Search

Autonomous navigation is an important guarantee for intelligent agricultural machinery to complete harvesting operations. Navigation line recognition is an important step in achieving autonomous navigation of intelligent agricultural machinery. Real-time and accurate detection of harvesting navigation lines can effectively accelerate the progress of operations and reduce crop loss rates. Visual sensors have the advantages of low cost and rich information acquisition, making them widely used in route detection. Frequent changes in lighting under cloudy weather make it difficult for a single feature to cope with wheat field environments. In this study, a wheat harvesting boundary detection method based on multi texture feature fusion was proposed. In the harvested area, the characteristics of low stubble and no top wheat ears result in differences in uniformity, density, and other aspects when harvesting under both light and backlight compared to the non-harvested area. At the same time, due to the exposed wheat stubble in the harvested area, it appears more regular on the image, and its gradient direction is more consistent than that in the non-harvested area. Therefore, a two-dimensional feature vector composed of image entropy and directional gradient was constructed to classify the harvested and unharvested areas of the wheat field, and then the harvesting boundary was extracted. Due to the susceptibility of image entropy features to perspective phenomena, this paper compared the entropy features of different regions in the image when fixing the camera installation angle and height, and ultimately selected the middle region of the image as the region of interest. After analyzing the characteristics of image entropy feature extraction, a histogram statistical method based on sliding windows was proposed to accelerate the speed of image entropy feature extraction. By further dividing the window to be calculated into several sub windows, sliding and combining these sub windows significantly reduced the computation. The entropy feature extraction in this paper took 0.53 seconds, which is 49.52% faster than the traditional method of directly extracting entropy from the entire window. After extracting twodimensional features, based on the distribution characteristics of the feature histogram and combined with the maximum entropy threshold segmentation algorithm, the wheat field image was preliminarily classified. For entropy features, low noise points affected the threshold segmentation effect. By comparing the impact of discarding different proportions of low entropy points on the segmentation threshold, this paper discarded 10% of low entropy points, enhancing the threshold segmentation effect. The method of removing small connected regions was used to eliminate the misclassified regions in the initial classification binary image. Then, the Canny operator was used to extract edge contour points distributed near the harvesting boundary. Due to the consistent direction between the harvesting boundary and the agricultural machinery's forward direction, the Ransac algorithm was used to restrict the fitting line in the region, obtaining the accurate harvesting boundary. In order to verify the feasibility of the method proposed in this article, wheat field images under different lighting conditions were collected, including 2 200 weak light images, 758 local strong light images, and 1 134 strong light images. After selecting the region of interest, the size of the image to be processed was 240 pixels×1 280 pixels. The algorithm in this paper took an average of 0.88 s to process each image on laptops. The detection rates under weak light, local strong light, and strong light were 90.41%, 88.26%, and 89.68%, respectively, with an average of 89.45%. Compared with the traditional method of using Adaboost algorithm for machine learning, the detection speed of this algorithm was improved by 73.89%, and the detection rate was increased by 46.19 percentage points, 46.00 percentage points, and 49.64 percentage points under weak light, local strong light, and strong light, respectively. Compared with traditional algorithms, the method proposed in this paper significantly improved real-time performance and detection rate, which can provide reference for the detection of field agricultural machinery navigation lines. [ABSTRACT FROM AUTHOR]

Fruit picking has been one of the most important operations in modern agriculture. Manual picking cannot fully meet large-scale apple production in recent years, due to the labor-intensive and time-consuming task. Alternatively, robot picking can be expected to replace manual work. However, the conventional semi-automatic picking machine can seriously vibrate the branches and damage the fresh apples during batch harvesting in the existing orchard. It is a high demand to detect apples under complex environments, and then pick them without damaging the fruit or trees. The picking robots are also required a compatible auxiliary platform during operations in an orchard. The performance of picking robots can be assessed using the picking speed, picking success, and fruit damage rates. These parameters depend on three key technologies: target recognition, localization, and fruit separation. In this paper, an overview was provided of the history and current status of commercial apple-picking robots. Specifically, the performance and robustness were highlighted, in terms of the picking efficiency, structural composition, the type of orchard, and adaptability to the external environment. The main technical features were then summarized from the application of apple-picking robots. Since the apple picking was operated in an unstructured orchard environment, the most serious challenge remained in the application of target recognition, localization, and fruit separation techniques. Therefore, the recognition techniques were reviewed for the apples in the complex natural environments with changing light, branch and leaf shading, overlapping fruit, night-time environments, and same-colored apples. Deep learning-based apple recognition algorithms were the far-reaching prospects in complex environments, particularly in multiple scenarios. The accuracy and speed of apple recognition were improved using deep learning recognition algorithms in the field of apple picking. The second most challenge was the application of the apple localization for the fruit occlusion and overlap, while the fruit displacement by wind during the imaging process. Therefore, four aspects were introduced in the apple localization, including 2D information acquisition, depth information acquisition, apple pose acquisition and oscillating fruit localization. Point cloud processing algorithms were highlighted to achieve the precise localization of occluded apples. In addition, the applications of end-effectors were reviewed in the apple-picking robots with high efficiency and non-destructive picking. Three types of the end-effector structure (such as hand-jaw, vacuum, and shear) were summarized under fruit separation. It was found that the hand-jaw was the most commonly-used type of end-effector. Current research on the end-effectors was focused on the flexible materials for the finger surfaces, under-driven, flexible structures or control systems, such as the soft hands and perception-based servo control. Therefore, it is necessary to improve the picking speed and success rate with the low fruit damage and cost saving in the apple picking robot, in order to accelerate the process of apple picking automation. Future development was also proposed for the apple-picking robot in the urgent commercial need of the pioneering innovation in the combination of agricultural machinery and agronomy. Some optimization can be expected to be performed on the recognition algorithm, multi-sensor fusion, multi-arm cooperation, human-machine collaboration, extending device versatility, and integrating 5G and IoT technology. This finding can provide a strong reference for the current status, future development trends, and equipment innovation of apple-picking robots, together with the key technologies. [ABSTRACT FROM AUTHOR]

The information of grain yield distribution is one of the main information in digital agriculture, and its effective acquisition is of great significance for the process of grain harvesting. At present, domestic and foreign researchers had designed different types of grain yield monitoring systems with a variety of means. But due to the impact of measurement accuracy, model matching and other factors, these systems had not been effectively applied to the actual production in China. This study designed an online monitoring system based on the principle of grain flow pressure for monitoring grain yield. In this paper, the mathematical model of grain yield based on grain flow pressure was established, and the whole structure of the pressure-type grain yield monitoring system was determined. The monitoring system was mainly composed of grain flow monitoring device, positioning device, cutting table height control switch, core processor and human-computer interaction device, etc. Because the system proposed had the functions of sensor signal acquisition and processing, data display and storage, it realized real-time measurement, display and storage of grain yield in the process of grain harvesting. Based on the monitoring mathematical model between grain yield and grain flow pressure, a testbed was set up to simulate the actual operation of the end conveying auger of the grain collecting lifter of the grain combine harvests. The testbed was mainly composed of grain flow monitoring device, auger, feeding box, insert plate, three phase alternating current motor, reducer, stage and other parts. The Box-Behnken experimental design method was used to optimize the structural parameters of the grain flow monitoring device with the testbed. In this paper, the influences of the number of the sensors, the installation position of the sensors and the horizontal inclination angle of the monitoring device on the error of the grain yield monitoring system were studied. The optimal parameter combination was determined as follows: the number of the sensors was 5, the sensor installation position was 0.24 cm, and the horizontal inclination angle of the monitoring device was 5°. A verification test was carried out under the optimal working parameters. The experimental results showed that the measurement error of the grain yield monitoring system was 3.27%, which met the precision requirement of grain yield monitoring. In addition, the grain yield monitoring system was applied to field harvesting to verify its actual monitoring effect of yield. The field experimental results showed that the error of the field yield measurement was 5.28%. The grain yield monitoring data of the field experiment were filtered and interpolated, and the yield distribution map was finally generated. The yield distribution map could provide decision basis for subsequent variable sowing and fertilizer management. It can be concluded that the grain yield monitoring system had the characteristics of good versatility, convenient installation and high monitoring accuracy. This study could meet the urgent needs of grain yield monitoring in actual production, and had important practical significance for realizing intelligent and digital agriculture. [ABSTRACT FROM AUTHOR]

