At present, picking Sichuan pepper is mainly undertaken by people, which is inefficient and presents the possibility of workers getting hurt. It is necessary to develop an intelligent robot for picking Sichuan peppers in which the key technology is accurate segmentation by means of mechanical vision. In this study, we first took images of Sichuan peppers (Hanyuan variety) in an orchard under various conditions of light intensity, cluster numbers, and image occlusion by other elements such as leaves. Under these various image conditions, we compared the ability of different technologies to segment the images, examining both traditional image segmentation methods (RGB color space, HSV color space, k-means clustering algorithm) and deep learning algorithms (U-Net convolutional network, Pyramid Scene Parsing Network, DeeplabV3+ convolutional network). After the images had been segmented, we compared the effectiveness of each algorithm at identifying Sichuan peppers in the various types of image, using the Intersection Over Union(IOU) and Mean Pixel Accuracy(MPA) indexes to measure success. The results showed that the U-Net algorithm was the most effective in the case of single front-lit clusters light without occlusion, with an IOU of 87.23% and an MPA of 95.95%. In multiple front-lit clusters without occlusion, its IOU was 76.52% and its MPA was 94.33%. Based on these results, we propose applicable segmentation methods for an intelligent Sichuan pepper-picking robot which can identify the fruit in images from various growing environments. The research showed good accuracy for the recognition and segmentation of Sichuan peppers, which suggests that this method can provide technical support for the visual recognition of a pepper-picking robot in the field.

The potato industry is crucial to the development of the agricultural economy, and mechanized seeding is an effective aid to its modernization. Due to the metering devices having different sizes and structures, and even control, operation of sudden instability and other characteristics, and the complexity and variability of the farmland environment and other reasons, the mechanical sowing process may be affected by internal and external random and unpredictable factors, thus causing seed potato leakage, reseeding, and other phenomena and resulting in a decline in the quality of potato sowing brought about by the cascade effect: the quality and yield decline, precision sowing has become the modern potato production in the problem of modern potato production needs to be solved. This paper reviews the potato planter around the seeding quality of single seeding, plant spacing, depth and other directions of device optimization and digital sensing technology innovation involved, which single seeding direction from a variety of metering devices and the use of other sowing methods of potato planter detection, replanting, metering and other parts of the entry, and the introduction of the other field crops crop related research to provide a more comprehensive perspective. The advantages and disadvantages of the related research were compared and the existing problems were analyzed, and the future development direction of potato precision sowing technology was prospected.

In order to address the problem of a high miss-seeding rate in mechanized potato planting work, a novel reseeding device is designed and analyzed. Based on dynamic and kinematic principles, the seed potato’s motion analysis model in the seed preparation process was constructed. The analysis results indicate that the seed preparation performance is positively related to the seed preparation opening length l₁ and inclination angle of the seed-returning pipe θ. Then, the potato’s motion analysis model in the reseeding process was constructed. The analysis showed that the displacement of seeding potatoes in the horizontal direction d_s is influenced by the initial seeding potato’s speed $v_{0t}$, dropping height h_s, and the angle between the seeding pipe and the horizontal ground β_s. The horizontal moving distance x_r of the reseeding potatoes is influenced by the angle between the bottom of the reseeding pipe and horizontal ground β_s2, the distance from its centroid to the reseeding door d, and the dropping height of the potato h_r. The analysis results indicated that the reseeding potato can be effectively discharged into the furrow. Then, a prototype of a reseeding control system was constructed based on the STM32 microcontroller, electric pushers, and through-beam laser sensors. The simulation analysis was conducted to verify the theoretical analysis by using EDEM2020 software. The simulation results indicated that with the increase in the seeding chain speed, the seed preparation success rate initially increased slowly and then decreased gradually. The seed preparation performance can be increased by increasing the seed preparation opening length or decreasing the seed-returning pipe inclination angle. The impact on the successful seed preparation rate is ranked by significance as follows: seed preparation opening length > seed-returning pipe inclination angle > chain speed. Then, the prototype reseeding device and the corresponding seed metering device were manufactured and a series of bench tests and field tests were conducted. The bench test results showed an average successful seed preparation rate of 93.6%. The average qualified-seeding rate, miss-seeding rate, and multi-seeding rate in the field test were 89.6%, 2.46%, and 7.94%, respectively. This study can provide a theoretical reference for the design of potato reseeding devices.

