at temperatures ranging from −15 °C to 20 °C and frequencies between 1 and 200 MHz. By using the dielectric constant, frequency, and temperature as input variables, along with volume density and scattering parameter characteristics, three moisture content prediction models—SPO-SVM, XGBoost, and GA-BP—were established. The results show that temperature significantly affects the dielectric constant of maize kernels, especially when the moisture levels exceed 22.4%. The prediction model significantly improves the prediction accuracy under low-temperature conditions after introducing the volume density feature. Furthermore, incorporating the multi-phase and amplitude characteristics of scattering parameters further improves the model’s performance. This study verifies the mechanism and behavior of dielectric constant variations in maize kernels under low-temperature conditions. The proposed model effectively mitigates measurement errors caused by the icing of free water and is well suited for measuring maize moisture content under low-temperature conditions.

Keywords: scattering parameters; maize kernels; moisture content; low temperature (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2025
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