The existing oil sunflower threshing device cannot meet the requirements of oil sunflower threshing under different conditions. Aiming at the problems of the low oil sunflower threshing rate and the high breaking rate during the threshing process, a threshing device of oil sunflower with variable clearance based on multi-bar mechanism is designed in this paper. The structure and the working principle of the oil-sunflower threshing device with variable clearance were introduced, and the mechanisms of kinematics of the clearance adjustment mechanism and angle adjustment mechanism of the structure of variable clearance concave screen were analyzed, the motion trajectory analysis and solution were performed to determine the structural parameters, the variable clearance range of the variable clearance concave sieve was 20-60 mm. A test bench of the oil-sunflower threshing device with variable clearance was developed. The threshing test was completed at the Key Laboratory of Innovation Design Laboratory of Xinjiang Agricultural Engineering Equipment. The test object was oil sunflower No. 31 with the disk diameter of 180-220 mm and the disk thickness of 25-40 mm, the weight of single sunflower disk was 300-380 g, the moisture content of the sunflower disk was 29.59%. The test was performed according to the GB/T5982-2017 thresher test method and the DB37/T2878.2-2016 technical requirements. The orthogonal experiment of three factors and three levels was carried out, threshing rate and breaking rate were taken as the indexes and the cylinder speed，the threshing clearance as well as feed rate were the factors. The test results showed that during the threshing process, the factors that affect the oil sunflower threshing rate and breaking rate are threshing clearance, drum speed and feed rate. The optimal combination of operating parameters was that the threshing clearance 35 mm, the drum speed 280 r/min and the feed rate 1.8 kg/s. Through the analysis of variance, it was concluded that the threshing clearance had a very significant effect on the oil sunflower threshing rate and breaking rate, the drum speed was significant, and the feed amount was not significant. Multiple repeated tests were performed under a better combination of operating parameters. The test results showed that the average threshing rate of oil sunflower was 99.01%, and the breaking rate was 2.28%, which met the national standards that the threshing rate greater than 98 % and the breaking rate less than 5%. The better operating parameters of this study are only applicable to the material conditions tested in this paper, but the oil sunflower harvesting operations are complicated, and the factors such as oil sunflower varieties, moisture content, and output are also different. Adjusting the diameter of the threshing concave plate sieve, changing the threshing clearance and other working parameters is to meet the requirements of oil sunflower threshing under different conditions. The research results can provide reference for the design of subsequent oil sunflower threshing device. [ABSTRACT FROM AUTHOR]

Moisture content is one of the important indicators in grain harvesting, trading, storage and processing. High moisture content will lead to a series of problems of grain such as mildew, deterioration, shortened storage time, lower transaction price and higher processing cost. With the development of precision agriculture, accurate detection of grain moisture content can also accurately assess the growing situation of crops, and then provide guidance for the next season’s crop planting. Compared with the drying method, the capacitance method and the electric resistance method, the microwave method is easy to realize the non-destructive measurement of the grain moisture content, which is an important direction of moisture content detection. In the field of on-line detection of moisture content of rice and wheat in combine harvesters, foreign related research started earlier, and enterprises have commercialized, but this technology is still in the research stage in China. Aiming at the problem that the rice-wheat combine harvester is difficult to accurately measure the moisture content of wheat and rice during harvesting operation, this paper studied a non-destructive on-line detection method of grain moisture content based on microwave reflection method, established the grain moisture content measurement model, designed a non-destructive on-line detection device for grain moisture content used on rice-wheat combine harvesters. The device used a 450 MHz microwave measurement module to measure the moisture content of rice and wheat non-destructively. The voltage conversion circuit was designed to convert microwave parameters into voltage signals, and the average filtering algorithm was used for signal filtering to reduce the impact of interference factors. Finally, the moisture content detection model of rice and wheat, which was established by the calibration experiment, was used to calculate the moisture content. The calculation result was displayed on the display in real time via CAN bus communication. Due to the insufficient installation space in rice-wheat combine harvester, the structure of the detecting device was designed and optimized, and the circuit portion and the sampling mechanism were integrated in a compact structure. Based on the above theoretical research, technology development and structural design, this paper carried out laboratory static experiments and field harvesting experiments. The laboratory static experiment used rice and wheat to illustrate the establishment process of the grain moisture content detection model: 30 groups of rice and 30 groups of wheat samples were prepared, moisture contents and voltages calibration experiment was completed, the rice and wheat moisture content detection models was established and the experimental results were analyzed. The field harvesting experiment was verified the practicability and reliability of the grain moisture content detecting device with rice as the test object. The experiment results show that the performance standard deviations of the laboratory static experiment and the field harvest experiment are 0.458 3 and 1.078 0, respectively, and the relative error are around 2.5% and 5%, respectively. Moisture content measuring range of the detection device for rice and wheat is 14%-34%, which meets the project requirements. [ABSTRACT FROM AUTHOR]

High-speed photography which can take a lot of pictures catching the movement state of the fruit in rapid motionin during a very short time has become the mainstream method to study fruit motion. The mean limitation of the existing researchs is that tracking movement of one feature point on fruit surface can not reflect the exact movement of the fruit,especially swing and rotation. In this paper, We divided the spatial motion of the fruit into the translation, swing and rotation of the instantaneous attitude corresponding fruit spatial motion and proposed a method to calculate 3 kinds of spatial motion of fruit by 3 feature points on fruit surface. First, we constructed a coordinate system called characteristic point coordinates with 2 space vectors from 3 surface feature points. Second, we assumed that the fruit was a rotating body. Then, the coordinate system which we called the conjoined base coordinate system was established with the origin of the joint of the fruit stalk ,in which the Z-axis coincides with the rotation axis of the fruit. The movement of the fruit was represented by the movement of the conjoined base coordinate origin. The swing of the fruit was represented by the swing of the Z-axis of the conjoined base coordinate system. The rotation of the fruit was represented by the rotating around Z-axis of the Y-axis or X-axis in the conjoined base coordinate system. The third, we got the transformation relationship between 2 coordinate systems through the space vector relationship. Final, we used the spatial coordinates of the feature points and coordinate relationship gotten above to calculate the position and attitude of conjoined base coordinate frame by frame. Conjoined base coordinate of 2 adjacent time could calculate the instantaneous dynamic displacement, speed and acceleration of the fruit, as well as the motion parameters such as instantaneous angle, angular speed and angular acceleration for fruit swing and rotation.The ADAMS computing software was used to simulate the motion by setting a specific complex motion relationship of translation, swing and rotation. The calculation formula constructed in this paper was used for calculation and the calculation results were compared with the theoretical simulation values to determine the calculation accuracy of the calculation formula. The maximum one-way average absolute error of displacement was only 5.9×10-8 mm, and the absolute errors of displacement, speed and acceleration were enlarged gradually by the order of magnitude of 103. The relative errors of displacement and speed were identical, while the relative error of acceleration was larger than that of displacement and speed. The average absolute error and average relative error of maximum acceleration were 6.5×10-2 mm/s2 and 4.13×10-2%, respectively. The maximum average absolute errors of swing and rotation were 5.43×10-2 and 9.51×10-2 °/s2, respectively. The results show that the method constructed in this paper is feasible to solve the instantaneous motion attitude of the fruit. [ABSTRACT FROM AUTHOR]

