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Nano vector network analyzer effectively measures peanut moisture content

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Abstract

Moisture content is an important index in peanut (Arachis hypogaea) production and storage. To achieve the accurate and rapid nondestructive detection of peanut moisture content, we designed a detection device that utilizes a low-cost vector network analyzer (VNA). The aim of the study was to compare the performance of the low-cost VNA with that of a commercial VNA to determine its suitability as a more economical replacement. Peanut pod samples with different moisture contents were used as the research object. The low-cost VNA was used to measure the scattering parameters of peanut pods with different moisture contents using the microwave free space method. The measured scattering parameters were compared with the actual moisture content of peanut pods using the XGBoost algorithm, and a model of peanut pod moisture measurement using scattering parameters was obtained. To reduce the influence of redundant frequency on the model, the measured frequency was screened using the step, equal division, and competitive adaptive reweighted sampling (CARS) methods. The results showed that both the equal division and CARS method effectively screened the frequency. The equal division method produced the best model with a coefficient of variation (R2) value of 0.9990, mean square error (MSE) of 0.1064, root mean square error (RMSE) of 0.3262, and mean absolute error (MAE) of 0.1937. Furthermore, the device displayed a low percentage of error, indicating its suitability for nondestructive testing of peanut pod moisture content. When the actual moisture content was 35.57%, the maximum error of the predicted value was 1.52%, indicating that the device meets the requirements of nondestructive testing of peanut pod moisture content.

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Acknowledgements

This study was supported by the National Natural Science Foundation of China [Grant Number 32071911], National Modern Agricultural Industry Technology System Post Scientist Project [grant number CARS-13, National Peanut Industry Technology System–Sowing and Field Management Mechanization Post], Shandong Modern Agricultural Industry System Wheat Industry Innovation Team [Grant Number SDIT-01-12], and Qingdao Agricultural University Doctoral Start-up Fund [Grant Number 663-1119049].

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Authors and Affiliations

  1. College of Mechanical and Electrical Engineering, Qingdao Agricultural University, Qingdao, 266109, People’s Republic of China

    Fangyan Ma, **npei Zhang, Dongwei Wang, **aoning He, Yuanyuan Yin, Hang Yin & Liqing Zhao

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  1. Fangyan Ma
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  2. **npei Zhang
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  3. Dongwei Wang
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  5. Yuanyuan Yin
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  7. Liqing Zhao
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Correspondence to Liqing Zhao.

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Ma, F., Zhang, X., Wang, D. et al. Nano vector network analyzer effectively measures peanut moisture content. Food Measure 17, 6026–6038 (2023). https://doi.org/10.1007/s11694-023-02093-2

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