In the potato mechanical planting industry, the high multi-seeding rate and miss-seeding rate are problems that exist in many potato precision seed metering devices. The main potato seeds in China are cut potatoes with different shapes and sizes. However, there is a lack of research on precision seeding technology for cut potatoes, and the adaptability of many existing potato seeding devices on cut potato is poor. The mechanized precision seeding of potato can effectively reduce labor consumption, improve the seeding effect (decrease multi-seeding rate and miss-seeding rate), improve the improve production of potato per acre and improve the quality commodity potatoes. In response to the above issues, a precision seed metering device with novel scoops, which can adapt to various sizes and shapes of cut potatoes, was developed. In this study, the different seed collecting scenarios (SCSs) were constructed. Through the statics and kinematic analysis, the excess seeds removing (ESR) process was divided in to three areas. The kinematic model of seed potato was established to study the influence of different SCSs and sprocket rotational speeds on the ESR performance, and preliminary determined the appropriate sprocket rotational speed range for ESR process. Then, the coupled simulation results of EDEM and RecurDyn revealed that different sprocket speeds and SCSs had a significant influence on the ESR performance. Finally, the bench tests and field tests were conducted to verify the actual performance of the precision seed metering device. The results showed that, with the increase of the sprocket rotational speed, the ESR performance of the device improved, the multi-seeding rate significantly decreased, but the miss-seeding rate increased. High sprocket rotational speed will remove more seed potatoes and cause high miss-seeding rate. The bench tests showed the appropriate sprocket rotational speed for medium and large potato was 35 r/ min. The field tests obtained the best qualified-seeding rate of 91.54%, the miss-seeding rate of 3.08% and the multi-seeding rate of 5.38%. This study can provide theoretical reference for the design of potato precision seed metering device.

The problem of soil and Chuanxiong tuber congestion on vibrating screens usually exists during the Chuanxiong mechanized harvesting process. To address this problem, the conveyance performance of a crankshaft rocker vibrating screen was studied. By establishing and solving the dynamics and kinematics equations for the crankshaft rocker vibrating mechanism and Chuanxiong soil residue, the acceleration of the vibrating screen and Chuanxiong-soil residue was studied. The sliding speed, motion process, and conveying distance of the Chuanxiong soil residue were also analyzed. The theoretical analysis results indicated that the acceleration of the vibrating screen depends on the rod lengths of the vibrating mechanism and the crank rotational speed and position. The displacement of the Chuanxiong-soil residue along the positive sliding direction in a cycle was more significant than that of the negative sliding direction. The appropriate advancement speed of the harvester was also obtained. The RecurDyn and EDEM coupling simulation was conducted. The simulation results verified the theoretical analysis. In the simulation, the Chuanxiong-soil residue was effectively conveyed. The field tests were conducted to verify the theoretical analysis. The harvester was tested in the field with crank rotational speeds of 0 r/min, 120 r/min, and 240 r/min, and advancement speeds of 0.5 m/s, 1 m/s, 1.5 m/s, and 2 m/s. The results showed that there was no congestion in the screen during the working process when the rotational speed of the crank was 240 r/min, and the advancement speed of the harvester was no faster than 1.5 m/s. When the crank rotational speed was 240 r/min, and the advancement speeds were 0.5 m/s, 1 m/s, and 1.5 m/s, the weights of Chuanxiong and soil on the screen after the test were 71.5 kg, 84.7 kg, and 105.7 kg, respectively. The field tests verified the conveyance performance of the vibrating screen. This study can provide a theoretical reference for designing the crankshaft rocker vibrating mechanism for the rhizome harvesting machine.

Multimode fibers with core diameters of 50 μm and 62.5 μm are the core media for short-distance, low-cost, and high-bandwidth optical transmission scenarios. Currently, the detection of their end-face defects is still mainly based on manual microscopic inspection. Most of the existing machine vision detection schemes are aimed at polarization-maintaining fibers (POL), which are easily interfered with by impurities and have insufficient accuracy and efficiency. This study introduces the information entropy in information theory as a constraint for feature selection, proposes the WGMOS digital image detection method, and optimizes the entire process of image acquisition, correction, filtering, adaptive segmentation, and feature extraction. By minimizing the information entropy of background noise and maximizing the information content of defect features, interference is suppressed. Experiments show that compared with the POL detection method, this scheme can exclude more impurities, with the image equalization value increased by ≥38.20% and the signal-to-noise ratio increased by ≥6.0%. It can achieve efficient and accurate detection of multimode fiber end-face defects.