A method for inverse kinematics analysis based on screw theory was presented in this paper, which can directly map the position and orientation of the working object to the joint variables of the manipulator with its application to a full inverse kinematics analysis of forest-fruit harvesting manipulator characterized by a hybrid kinematic structure, 2P4R. The solution of inverse kinematics modeling derived by screw theory was commonly realized by Paden-Kahan sub-problem method, which decomposes a full kinematics problem into sub-problem with obviously geometrical meaning through choosing appropriate point, usually, intersection of adjacent joint, such as wrist joint, to reduce the number of the variable quantity, and then close-form solution can be easily obtained. However, in practice, it is hard to gain the position of those points through measure because of their absence before end-effector actually moving to the desired position. And few researchers mentioned this issue in the relevant literature. In order to discuss this problem, firstly, a geometrical method was proposed for this issue to obtain the position of the required point, wrist joint, according to the orientation of end-effector and its geometric properties and geometric relationships through using the vector algebra method. Furthermore, a mapping between driving and driven join was gained in order to simplify the solving process of the equation set at a later, according to the solution of the structural equation of the manipulator derived by the product-of-exponentials (POEs) formula and structural character of manipulator. Meanwhile, the closed-form solution for each driving joint variables was derived by employing the proposed method with Paden-Kahan sub-problem method. A mapping relationship between the plücker coordinates of the object and the location information of end-effector was derived through an algebraic method according to the principle of minimum displacement and its operating mode in which the gripper of end-effector should reach the position of the trunk with two labels detected by the robot vision system and be perpendicular to the orientation of the trunk. In addition, the problem of multiple solutions in the inverse kinematics analysis for the harvesting manipulator was solved according to the range of joint variables. Finally, the real-world experiment was performed under laboratory environment. In order to vertify the correctness and obtain the accuracy of the method proposed in this paper. A wooden stick with two markers was placed in the kinematics test platform as the object, which consisted of a laser tracker and a harvesting manipulator. Then, the values of each joint variable could be calculated via the proposed method according to the plücker coordinate data of the markers measured in the object. The results showed that the forest-fruit harvesting manipulator was driven by the solution of inverse kinematics to the position on the stick that its end-effect reached and normal to the stick, which meant this method could meet the requirements of the operating mode. Then ten sets of joint variable values were randomly generated where the positions were measured and the manipulator was sequentially driven by that. The joint variable values were calculated according to the positions through the method proposed in this paper. At last, the calculated results were re-inputted into the controller to drive the manipulator to the new positions. The two measure results on different positions driven by joint variable values generated and calculated were used to obtain the error. The results showed that the maximum position error of end-effector was 6.597 mm, far less than the open size of its gripper, 200 mm, and no more than 3.30%, with the maximum orientation error of 0.975°. The method in this paper was not limited by the specific structure, therefore it is versatile. [ABSTRACT FROM AUTHOR]

Grain loss rate is one of the most important performance index of corn head in mechanized harvesting. Seed harvesting is the main development direction of mechanized corn harvesting. The characters of seed harvesting corn variaty increased the urgency to reduce grain loss on corn head. The paper was proposed to solve the problem of grain loss on corn head. Theoretical analysis was conducted to the snapping process. Corn ear was subjected to pull force by the snapping rolls and the pull force transferred by corn stalk. Corn kernels were divided into 2 types due to their force condition. A kernel at the bottom end of corn ear was subjected to reaction forces by stripper plates, corn cob and the adjacent kernels and shear force by the pedicel. Kernels out of contact with the stripper plates were subjected to reaction forces by the adjacent kernels, pull force and shear force by corn cob. As the impact force was related to the impact time according to the theorem of impulse, the paper analyzed collision model between corn ear and stripper plates in the snapping process. A mathematical model was obtained about the impact time and intrinsic parameters of the system. The impact time was dependent on system mass, stiffness coefficient and damping coefficient, which lays on the mechanical structure and materials of collision objects. So, the impact force would decrease as the impact time could be prolonged by reducing the stiffness coefficient and raising the damping coefficient. The quantity of shed kernels could be reduced consequently. The paper proposed a corn head with wheel type rigid-flexible coupling snapping device to reduce loss. The corn head consisted of the frame, gear-box, snapping rolls, gathering chain, wheel type rigid-flexible coupling snapping device, and chain wheels. The wheel type rigid-flexible coupling snapping device consisted of snapping wheel axle, spring seat axle, supporting axle, buffer spring, and snapping wheel frame. Force analysis was conducted on the snapping wheel. According to the force conditions and dimension boundary condition, the structure diameters of snapping wheel, snapping wheel frame, and buffer spring were confirmed. In order to obtain the optimal parameters with the minimum loss rate of wheel type rigid-flexible coupling snapping device, the optimization experiments were conducted of the factors at 3 different levels. In the optimization experiments, the snapping wheel radius was designed at 10, 15 and 20 mm respectively, the flexible body thickness was at 2, 4 and 6 mm respectively, the snapping rolls rotating speed at 700, 800 and 900 r/min respectively. The Response Surface Analysis method was used to design the experiments. The software Design-Expert 8.0.6.1 was used to analyze the data. Regression equation was induced according to the experiment and analysis above. The optimal combination of wheel type coupling snapping device was as follows: The snapping rolls rotating speed was 700 r/min, the snapping wheel radius was 15 mm, the flexible body thickness was 4 mm. Verification contrast test was conducted between corn head with wheel type rigid-flexible coupling snapping device and the one with snapping rolls and stripper plates on corns at different moisture contents. As the kernels moisture contents were 21.8%, 16.7% and 13.4%, the grain loss rate decreased 53.4%, 48.6% and 47.0% respectively. This study provides not only theoretical basis but also design reference for the improvement of corn harvester design. [ABSTRACT FROM AUTHOR]

