In the context of the rapid rise of agricultural mechanization in China, this paper examines the impact of household-owned farm machinery and outsourced agricultural machinery services on the land ...leasing behavior of Chinese relatively large-scale farmers. Based on the CFPS2018 survey data, this study suggests that farm machinery is beneficial for expanding the scale of farms. With increases in household-owned machinery, farmers are more inclined to lease-in land, and they are less inclined to rent-out land. The more agricultural machinery services farmers purchase, the more they tend to transfer-in land and the probability of transfer-out land is lower. However, uneven village terrain can weaken the effects of the two kinds of agricultural mechanization on land leasing. Moreover, this study confirms that household-owned farm machinery and outsourced agricultural machinery services could positively regulate each other's influence on land leasing, indicating that there is a complementary relationship between the two types of agricultural machinery. Further mechanism analyses show that the channels by which household-owned farm machinery and outsourced agricultural machinery services affect land leasing are quite different. The self-purchased machinery of farmers mainly plays a role through labor complementarity effects, while outsourced agricultural machinery services mainly affect land leasing through labor substitution effects.
•With increases in household-owned machinery, farmers are more (less) inclined to lease-in (lease-out) land.•The more agricultural machinery services farmers purchase, the more (less) they tend to transfer-in (transfer-out) land.•There is a complementary relationship between household-owned farm machinery and outsourced agricultural machinery services.•Self-purchased farm machinery mainly plays a role through labor complementarity effects.•Outsourced agricultural machinery services mainly affect land leasing through labor substitution effects.
•China’s agricultural machinery operation big data system was developed.•The system integrated positioning data and working data of major manufacturers.•A case study for China’s wheat harvesters ...demonstrated its potential.
Agricultural machinery operations are mainly performed by cross-regional socialized services in China. It is necessary to take advantage of national data system to implement dynamic monitoring, data sharing, and big data applications for agricultural machinery operations. This application note outlines the system composition, principal technology, primary functions, and application examples of the big data system. This system integrates agricultural machinery operations with big data, which can promote scientific decision-making with data management and facilitate more efficient agricultural production. Promoting the effective, orderly, and scientific growth of agricultural machinery operations and the advancement of agricultural modernization is of theoretical and practical importance.
•Task assignment model.•Dynamic and static simulation.•Crop harvesting simulation.
Task assignment is a key problem in multi-machine cooperative navigation. In the context of regional farmland ...operation, multiple agricultural machines often need to complete multiple tasks together. In order to realize the management of multiple agricultural machinery cooperation, studies on task assignment based on the improved ant colony algorithm have been conducted under the farmland operation environment. First, a task assignment model of multiple agricultural machinery cooperation was established by combining dynamic and static task assignments. Then, according to the task assignment model, the task assignment process based on the improved ant colony algorithm was established while considering the match between supply and demand, the operation capacity of the agricultural machinery, and the operation cycle and path cost. Finally, the dynamic and static task assignments of multiple agricultural machinery cooperation based on the improved ant colony algorithm were simulated on MATLAB. Taking the crop harvesting experiment as an example, according to the actual farmland location information of the Zhuozhou Experimental Farm, the different (agricultural machinery, task) combinations were set, and the task assignment results were compared and analyzed. Results showed that the path costs of harvester and grain transporters were reduced by 51.27% and 22.00% respectively, When the quantities of tasks were set to 11, indicating that the improved ant colony algorithm can effectively reduce the path cost. When the quantities of tasks were set to 5, 11, 16 and 22, the average operation cycles were shortened by 67.32%, 37.50%, 55.95%, and 56.37% respectively. The problem of “nearby” in the task assignment was solved to a certain extent, the overload of some agricultural machinery and the idle of other agricultural machinery were avoided, and the operation cycle was shortened. At the same time, based on the static task assignment, the dynamic task assignment was realized in the two scenarios of new tasks and malfunctioning harvesters, thus laying a foundation for further solving the scheduling management problem of multiple agricultural machinery cooperation under a complex farmland operation environment.
To improve the utilisation of peanut vines as animal feed and address the inability of current agronomic and agricultural machinery in China to adapt and the low levels of mechanised peanut ...production, a “three-stage” harvesting mode, “vine cutting harvesting – digging and drying – pickup and picking”, that produces peanut vines suitable for feed was proposed. The general agronomic process of mechanised peanut production under this mode was studied, and the requirements for integrating agricultural machinery and agronomy into each key production process were proposed. Plant characteristics, stubble height consistency and pickup effects were measured and tested in the field. The influence of ridge height differences, ridge width differences and row spacing differences on the variation coefficient of stubble height consistency and their significance were analysed. The results showed that the influence of ridge height differences and ridge width differences was significant and that of row spacing differences was not significant. The influence of pickup spring finger spacing, soil penetration depth, forward speed, variety, stubble height and the variation coefficient of stubble height consistency on the pickup rate and the pickup dropping rate, and their significance were studied. The results showed that the stubble height and its consistency variability coefficient had an extremely significant impact on the pickup rate and the spring finger spacing had a significant impact; the soil penetration depth and forward speed had significant effects on the pickup dropping rate, and the stalk connection force and the stubble height had an extremely significant impact.
•Three-stages proposed: vine cutting & harvesting/digging & drying/pickup.•General agronomic process of mechanised peanut production studied.•Requirements of agricultural machinery & agronomy integrated in each production phase.•Standard machine needs only slight change to adapt mode and realise multiple roles.
•The first model based on GRU to reconstruct missing points in agricultural machinery trajectories is proposed.•A bidirectional feature extraction module is proposed to capture bidirectional ...information of the missing trajectory points.•A lightweight model is customized for massive agricultural machinery trajectory data.•The reconstruction deviation exceeds the Beidou GNSS positioning accuracy.
