Direct seeding of rice is a green planting technique because it reduces irrigation water and lowers agricultural production costs. A vacuum seed meter with a double hole for rice was developed to improve the planting accuracy of direct seeding and to meet the tiny seeding rate. The key components of the vacuum seed meter were theoretically analyzed and designed. The optimal parameters of the seed disturbance structure were determined by the Box-Behnken test using the quality of feed index (each group of holes is 1 to 2), miss index, and multiple index as test indices. The results of the Box-Behnken test showed that the optimal parameters were a height of the seed disturbance structure of 1.65 mm, a diameter of the upper arc of 98.87 mm, and a central angle of the upper arc of 11.4°. Based on the optimal seed disturbance structure, the effect of the shaped hole structure parameters on the planting accuracy was investigated, and the optimal hole width and depth were determined to be 4 mm and 2 mm. CFD-DEM numerical simulations showed that the pressure gradient force on the seeds was greater than the drag force, and the pressure gradient force and drag force were positively correlated with the width of the shaped hole. When the rotational speed was 60 r/min and the vacuum pressure was 2.0 kPa, 2.4 kPa, and 2.8 kPa, the miss index of the vacuum seed meter with Wuyou 1179 as the test material was 3.52%, 2.5%, and 2.22%; the quality of feed index was 92.41%, 92.13%, and 87.13%; and the multiple index was 4.07%, 5.37%, and 10.65%. For Huanghuazhan and Taixiang 812 rice seeds, the planting accuracy of the vacuum seed meter with the double hole can meet the requirements for direct seeding of rice. This study provides a theoretical basis and design reference for rice precision planting technology.

An air-suction seed metering device has been widely used for precision planting in various crops, due to the minimal seed damage, high efficiency, simple structure and strong adaptability. Single-seed broadcasting has been one of the most important capabilities to improve the quality of hybrid rice planting, particularly with the direct seeding of hybrid rice and the seed production levels. However, the stable filling and high precision of single seed broadcasting are highly required to meet the large amount of sowing in the air-suction seed metering device in recent years. In this study, an improved air-suction single-seed metering device was proposed with rectangular suction holes and auxiliary seed filling. Taking the "Yoshida" hybrid rice as the research object, the gravity distribution of the seed was analyzed to optimize the structure parameters. It was found that the high adhesion of the seed depended mainly on the rectangular shape of the seed suction hole on the seed-sucking plate. According to the fluid-solid coupling theory in CFD-DEM, Ansys Fluent and Rocky Dem software were used to simulate the airflow part of the planter and the interaction between the planter and seeds. A CFD-DEM simulation model was then established to exchange data for the air-suction single-seed metering device. Five types of single-factor experiments were conducted with the seed suction holes in the same area. The drag force, pressure gradient force, and air-suction force were taken as the experimental indicators. The seed suction hole with the maximum air-suction force was optimized as the size of 0.8 mm × 2.25 mm. In this case of the seed suction hole, the auxiliary filling angle, working speed, and working pressure were selected as the experimental factors, with the single rate (S), multiple rate (M), and leakage rate (L) as the experimental indicators. The optimal ranges of auxiliary filling angle, working speed, and working pressure were determined to be 70°-90°, 30-60 r/min, and 400-800 Pa, respectively. Subsequently, the Box-Behnken experimental design was conducted to combine with the variance analysis, response surface method, and multi-objective optimization. The variance analysis indicated that the primary and secondary influencing factors on the single rate were the auxiliary filling angle, working pressure, and their interaction term. The primary and secondary influencing factors on the multiple rate were the auxiliary filling angle, working pressure, the interaction term between the working speed and working pressure, and the interaction term between the auxiliary filling angle and working pressure. The primary and secondary influencing factors on the leakage rate were the auxiliary filling angle, working pressure, and the interaction term between the auxiliary filling angle and working speed. The response surface analysis showed that the single rate had a strong correlation with the interaction term between the working pressure and auxiliary filling angle. The multiple rate had a strong correlation with the interaction terms between the working pressure and auxiliary filling angle, as well as between the working pressure and working speed. The leakage rate had a strong correlation with the interaction term between the auxiliary filling angle and working speed. The multi-objective optimization showed that the better performance of the seed metering device was achieved in a single rate of 86.91%, a multiple rate of 9.46%, and a leakage rate of 3.63%, when the auxiliary filling angle was 80.90°, the working speed was 42.65 r/min, and the working pressure was 621 Pa. The experimental verification showed high consistency with the optimized, with a single rate of 10.23%, a multiple rate of 9.46%, and a leakage rate of 3.41%. The research findings can provide better guidance to optimize the air-suction single seed metering device, in order to improve the overall operational accuracy for direct rice seeding machines.

The primary aim of this study was to classify the hazard level of brown planthopper (BPH) damage in rice. Three datasets, including spectral reflectance corresponding to the sensitive wavelengths from rice canopy spectral wavelengths, rice stem spectral wavelengths, and fusion information of rice canopy and stem spectral wavelengths were used for BPH hazard level classification by using different algorithms. Datasets and algorithms were optimized by the BPH hazard level classification effects (which was evaluated by indices of accuracy, precision, recall, F₁, and k-value). The optimized algorithm combination was used to build a hazard level classification model for spectral reflectance corresponding to the sensitive wavelength from the rice canopy spectral images. Results showed that: (1) The spectral reflectance corresponding to the sensitive wavelengths of fusion information dataset performed best in BPH hazard level classification, with the highest accuracy (99.08%), precision (99.31%), recall (98.83%), F₁ (0.99), and k-value (0.99). (2) The optimum algorithm combination was Savitzky-Golay (S-G) smoothing, principal component analysis (PCA) for sensitive wavelength selection, and broad-learning system (BLS) for modeling. (3) The spectral reflectance corresponding to the sensitive wavelengths dataset of rice canopy spectral images achieved accuracy (80.63%), precision (80.28%), recall (77.03%), F₁ (0.79), and k-value (0.74) in classifying BPH hazard level by using the optimum algorithm combination.