Castor is one of the top ten oil crops in the world, which has a extremely high economic value. For a long time, the harvesting of castor bean has relied on manual operations, so the development of the castor industry have been greatly restricted by the high labor intensity and low efficiency. At present, there are few studies on harvesting machinery of castor, and the mechanization of castor harvesting is still in the initial stage. The existing castor harvesting equipments are not suitable for the growth features of castor, which has the problems of high loss rate and high damage rate. In order to solve these problems, a brush-roller harvesting method was proposed in this paper. The harvesting principle of brush-roller castor harvester is that the castor capsules are separated from the plant by the brushing force caused from the brush wire. According to the physical characteristics and planting mode of castor, the picking mechanism of brush-roller castor harvester was designed. Firstly, the structure of the picking mechanism was introduced, the picking mechanism is mainly composed of crop divider, brush roller, screw conveyor, transfer case, et. Then, the kinematic and mechanical analysis of the working process of the mechanism was carried out, so as to determine the structural parameters and working parameters of each part of the picking mechanism. In order to improve the harvesting quality of castor, we conducted a field experiment in October 2020 in Hohhot, Inner Mongolia. In the field experiment, Box-benhnken response surface design theory was used on the basis of single fator experiment to optimize the working parameters of the picking mechanism. The picking rate, the breakage rate and the impurity rate were used as the evaluation indexes of working quality. And the moving speed, the brush roller speed and the length of brush wire were taken as three factors influencing the working quality. The quadratic polynomial response surface regression model was established, and the influence of various factors on the response value was analyzed. From the regression model and variance analysis of regression equation, it could be seen that: lower moving speed, moderate brush roller speed, and shorter brush wire led to higher picking rate; Lower moving speed, lower brush roller speed, and longer brush wire led to lower breakage rate; Higher moving speed, lower brush roller speed, and longer brush wire led to lower impurity rate. The experiment results also showed that the significant effects of moving speed, length of brush wire and brush roller speed on increasing the picking rate were in a decreasing order. The significant effects of brush roller speed, length of brush wire and moving speed on reducing the breakage rate and the impurity rate were in a decreasing order. At the same time, the factors were multi-objective optimized comprehensively, and the optimization results were verified by experiments. The results showed that the optimum parameters were: 0.72 m/s for the moving speed, 372 r/min for the brush roller speed and 57 mm for the length of brush wire. Under these conditions, the picking rate was 91.36%, the breakage rate was 0.18%, and the impurity rate was 11.67%. The measured values of each index were in good agreement with the theoretical optimization values, which meant that the model established was reliable and could be used for optimization. The results can provide a reference for further improving the structure design and working parameters optimization of the brush-roller castor harvester. [ABSTRACT FROM AUTHOR]

As a main grain production equipment, the combine wheat harvester plays an important role in grain production, and its technological development level is an important indicator of the degree of agricultural modernization. However, during the harvesting process, the working parts of the harvester interact with the crop to be harvested, so that the dust originally attached to the surface of the crop is disturbed and separated from the surface of the organism, forming floating and flying dust, some of which are scattered around the harvester, seriously affecting The driver’s body is healthy; some infected plants carry diseased dust, which is more harmful to the human body; more dust is dispersed in the air with the wind, causing a wider range of air pollution and increasing the amount of inhalable particles in the air. This has become one of the sources of air pollution during the crop harvest season. In order to understand the dust generation status and the characteristics of the dust composition, this paper first conducts the dust concentration and distribution test on the operation site of the combine wheat harvester .The result is as the header and tail of harvester are the main areas where dust is generated, Excessive dust mass concentration will harm the health of workers .The characteristics of the dust sample was tested results as follows: the proportions of dust with a particle size of 10μm and 100μm or less are 45% and 92%, the dust is mostly composed of minerals, grease and carbohydrates. The dust measurement test revealed for the first time the dust generation and dust composition characteristics of combine wheat harvester operations in the rice-wheat (oil) rotation area in southern my country. On this basis, a dust suppression system installed on the combine wheat harvester was designed. The system adopts the working principle of negative pressure dust suction and filter cartridge dust collection. The system utilizes the power of the existing combine wheat harvester and can change the working parameters of the fan at any time to meet a variety of field working conditions. Conduct field tests on the dust suppression system. Through theoretical analysis to determine the main factors that affect the efficiency of the dust suppression system. Taking the harvester header dust suppression efficiency and harvester tail dust suppression efficiency as the test indicators, and the harvester speed, fan speed and environment humidity as the test factors. Using Box-Behnken central combination test method, the three-factor and three-level test are carried out. A mathematical regression model of various factors and test indicators was established. Through variance analysis and response surface analysis, the influence of harvester speed, fan speed and environment humidity on the test indicators is obtained. Use Design-Export8.0.6.1 data analysis software to fitting and optimization analysis of the test results, the optimal parameter combination is obtained as follows: harvester speed 3.73 km/h, fan speed 3 507 r/min, and ambient humidity 56%. On this condition, the efficiency of the header dust suppression is 76.8%,the efficiency of the tail dust suppression is 79.6%. The optimal working parameters are tested and verified to verify the feasibility of optimizing the optimal parameter combination, the minimum fan speed of the dust suppression system to meet the dust suppression requirements under difficult working conditions is 3 332 r/min. This research can provide a basis for the design of the harvester dust suppression system. [ABSTRACT FROM AUTHOR]

Image Jacobian matrix is core portion of robot vision servo system. During estimating image Jacobian matrix with traditional methodology of KF (Kalman Filter) and UKF (Unscented Kalman Filter), the system noises of unknown statistical properties is determined according to priori knowledge, which is remained unchanged in system. However, this methodology of dealing system noises would make image Jacobian matrix’s estimation inaccuracy because of time-varying system noises. Based on traditional methodology of KF and UKF, in this paper, we structured propagator of system noises estimation with the difference value of system state predicted value and updated value, and raised Adoption Unscented Kalman Filter to estimate image Jacobian matrix. Two points on the tomato string’s stem, clamping point and picking point, were chosen as feature points in the image feature space. The center of mass of fruit stem was extracted as the holding point. According to the vertical growth characteristics of tomato clusters and the distance between the holding point on the end and the cutting point on the image, a point above the holding point was extracted as the cutting point. Image Jacobian matrix was used to transform information of pixel difference in image feature space to change in pose of end-effector in manipulator motion space. First, results of image feature space localization experiment showed that six image feature errors were smaller and the average image feature error of visual servo system based on AUKF was 4.978 pixes/mm in condition of unknown system noises. Compared with visual servo system based on KF and UKF, average image feature error reduced 54.44% and 24.78%, respectively. Second, three dimensional space positioning experiment between end-effector and target picking point showed that the final distance between end-effector and target picking point was 4.19 mm, reduced by 79.74% and 80.38% compared to methods of KF and UKF. Third, the response time of visual servo control system based on KF method, UKF method and AUKF method to estimate image Jacobian matrix was 2, 1.5 and 1.2 s, respectively. The picking experiment was carried out on the visual servo test platform of the seven-degree-of-freedom picking manipulator. The visual system based on each visual servo control method was tested for 30 times. For the visual servo system based on AUKF method estimation, the success rate of picking the static target was 90%, and the success rate of picking the dynamic target was 83%. Compared with KF methodology and UKF methodology, the success rate of static picking test was increased by 17 and 10 percentage points, respectively, and the success rate of dynamic picking test was increased by 16 and 10 percentage points, respectively. The results showed that the static picking time based on AUKF methodology was the 18 s, compared with the visual servo system based on KF methodology and UKF methodology, the time of static picking was reduced by 35.71% and 25%, respectively. The average dynamic picking time of visual servo system based on AUKF was 22 s and the test time of dynamic picking was reduced by 35.29% and 26.67%, respectively compared with the visual servo system based on KF methodology and UKF methodology. The image Jacobian matrix based on AUKF was suitable for the dynamic picking of tomato clusters, and the accuracy of visual servo control under dynamic condition was lower than that under static condition. Test results suggested that the proposed AUKF method with KF method and the UKF method compared to estimating by image Jacobin matrix, and AUKF method to estimate the image Jacobin matrix, reduced the process of picking robot visual servo control system noise interference, which made the picking robot visual servo control system of processing noise adapted to the change of the visual servo system, resulting in higher positioning precision for picking robot visual servo control system . [ABSTRACT FROM AUTHOR]

