Design and Optimization of a Vibration-Assisted Crop Seed Drying Tray with Real-Time Moisture Monitoring

In modern agriculture, reducing the internal moisture content of crop seeds is essential to enhance the activity and mobility of seed oil molecules, thereby increasing oil yield while minimizing the risk of mold and deterioration. However, traditional drying methods often result in uneven heating, leading to seed scorching and diminished drying efficiency and economic returns. To address these limitations, this study proposes a novel thin-layer seed drying system incorporating a redesigned drying tray structure. Specifically, the system places the seed-bearing tray beneath a vibration module operating at a predetermined frequency. The vibration mechanism induces the uniform motion of the seeds, thereby preventing localized overheating (scalding) and enabling automatic weighing for the real-time monitoring of moisture reduction during the drying process. The advancement of wireless sensor technologies in agriculture has enabled the deployment of more refined, large-scale monitoring networks. In this work, a commercial chip-based piezoelectric vibration detection device was integrated into the experimental setup to collect time-domain response signals resulting from interactions among seeds, impurities, and the drying tray. These signals were used to construct a comprehensive database of seed collision signatures. To mitigate discontinuities in signal transmission caused by vibration and potential equipment failure, the shortest routing protocol (SRP) was implemented. Additionally, the system outage probability (OP) and a refined closed-form solution for signal transmission reliability were derived under a Rayleigh fading channel model. To validate the proposed method, a series of experiments were conducted to determine the optimal vibration frequencies for various seed types. The results demonstrated a reduction in seed scalding rate to 1.5%, a decrease in seed loss rate to 0.4%, and an increase in moisture monitoring accuracy to 97.0%. Compared to traditional drying approaches, the vibrating drying tray substantially reduced seed loss and effectively distinguished between seeds and impurities. Furthermore, the approach shows strong potential for broader applications in seed classification and moisture detection across different crop types.