Li Chenxiao, Yu Xiaoting, Zhao Chenyu, Ren Yuan, Xu Yanlei. Non-destructive detection of moisture content of leafy vegetables based on microwave free space traveling-standing wave method[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2021, 37(11): 307-314. DOI: 10.11975/j.issn.1002-6819.2021.11.035
    Citation: Li Chenxiao, Yu Xiaoting, Zhao Chenyu, Ren Yuan, Xu Yanlei. Non-destructive detection of moisture content of leafy vegetables based on microwave free space traveling-standing wave method[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2021, 37(11): 307-314. DOI: 10.11975/j.issn.1002-6819.2021.11.035

    Non-destructive detection of moisture content of leafy vegetables based on microwave free space traveling-standing wave method

    • Vegetables are one of the most essential food products for body health in daily life. Edible parts are normally reserved in roots, stems, and leaves of plants, particularly containing 70%-98% of water, rich chlorophyll, vitamins, and minerals. Vegetable freshness has also been one of the key factors affecting food quality. The storage time, moisture, chlorophyll, and carotene content usually determine the vegetable freshness. A chemical or spectral analysis can be used to measure the chlorophyll and carotene content, but the time-consuming and laborious procedure cannot achieve rapid and real-time detection in intelligent agriculture. Additionally, the storage time depended mainly on the storage environment. In this study, non-destructive detection of freshness was investigated to predict the moisture content of the vegetable using free space traveling-standing wave attenuation. The microwave method was characterized by fast, non-destructive, and high precision, suitable for the detection of moisture content in many fields, compared with the traditional drying, azeotropic distillation, capacitance, resistance, and infrared methods. Nevertheless, some specific measuring errors were found in the detection of vegetable moisture content. The reason was that the microwave was easy to penetrate the sample, and produce multiple reflections because the leaves of the vegetable were thin. Therefore, free space travelling-standing wave was selected to predict the freshness of the vegetable. The changes of moisture content were explored in vegetable leaves during storage, using the traveling-standing wave formed by multiple reflections in the system. The network structure was relatively simple without the need for complex equipment, such as a vector network analyzer. The system was composed of a microwave oscillator, a microwave transmitting antenna, a receiving horn antenna, a detector, a sample container, a slide rail, and a controller. The X-band of the microwave was selected, because of the strong dipole moment of water molecules at microwave frequency. Particularly, the electric energy was strongly absorbed by water, and then the polarization reaction occurred inside the material, when the external electric field was applied to the water-containing material. By contrast, the microwave frequency in the X-band was facilitated more sensitive to the change of moisture content, where the dielectric constant and dielectric loss factor changed obviously. A voltage conversion circuit was designed to convert the microwave into voltage signals. STM32F103ZET6 micro control unit was used as the controller. An internal program was designed to realize microwave data acquisition, system control, data processing, and display output. Fresh and intact Chinese cabbage and lettuce without mechanical damages in the greenhouse were taken as the research objects. 226 groups of experimental data were collected, where 50 groups were used as the modeling dataset, and the remaining 176 groups were the verification dataset. Linear regression was used to establish the prediction models of moisture content in vegetables. The prediction model was then written into the measurement system to realize the subsequent prediction of water content in vegetables. The measurement results showed that the goodness-of-fit values of prediction equations were 0.992 0 and 0.991 9, while the Root Mean Square Error(RMSE) errors were 1.188% and 0.803%, and the performance standard errors were 1.071% and 1.179%, for the water content of cabbage and lettuce, respectively, compared with the standard direct drying released in GB 5009.3-2016. Consequently, a rapid, non-destructive, and high-precision detection of vegetable moisture content was realized without multiple reflections in the process of microwave measurement. The simple device with excellent practicability can also be expected to serve food processing and storage in modern agricultural production.
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