The stem tip of vegetable sweet potato is an excellent nutritious and healthy food, which is widely used in many countries. It’s estimated that the total value of Chinese vegetable sweet potato’s market is about tens of billions of yuan, which means it has a promising future. Due to the difficulties of the long harvest period, high harvest requirement, and low mechanized level, the high cost and low efficiency in harvest is prominent. As such, it decreases the motivation of the farmers deeply. Also, the market still has a strong need for the stem tip harvester urgently. In order to fill the blanket in the mechanized harvest on stem tips of vegetable sweet potatoes in China, and to solve the current problems, in this research, we designed a stem tip harvester for vegetable sweet potatoes in combination with agronomy, which was composed of the reeling, cutting, conveying and collecting devices. It could finish cutting, conveying and collecting the stem tips for vegetable sweet potatoes every single row in one operation. In this paper, we introduced the harvester’s working theory based on analyzing the whole machine’s mechanical structure. To improve the integrity rate of stem tip, to lower the missing rate in cutting, to lower the stubble height and to improve the harvester’s working quality, we did a test on the harvester’s working parameters, using Box-Benhnken's central combination test method based on the single factor test. Three-level quadratic regression orthogonal experimental design was done through the forward speed, the reel speed and the reciprocating cutter line speed. The model of response surface was established to research and analysis the machine’s working quality due to different factors. Finally, the optimization of machine operation parameters was realized. The results showed that the prominent order in the stem tips’integrity rates was the reel speed > the reciprocating cutter line speed > the forward speed. The prominent order in the stem tips’missing rate was the forward speed > the reciprocating cutter line speed > the reel speed. The prominent order in the stem tip’s stubble height was the reel speed > the forward speed > the reciprocating cutter line speed. In 2019, the test was done in three times to verify the model’s correction in Baiba test base, Nanjing Research Institute for Agricultural Mechanization. The field test results showed the optimal working parameters were the forward speed 0.38 m/s, the reel speed 26 r/min, and the reciprocating cutter line speed 0.60 m/s. The integrity rate of stem tips was 97.10%, the missing rate was 12.11%, and the stubble height was 62.09 mm. The error was in the range of 5% compared to the theoretical optimization. Compared with the single manual picking efficiency of 0.001 hm²/h, the operating efficiency of this machine can reach 0.1 hm²/h, The operation effect of the machine was obviously improved compared with that of manual operation, better to meet the requirements of the vegetable sweet potatoes’stem tips machinery harvesting. The test research supplies a strong support and theoretical basis to the mechanical development of the harvester for vegetable sweet potatoes’stem tips. [ABSTRACT FROM AUTHOR]

It is difficult to locate the apple in fog and haze environment for apple harvest robot. This paper proposed a new method to apply the principle of DCP (dark channel prior) to remove fog and haze on images which were collected from apple orchard. We adopted a new route to achieve the value of atmospheric light coefficient. Scan the hazed image with a 15×15 window, and get the smallest value of the 225 pixels from every window. All the smallest values constituted a dark channel image. The values of dark channel were stored in a matrix at the first step, and then the 1/1000 largest elements and their locations were calculated and stored in a new matrix which had the same shape with the dark channel matrix. Extract the matrix of red (R) channel of the hazed image at the next step. At the third step, the corresponding values in the matrix of R channel were obtained according to the position information in the new matrix. Finally, the average value of these values was calculated as the value of atmospheric light coefficient. According to the requirement of apple harvest robot, we took the haze-removal strength parameter of DCP algorithm as 1. In order to speed up the running of the algorithm, we calculated the transmission radio with guided filter. Image segmentation method used in the study had 3 stages: binaryzation, de-noising and dilation. Firstly, the grey image was obtained by calculating a special linear combination with red (R) channel, green (G) channel and blue (B) channel. This method emphasized the value of red channel in color images, which was conducive to separate the apple better at the next step. Secondly, binary image was obtained by Otsu method based on the grey image. Finally, after the process of de-noising and dilation, a better segmentation results could be obtained. We developed an experimental software with Microsoft Vision Studio 2010 and OpenCV (Open Source Computer Vision Library) to test the haze-removal effects in apple harvest robot vision system. The graphical user interface of the program was developed based on MFC (Microsoft Foundation Classes) library. The software had achieved the following functions: reading the image, calculating the dark channel value, calculating the value of atmospheric light coefficient based on the R channel, calculating the transmission radio, and so on. Based on this software we compared some haze-removal methods including MSR (multiscale retinex), AHE (adaptive histogram equalization) and DCP with different parameters. Hardware platform of the experiment was X230, which is a notebook computer produced by Lenovo Inc. We took Nikon D7100 camera as the image acquisition equipment and fixed it with tripod when it worked. Experimental images were collected at the apple base in Changping District of Beijing. Image acquisition dates were some days with heavy fog and haze in November 2015. Twelve images were selected as the experimental materials. After the analysis of the experimental data, this paper got the following results: 1) The average contrast value of the images was 64.04 with our method; the AHE method was faster, but the contrast value was 35.46 with the AHE; the histogram obtained by our method had the characteristics of Gaussian distribution, which showed that our method could get better image quality; 2) Testing the 640×480 images pixels, our method required 36.46 ms computing time, the MSR method required 126.43 ms, and the AHE required 28.58 ms. The time performance of our method was not as good as the AHE, but it was better than the MSR; 3) The average location accuracy was 94.8% with our method, which was higher than other methods. The experiments show that our method can get better balance between efficiency and performance. It is a feasible method for the actual apple harvest operation. [ABSTRACT FROM AUTHOR]

