Design of an Air-Assisted Mechanical Seed-Metering Device for Millet (Setaria Italica) Based on Experiments and Simulation Analysis

In this study, an air-assisted mechanical seed-metering device for millet (Setariaitalica) was developed. The discrete element method (DEM) and response surface method (RSM) were used to research the influences of the side length, depth, and oblique angle of the shaped hole on the seeding performance (quality, multiples, and miss indices) of the seed-metering device, and the parameters of the shaped hole were optimized. Furthermore, after determining the size of the shaped hole, the influence of negative pressure on the quality index was studied under the condition of the higher rotational speed of the seed-sowing wheel. At the rotational speed of 20 r/min, the optimal values of the side length, depth, and oblique angle of the shaped hole were found to be 3.55 mm, 2.1 mm, and 109°, which resulted in a quality index of 94%. The optimal parameters were consistent with the simulated values and bench test values, with a relative deviation of 5.05%. Moreover, under the condition of a rotational speed of 40 r/min, the application of appropriate negative pressure to the seeds was found to promote seed entry into the shaped hole, thus significantly reducing the miss index and increasing the quality index. At the negative pressure of −90 Pa, the quality index was found to exceed 90%. These results provide a theoretical basis for future studies on a seed-metering device for millet (Setaria italica)

Optimal Configuration Research of Plant Landscapes under Combined Horizontal and Vertical Curves on Mountainous Roads

The combination of horizontal curves and gradients can lead to visual perception errors by drivers, resulting in risky operations. While plant landscapes serve to guide road alignment and alleviate driver stress, irrational plant landscapes can obstruct the driver’s view, leading to traffic accidents. This study aims to explore the optimal configuration of plant landscapes on horizontal–vertical curve sections. The standard deviation of speed and lateral displacement were selected as two important measures of vehicle stability, and four crucial factors of plant landscapes were identified: color, height, roadside distance, and plant spacing. Subsequently, Design Expert 10, UC-win/Road 16.0 software, and a driving simulator were employed for scene design, modeling, and driving data acquisition. The Box–Behnken Design response surface method was utilized to analyze the influence of plant landscape factors on vehicle stability and predict the optimal configuration of plant landscapes on horizontal–vertical curve sections. Finally, validation experiments were conducted. The results indicate that the height and spacing of plants significantly affect vehicle speed, while plant height and roadside distance significantly impact vehicle lateral displacement. Through validation experiments, it was confirmed that the optimal plant landscape configuration is green in color, with a height of 4 m, a roadside distance of 1 m, and a plant spacing of 10 m. Therefore, rational plant landscapes can enhance driving stability and are essential measures for improving traffic efficiency and safety

The dynamics of tea plantation encroachment into forests and effect on forest landscape pattern during 1991–2021 through time series Landsat images

Tea plantations encroachment into forests has occurred in the major tea planting area of Yunnan province, China in the past decades. However, the dynamics of tea plantation encroachment into forests and the effect on forest landscape pattern is not clear. In this study, we proposed a method to evaluate the dynamic effects of tea plantation encroachment on forest landscape pattern change by using time series Landsat 5/7/8 data from 1991 to 2021 on the Google Earth Engine (GEE) platform. First, a pixel- and phenology-based algorithm was applied to generate tea plantations encroachment into forests maps for seven historical periods. Second, three indices including the tea plantations encroachment index (TPEI), the growth area of tea plantations encroachment into forests (GATEF), and the growth index of tea plantations encroachment into forests (GITEF) were used to quantify the tea plantations encroachment into forests of seven historical periods. Third, the effects of forests landscape pattern resulting from tea plantations encroachment were evaluated in class metrics and landscape metrics respectively. Our results show a total of 13,721 ha of GATEF from the early 1990s to the early 2020s. The GITEF increased from the early 1990s to the early 2010s and decreased from the early 2010s to the early 2020s in our study area. And the TPEI indicates that the edge encroachment mode dominated in our study period. Correlation analysis indicates that tea plantations encroachment level had significant correlation coefficients with landscape pattern indices (such as CONTAG (r = −0.91), ED (r = 0.95), DIVISION (r = 0.85), and SHEI (r = 0.86)), which indicates that the level of tea plantations encroachment affects significantly the forest landscape pattern. This study provides a promising approach to quantifying the effect of forest landscape pattern results from tea plantations encroachment