In this study, the effect of drying approaches in conjunction with variable temperature and tempering on the physicochemical quality of rice was investigated. The development of fissures, head rice yield, taste quality, textural properties, and microstructure of rice with different drying approaches were evaluated by employing principal component analysis (PCA). The results showed that increasing the tempering treatment could enhance the physicochemical quality of rice, and that the different drying approaches had a significant influence (P < 0.05) on the development of fissures, head rice yield, taste quality, and textural properties. High temperatures result in partial gelatinization of the starch, destruction of the starch granules, and an increase in fissures, as revealed by the microstructure of rice with different drying approaches. In addition, the drying approaches with a variable temperature of Δ0 (35 °C), Δ5 (45 °C–50 °C), and Δ0 (45 °C) in combination with the tempering treatment exhibited a high overall physicochemical quality. This study offers a point of reference for further research into the changes in the physicochemical quality of rice during drying.

Aiming at the problem of poor uniformity and stability of fertilizer discharge caused by the operation of the fertilizer discharger in the variable fertilization operation of rice. Combined with the agronomic requirements of deep fertilization on the northeast side, an impeller type variable side deep fertilizer was designed. According to the change of the prescription map, change the adjustment factors to achieve reasonable fertilization. Based on EDEM simulation, using the fertilizer discharge stability and uniformity coefficient of variation as indicators, under different impeller blades, different impeller speeds and different fertilizer discharge port angles, a secondary orthogonal rotation combination test was carried out, using Design-Expert. V8.0.6.1 is analyzed and tested, the regression equation and the response surface diagram are obtained, the interaction between the influencing factors is analyzed, and the best combination is determined. It is concluded that the stability and uniformity coefficient of variation of fertilizer discharge have reached the quality evaluation index of fertilization machinery According to technical specifications, the coefficient of variation of stability is 0.67%~2.85%, and the coefficient of variation of uniformity is 2.7%~16.4%. When the number of blades is 6, the fan angle of the fertilizer outlet is 35.7°, and the impeller speed is 18.85 r·min-1, the minimum variation coefficient of stability is 0.67%, and the minimum variation coefficient of uniformity is 2.1%. The bench test results are basically consistent with the optimal combination of simulation, and meet the design requirements.

To solve the problems of poor stability and low monitoring precision in the online detection of rice moisture in the drying tower, we designed an online detection device for rice moisture at the outlet of the drying tower. The structure of a tri-plate capacitor was adopted, and the electrostatic field of the tri-plate capacitor was simulated using COMSOL software. A central composite design of three factors and five levels was carried out with the thickness, spacing, and area of the plates as the influencing factors and the capacitance-specific sensitivity as the test index. This device was composed of a dynamic acquisition device and a detection system. The dynamic sampling device was found to achieve dynamic continuous sampling and static intermittent measurements of rice using a ten-shaped leaf plate structure. The hardware circuit of the inspection system with STM32F407ZGT6 as the main control chip was designed to realize stable communication between the master and slave computers. Additionally, an optimized BP neural network prediction model based on the genetic algorithm was established using the MATLAB software. Indoor static and dynamic verification tests were also carried out. The results showed that the optimal plate structure parameter combination includes a plate thickness of 1 mm, plate spacing of 100 mm, and relative area of 18,000.069 mm² while satisfying the mechanical design and practical application needs of the device. The structure of the BP neural network was 2-90-1, the length of individual code in the genetic algorithm was 361, and the prediction model was trained 765 times to obtain a minimum MSE value of 1.9683 × 10⁻⁵, which was lower than that of the unoptimized BP neural network with an MSE of 7.1215 × 10⁻⁴. The mean relative error of the device was 1.44% under the static test and 2.103% under the dynamic test, which met the accuracy requirements for the design of the device.

The current real-time detection of sowing depth has the problems of low detection accuracy and poor reliability. After analyzing the movement mechanism of the sowing monomer parallel four-bar linkage, an improved adaptive Kalman filtering method for sowing depth detection is proposed. The method uses two MPU6050 attitude sensors. The difference between the rotation angle of the parallel four-bar linkage and the attitude angle of the sowing monomer is used as the relative rotation angle of the parallel four-bar linkage relative to the sowing monomer. The sowing monomer parallel four-bar linkage has the characteristics of up–down translation, and sowing depth changes can be obtained by converting the angle data. By using moving average filter, particle filter, Kalman filter, and improved adaptive Kalman filter to fuse the data of MPU6050 in two positions and perform MATLAB simulation, the average mean squared errors of the above four filtering algorithms are 0.12645, 0.05545, 0.03785, and 0.0189, respectively. In the end, the experiment of sowing depth detection was carried out, and it was found that the improved adaptive Kalman filter algorithm detects the smallest sowing depth mean squared error, which is 0.0636, and the algorithm can track data changes better. At the same time, it is more adaptable to noise and obtains an ideal filtering effect.