In this paper, the combination of finite element modeling and experiment was used to study the effects of different vibration parameters such as vibration time (A), amplitude (B) of the vibration excitation point on apricot tree vibration and vibration frequency (C), and optimize the performance of forest fruit vibration harvesting prototype. The effects of different vibration parameters on the vibration detection points of apricot trees were analyzed by vibration response test. The response analysis of apricot tree free modal vibration using ANSYS Workbench software showed that apricot trees had typical free modal responses at 15, 26, 30 and 40 orders, the corresponding frequencies were 5.5, 10.5, 15.1, and 29.3 Hz, respectively; and the maximum displacement deformation of fruit trees was 286.5, 261.9, 267.2, and 273.5 mm, respectively. The typical free modal cloud image analysis showed that the typical free modalities of the 15th and 26th orders were higher in the terminal end responsiveness of the apricot branches. The 30th order fruit tree had a high overall response consistency, and the apricot tree had the largest deformation response at the end; at the 40th order of 29.3 Hz, some branches of the fruit trees were severely deformed, and the overall structure of the tree was easily destroyed. The optimal response frequency of apricot tree vibration harvesting ranged from 0 to 20 Hz. The harmonic response analysis showed that in the optimal frequency range, the acceleration of the same position increased with the increase of the excitation amplitude at the same frequency, but the overall variation of the vibration curve was consistent with the trend; When the amplitude of the vibration excitation point of the apricot tree was 5, 10 and 15 mm, at the same frequency, as the excitation amplitude increased, the acceleration at the same position increased, but the overall variation of the vibration curve was consistent with the trend. The three-factor and three-level vibration response tests were conducted to study the effects of vibration time, vibration frequency and excitation point amplitude on the acceleration of three different detection points. The multivariate regression analysis of variance showed that the accelerations P1 and P2 of detection points 1 and 2 were less than 0.000 1, the overall model was highly significant (P<0.01), and the model regression terms B and C were significant. The acceleration P3 of the detection point 3 was 0.000 1, and the overall model was highly significant (P<0.01), except that the acceleration P3 value of the detection point 3 of the model regression terms AB, AC and A2 was not significant (P>0.05), and other regression terms were significant (P<0.05). The factors which affected the acceleration of the detection points 1 and 2 were the same as the amplitude of the excitation point, vibration frequency and vibration time. The order of the magnitude of the acceleration affecting the detection point 3 was the vibration time, the amplitude of the excitation point, and the vibration frequency. Through the response equations of the three detection points, the coefficient of determination R2 of the regression equations from the bottom to the top three detection points were 0.906 7, 0.879 3 and 0.973 3, respectively. Using the Design-Expert 10.0.3 software to optimize the detection point response equation, the optimal vibration recovery parameter combination was that the vibration time was 7.207 s, the vibration frequency was 15 Hz, and the amplitude of the excitation point was 10 mm. The verification test showed that the acceleration from the bottom to the top of each detection point was 10.4, 10.2 and 9.3 g, which was similar to the optimized value. These conclusions can provide design and theoretical basis for the design of mechanical parameters of apricot vibration harvesting. [ABSTRACT FROM AUTHOR]

Fruit and vegetable picking grippers are important technology to achieve rapid and labor-saving harvest. However, most of the existing fruit and vegetable picking grippers still use traditional rigid or underactuated grippers, which often cause fruits and vegetables damage by the heavy mass and lack of high-precision control, and have poor compliance in the operation process. In recent years, inspired by soft creature’s tentacles, soft robotic grippers have appeared and been used in robotics due to the emergence of soft robots. Soft robotic gripper, which is made of flexible material, is a new type of gripper for general purposes with grasping and holding capabilities enabled by a simple control scheme. Under the infinite degrees of freedom, the soft robotic gripper can change its shape and size corresponding to the load in a large range. These advantages overcome the defects of traditional fruit and vegetable picking robots, such as rigidity and poor adaptability. Moreover, soft robotic gripper is easy to manufacture and can be integrated with manual operation without any large-scale safe requirement. This paper gives a research on limitations of the traditional grippers and summarizes the characteristics of ideal picking grippers of fruit and vegetable. In addition, the concept of soft robotic grippers is introduced in detail, and the current development status about soft robotic grippers is described. The manuscript also summarizes the progress and superiority of soft robotic grippers in fruit and vegetable picking as well as strong adaptability to the environment. The characteristics of the soft robotic grippers driven by the common driving mode including pneumatic, cable, shape memory alloy and electroactive polymer mode have been analyzed in the process of fruit and vegetable grasping and picking. Compared with the rigid grippers, in addition to the simple control and mechanism, the soft robotic grippers have high-degree flexibility, adaptability and versatility. Based on the related work, the problems of modeling and control of fruit and vegetable picking devices have been discussed, and possible solutions of soft robotic grippers are also summarized by means of analysis and classification. We can choose the appropriate control methods according to the surface characteristics of picked fruits and vegetables. Finally, we conclude that multi-sensing, variable stiffness, multi-functional composite materials, as well as control strategies of fusion intelligence will be future development directions of fruit and vegetable picking grippers with the progress of micro-sensors and biomaterials. This research will provide theoretical and technical guidance for the development of fruit and vegetable picking grippers. It is expected that more fruit and vegetable picking operations could be carried out by soft robotic grippers, and the application will effectively reduce the damage rate of fruit and vegetable picking. As a new-generation operating device, the soft robotic grippers involve the development of materials, chemistry, machinery and other multidiscipline. Further studies are required to improve its design, controllability, manipulating methods, and so on. [ABSTRACT FROM AUTHOR]

Although China is a vegetable growing country, but the degree of mechanization of vegetable production is low, with China's urbanization and industrialization of the advance, arable land gradually less, so the vegetable cultivation plant more and more people pay attention. Facilities vegetable cultivation is an important way for vegetable cultivation. However, the level of mechanization of vegetable greenhouses is less than 25%, and the comprehensive mechanization level of vegetable production is about 20%, while that of leaf vegetables in China accounts for 30% to 40% of total production. Therefore, the development of efficient and stable facilities vegetable harvesting machinery is the premise to achieve the vegetable plantation and production process automation, and to achieve agriculture, especially vegetable production mechanization is of great significance. In this paper, the height of the vegetable pickling machine can not meet the requirements, the distance of the rhizome exposed is too short, which leads to the phenomenon of vegetable cutting and harvesting. Therefore, the model of the vegetable harvester is established, and the problem of cutting is analyzed. Based on the analysis of the above and below parts of the vegetable stem in the process of drawing, the mathematical parameters of the drawing force were analyzed, and the key factors affecting the pulling force of the vegetables were the height of the vegetables and the height slope. Through the tensile test of the rhizome of the vegetable sample and the compression test of the stem of the vegetable sample, the mechanics parameters of the vegetable were obtained, and the necessary theoretical support was provided for the simulation parameters of the extraction efficiency of the vegetable and the other research. The distinct element method (DEM) is a numerical simulation method for dealing with discontinuous medium problems. And it is widely used in the field of bulk material processing. EDEM software is a general CAE analysis software based on discrete element method, which is commonly used to simulate and analyze particle processing and operating system in industry and agricultural production. At present, its application in crop harvesting has not been reported, but it has been successfully applied in the field of agriculture, especially in the treatment of soil matrix. The discrete element simulation model of vegetable drawing process was established by using discrete element software EDEM, and the optimal drawing force and drawing effect were determined by studying the mechanism of pulling the vegetables. According to the simulation analysis, the relationship between the pulling force of vegetables and the displacement of vegetables and the simulation process of vegetable drawing were obtained. It was determined that the minimum drawing resistance was 26.87 N when the optimum drawing distance was 20 mm. The maximum safe draft load of vegetable rhizome was 37.5 N and the maximum safe compression load of vegetable stem was 84.36 N under the condition of safety factor of 1.1, using small universal testing machine. According to the upper and lower limits of the drawing force and the mathematical parameters of the drawing, the inclination angle of the planting trough to meet the planting of 1~6 vegetables was determined to be 17.8°. And at this angle of inclination, the maximum thrust value of the stem of the vegetable is less than the maximum destructive force of the vegetable 84.36 N. The final working parameters were applied to the single - row prototype test, and the good harvesting effect was obtained, which verified the rationality of the key parameters of the vegetable and vegetable harvest. [ABSTRACT FROM AUTHOR]

Currently, mass shake-and-catch tree fruit harvesting approach could cause fruit detachment efficiency in low level. Tree structure plays an important role in both harvest efficiency and machine performance for tree fruit. To obtain better harvest efficiency, it is important to optimize the machine parameters and provide proper excitation to the trees according to their growth morphology. This paper presented a finite element modeling method for the trained tree dynamic response study in relation to shaker type. Firstly, mathematic models of 3 types of shakers, including reciprocal shaker, orbital shaker and multidirectional shaker, were built, which were further used to analyze the basic working principles of these shakers. The basic principle of developed shaking models was analyzed according to their characteristics. In order to study the influence of different shakers on the dynamic response of trained tree, 3 training structures i.e. spindle, open center and vertical plane were selected. Their 3D (three-dimensional) physical models including trunk and secondary limbs were constructed in Pro/Engineer. Other elements, such as leaves and twigs, were removed from the model. Then, these models were imported into ANSYS software to analyze their modal shapes. The modal shape and resonance frequency were obtained in a frequency range of 1-50 Hz. Results showed that the resonance frequency and modal shape were influenced by the growth morphology of trees. Three types of trained tree model (spindle, open center and vertical plane) could obtain ideal response at the 10th, 14th, and 19th phase respectively. For the developed trained tree model, the natural frequency range was mainly contained from 7.0 to 20.0 Hz, corresponding to 420-1200 r/min of mechanical shaker. As having thick tree truck, the initial mode frequency of spindle-shape tree was greater than the other 2 types. To further study the dynamic response of the developed tree models, harmonic response simulation was conducted with 3 types of excitation patterns. For the spindle-shape tree, 3 excitations could all induce violent vibration at far-end of the limb (i.e. NODE4 and NODE5). Simulation results showed that multidirectional excitation could cause a relatively ideal response at 13.5 Hz (10th phase) for spindle-shape tree model. Multidirectional excitation could also induce the most violent response among the 3 methods and obtain the maximum displacement at featured location up to 1.844 m. Orbital excitation with 12.0 Hz (11st phase) could cause evident response with the maximum displacement of 2.485 m, and also provide relatively uniform response for open center tree model. However, a small part of area could only achieve a relatively low vibration response, as a portion of vibration energy was absorbed by the tree crotch. To obtain higher detachment efficiency, shaking from different directions would increase the machine performance for this type of trained tree. For vertical plane tree model, both reciprocal and orbital shaker could cause superior response considering mechanical harvest. Results obtained from field experiment validated the correctness of simulation results. The illustration method including modal analysis and harmonic response simulation, could be useful for new mechanical shaker design for trained fruit tree harvest. [ABSTRACT FROM AUTHOR]

Overlapped apples are common in natural scenes, and they can seriously affect the execution of picking task. Accurate segmentation of overlapped apples is one of the key problems that picking robot must solve. As the existing overlapped apples segmentation methods could not retain the contour of overlapped parts, a new method of segmenting overlapped apples was proposed in this paper. The steps of the algorithm were as follows: Firstly, the image was processed with morphological opening operation using disk-shaped structural element with the radius of 5 pixels so as to ensure the data information consistent in small area and to make the image more smooth. In order to distinguish the target and the background automatically, the image was then transformed from RGB color space into L*a*b color space. Then -means clustering method was used to segment images to extract apple region. Secondly, in order to extract accurate and entire contour of apple region and keep the contour of overlapped part simultaneously, Normalized Cut (Ncut) method was adopted. To ensure the accuracy of Ncut algorithm, the cluster number was chosen as 5. Thirdly, contour segmentation method was used to extract contour of each apple. The procedures of contour segmentation method were as follows: 1) The extracted contours were connected by simply using eroding operation in order to avoid disconnection at intersection of contours of 2 adjacent apples; 2) Refine the connected contour and search three cross point, then break off the contour at three cross point by assigning zero at three cross point, and 3 contours could be got; 3) Add the 2 contours whose bending directions were opposite, and this was the contour of unblocked apple and the other contour was the contour of blocked apple. Lastly, Spline interpolation method was used to reconstruct the contour of blocked apples. In order to verify the validity of this algorithm, 20 images of adjacent apples were used to conduct the experiment, and the result was compared with the comparison method. The comparison method is a method that uses the connection line of 2 concave points to segment overlapped apples, and then utilizes the Hough transform method to reconstruct the contour of apples. The experimental results showed that for unblocked apples in apple images, average segmentation error of the presented method was 3.15%, 7.73% less than that of comparison method (10.88%). Average overlap ratio of the presented method was 96.08% and was increased by 9.71% compared to comparison method (90.85%). In addition, this method could keep the complete contour information of unblocked apples and thus improved segmentation accuracy effectively. For blocked apples, average segmentation error and average overlap ratio were 5.24% and 93.81%, respectively. The segmentation error was decreased by 11.35% and average overlap ratio was increased by 12.74% compared to comparison method, which indicated that the method could reconstruct contour of blocked apples well. In conclusion, the presented algorithm is feasible to segment and reconstruct 2 overlapped apples without blocking by branches and leaves. However, for the images of overlapped apple blocked by branches and leaves, the images of more than 2 overlapped apples, and the images of 2 overlapped apples unblocked by branches and leaves with unclear contour at overlapped part, this method cannot complete the segmentation, and thus further research would be needed. [ABSTRACT FROM AUTHOR]

Recently, as scientific research has been further explored, the health care functions of the Lycium barbarum (L. barbarum) in anti-oxidation, anti-aging, anti-fatigue, protecting liver, improving body immunity, eye protection and other aspects have been further confirmed. Its unique and nutrient-rich health function is recognized gradually in western countries, and the market demand of the L. barbarum is expanding each year. The L. barbarum blooms and bears fruit continuously during the growing season which begins in mid-May. Depending on the picking time around the year, the L. barbarum fruit can be divided into spring, summer and autumn fruit. In order to make dried L. barbarum keep good commodity characters, the L. barbarum is harvested at 80 percent maturity. The full bearing period of L. barbarum is from May to September every year, which is the picking peak of L. barbarum. It must be picked once about every 7 days. For centuries, the mechanized harvesting of L. barbarum has been a tough problem. Its harvesting has been artificial, which brings about low picking efficiency and high harvesting costs. With the continuous expansion of L. barbarum acreage, fruit picker has been increasingly scarce, which will be followed by rising picking costs. It's no doubt that the picking has become the bottleneck restricting the development of L. barbarum industry. Aiming at realizing the harvesting mechanization of L. barbarum and establishing the theoretical guidance and design basis for the L. barbarum picking machine, the vibration picking mechanism of L. barbarum plant's fruiting branches in picking was studied, the parameter optimization and simulation analysis was done to determine exciting force vector and rotational speed of driving wheel, and an experiment was conducted to prove the obtained rotational speed of driving wheel in this paper. First, we analyzed the working principle of the picking machine to get the vibration picking mechanism. The fruiting branches' model was simplified and the L. barbarum plant's fruiting branches' physical model and mathematical model were got, which were solved by equation solutions. We then obtained the forced vibration response of the fruiting branch and the forced vibration picking inertia force exerted on ripe and unripe fruits and flowers on each node. Second, 10 L. barbarum trees were selected as the test samples. We measured the binding force and mechanical parameters of the L. barbarum and fruiting branches, such as the number of ripe and unripe fruits and flowers, diameter, length, elastic modulus, damping ratio of fruiting branches, and node number. Based on the principle of successful picking which is the ripe can be picked and the other parts wouldn't be picked, the parameters were optimized, and the inertia force changes of the fruits and flowers with rotational speed were simulated with the MATLAB software. Simulation results showed the reasonable rotational speed was 2 868.84-2 871.21 r/min. Finally, rotational speeds of 7 levels which came from the interval and beyond the interval were selected in the experiment. Using a self-developed experimental L. barbarum picking machine, the test was conducted at planting base of L. barbarum of Ningxia Academy of Agriculture and Forestry Sciences, and the fruit distribution before and after picking was compared. Experiment result showed that reasonable rotational speed was 2 870 r/min, which is within the reasonable simulation interval of rotational speed. Under this rotational speed, picking efficiency of ripe L. barbarum was 815 grains per minute, the picking rate of ripe fruit was 86.70%, the picking rate of unripe fruit was 7.36%, and the picking rate of flower was 7.43%. The damage rate of fruit was 8.62%. The efficiency ratio of machine to worker was 5.43. Due to the actual picking environment, this result differs from simulation conclusion that the ripe is picked totally and none of the unripe and flowers is picked. The results can provide a reference for the development of L. barbarum vibration picking machines. [ABSTRACT FROM AUTHOR]

Due to long stubble remained in farmland after harvesting as well as hardened and impervious soil in southern farmland of China, the tillage and land preparation parts of multifunctional rape-planting machine tend to wind grass and obstruct with mud, which impairs the working performance of ridging equipment and reduces the percentage of rapeseed seedling germination. In order to solve these problems, a rapeseed planting method is proposed, which combines the straw mulching cultivation with the direct seeding. The method is used to collect and cut the rice stubbles, and then the chopped rice stubbles are evenly covered on the inter-row spaces without involving the tillage apparatus. A multifunctional rape-planting device is mounted to a rice combine-harvester by replacing screening device, using the original harvester header to collect the rice stubbles and replacing the threshing cylinder to chop and scatter the rice stubbles. In this paper, an air-assisted chopping mechanism was designed, in which the moving knives and the transplanting blades were coaxially installed. The performance of the air-assisted chopping mechanism was evaluated by simulating the chopping operation of "stalk-standing" and "crop residue" in farmland through a bench test driven by an electric motor. A quadratic orthogonal rotating experiment was designed by Design-Expert software. Based on the variance analysis and regression fitting, a multiple regression equation was obtained, showing the effects of the rotating speed of feeding press rolls, the rotating speed of rotation shaft of moving knives and the gaps between moving knife and stationary knife on the qualified rate of chopped stalk length and the power attenuation. It was shown that the rotating speed of rotation shaft of moving knives had the most influential effect, followed by the gaps between moving knife and stationary knife, and the rotating speed of feeding press rolls had the least effect on the qualified rate of chopped stalk length and the power attenuation. The response surface method was applied to optimize the operation conditions. The optimum factors for "stalk-standing" and "crop residue" chopping operation were as follows: The rotating speeds of feeding press rolls were 399.2 and 401.64 r/min, the rotating speeds of rotation shaft of moving knives were 968.12 and 977.23 r/min, and the gaps between moving knife and stationary knife were 0.52 and 0.49 mm, respectively. Under the optimal condition, the corresponding qualified rates of chopped stalk length for "stalk-standing" and "crop residue" were 95.89% and 97.09%, as well as the power attenuations were 3.04 and 2.6 kW, respectively. The differences between the experimental and the software analytical value of the qualified rate of chopped stalk length for "stalk-standing" and "crop residue" were both 0.11% and those of power attenuation were 0.05 and 0.08 kW, respectively, which indicated that the software analytical value was in great agreement with the experiment value. Based on the theoretical analysis, the higher qualified rate of chopped stalk length could be achieved under the faster rotating speed of rotation shaft of moving knives and the smaller gaps between moving knife and stationary knife. Taking into consideration the existing form of rice straw in farmland, the rotating speed of feeding press roll was designed to be 401.64 r/min, the rotating speed of rotation shaft of moving knife 977.23 r/min, and the gap between moving knife and stationary knife 0.49 mm. It can provide technical support for the design of rapeseed planter with the combination of straw-mulching cultivation and direct seeding. [ABSTRACT FROM AUTHOR]

Sweet potato is a crop which is drought-resistant, tolerant of poor soil, and owns increasingly enormous potential. It is an important foodstuff, a raw material for starch industry, a kind of health food to prevent cancer and a new raw material for energy as well. The sweet potato planting area in China per year on average is usually 3 667 000 hectares, accounting for 45% of the world's planting area. As sweet potato vines are very long and broomy, the vines must be cleaned up before sweet potatoes are harvested, otherwise are unable to be harvested. Vine crushing and returning machine is usually the dominant form adopted to clean sweet potato vines internationally, but the problems existed in this type of machine were obvious such as low smashing proportion and more stubble residue on the top ridge. New problems have been brought by long stubble such as blocking, larger load and worse smooth working property. Aiming at these problems, the machinery and agronomy should be combined, in order to prove mechanical properties of sweet potato vine and stalk during harvest and working quality of sweet potato vine crushing and returning testing machine. In this paper, the types of fresh purple sweet potato Ningzi 1 and Ningzi 2 in Nanjing, Jiangsu Province were regarded as the tested subject, the electronic universal testing machine, electric drying oven with forced convection, and sweet potato vine crushing and returning testing machine etc. were applied, and the change of moisture percentage and shear strength of sweet potato stalk during harvest were studied. The results showed that at the beginning of experience harvest period, when the percentage of moisture were 81.5% and 78.1%, the shear force were 90.1 and 94.8 N, respectively, during 18 testing days the moisture percentage of sweet potato stalk reduced by 14.8% and 13.97%, respectively, but the shear force of stalk increased by 36.3 and 37.5 N respectively, which showed that the moisture percentage of sweet potato stalk was lower and the shear force was larger as the growth time of plants went on. The internal relations between mechanical crushing quality and percentage of moisture, shear strength were revealed: during the testing period of 18 days, the qualified rates of vine's crushing length for sweet potato type Ningzi 1 and Ningzi 2 dropped by 6.3% and 6.7% respectively, stubble length on top ridge increased by 3.6 and 4.4 cm respectively, which showed that with the increasing of the growth period and the rising of stalk's shear force, the working quality of sweet potato vine crushing and returning machine declined. The quadratic function regression equations on the change between shearing force and moisture percentage of the two types of fresh purple sweet potatoes' stalk were obtained with Matlab when the percentage of moisture was 86.92%-70.08%, and the fitting coefficient of determination R² both reached above 0.99. From the point of increasing the quality of mechanical smashing and mechanical work, it was put forward that the most suitable time of mechanical crushing for the two kinds of purple sweet potatoes during harvest was about 6-8 days, which was a relatively short time. The results offer the direct basis for parameter design of new sweet potato vine crushing and returning testing machine such as machine speed, cutter linear velocity, and also provide the important reference for the selection of suitable harvest period and cultivation agronomic research that fits for machinery operations. [ABSTRACT FROM AUTHOR]