Agricultural machinery trajectory data often encounters the phenomenon of missing trajectory points, and reconstructing these missing trajectory points is crucial for subsequent researches that require complete and high-quality agricultural machinery trajectory data. In this paper, we propose a new method called Fast-TRGRU to accurately and quickly reconstruct missing points in the trajectory of agricultural machinery. First, we design a novel data preprocessing process to improve the quality of raw data. Next, we introduce a bidirectional feature extraction module (BFE) to simultaneously utilize the bidirectional adjacent subtrajectory information of missing trajectory points. Then, we use gated recurrent unit (GRU) to extract spatiotemporal correlation features from time series data representing agricultural machinery trajectories to reconstruct trajectories. Finally, we reduce the training time of the model by adjusting the structure of the model in the GRU model. To verify the effectiveness of the model, we conducted experiments using 125 real agricultural machinery trajectory samples including 1,111,813 points provided by the Key Laboratory of Agricultural Machinery Monitoring and Big Data Applications of the Ministry of Agriculture and Rural Affairs. The experimental results show that when the trajectory missing rate is 10 %, the average reconstruction deviations of the model in longitude and latitude are only 1.80 m and 1.95 m, respectively. When the trajectory missing rate is 60 %, the average reconstruction deviation of the model in both longitude and latitude is still less than 4 m, which is higher than the positioning accuracy of the Beidou Navigation Satellite System. The Fast-TRGRU can provide complete and high-quality data for the analysis of agricultural machinery trajectories, effectively assisting in the research of optimizing agricultural machinery operation paths and evaluating agricultural machinery operation efficiency.
The article provides an overview of the peculiarities of functioning and analysis of performance indicators of machine-building enterprises in 22 countries of the European Union and Ukraine. The ...article studies profitability indicators of machine-building enterprises, with an emphasis on the peculiarities of approaches to pricing. A comparative analysis of the number of machine-building enterprises and the number of people employed in machine-building in each country was carried out. The indicators of imports of machinery and equipment for agriculture from Ukraine to the EU countries are analysed in terms of the main product groups. A comparative analysis of the activities of the machine-building industry of the EU and Ukraine per enterprise, with special attention to the indicators of costs and investments, was carried out. The volumes of investments in material assets, machinery and equipment, personnel, and energy costs were analysed. An evaluation of these indicators of the functioning of machine-building enterprises of the European Union and Ukraine has allowed to identify the key problems of domestic machine-building enterprises in the context of ensuring the competitiveness of their products in the EU market. In particular, the author has established the existence of fundamental differences between Ukrainian and European machine-building producers in terms of investment in personnel and renewal of fixed assets, which leads to a significant technological lag behind their European competitors and a lag in terms of individual productivity of personnel.
•The direct-seeding path for rice covers the entire field.•Rice direct-seeding path includes the encircling path around the field blocks.•Encircling path planning algorithm is applicable to different ...shapes fields.•The path planning encompasses various patterns and path sequences.
Path planning is one of the key technologies that determines the efficiency and quality of field operations using autonomous agricultural machinery. To date, there has been extensive research on global coverage path planning for unmanned agricultural machinery within the working area; however, the issue of “encircling and edging” left by the machinery during headland turns is often overlooked. This study focuses on the operational conditions of unmanned agricultural machinery in the rice fields of southern China. The path planning problem is abstracted under physical constraints, such as the space at the field headland, the agricultural environment (e.g., types of field ridges), the turning characteristics of the machinery, turning radius, working width, and minimum safety distance, into mathematical constraints. This yields an optimized path planning model and sequence combination. Based on the improved Reeds–Shepp curve, an en-circling and edging path planning algorithm is designed. The planned path for the unmanned agricultural machinery from start to finish consists only of arcs and straight lines, suitable for the right-angle turning, reversing, and 180° U-turn operations required for rice field machinery, thus significantly improving the coverage of field edges and missed areas at the headland. A rice direct-seeding machine was used as a test subject for encircling and edging field trials, with tests conducted in rectangular, trapezoidal, and irregular quadrilateral rice fields. The results show that, for rectangular plots, the full-field coverage rate of rice direct-seeding operations can reach 96.44%; for trapezoidal plots, the coverage rate is 95.47%; and for irregular quadrilateral fields, the coverage rate is 95.69%. These results are promising, indicating that the encircling and edging path planning based on the improved Reeds–Shepp curve can effectively increase the full-field coverage rate of unmanned agricultural machinery, improving work quality and meeting the needs of modernized, intelligent agricultural machinery operations.
In its historical process, agricultural mechanization has evolved from muscle power to advanced sensor applications, drones and autonomous tractors with the help of technology. The importance of ...agricultural mechanization increases due to reasons such as providing basic food need, reducing costs, eliminating labor problems and obtaining higher yields per unit area. The aim of this study is to evaluate the current situation of agricultural mechanization in Turkey. In this evaluation, the number of tractors, the number of combine harvesters and age groups, the change of agricultural machinery by years, import and export values, and the change of agricultural mechanization indicators by years were examined. While there were 654 636 tractors in 1988, this figure reached to 1 332 139 in 2018 in Turkey. While there were 12 578 combine harvesters in 2000, this value increased by approximately 37% in 2018 to 17 266. Over the years, there has been an increase in agricultural mechanization, fruit harvesters, cotton harvesters, motor scythes and feed spreading trailers, while there has been a serious decrease in the number of animal-borne grain planting machines, agricultural protection aircraft, threshing sled, primitive plough and livestock plows. Considering the import and export values of agricultural mechanization equipment between 2001 and 2018, the import value was approximately 2 times of the export value in 2001, while this value almost equalized in 2016, and the export value increased approximately 1.4 times the import value in 2018.
With the development of the “Internet +” model and the sharing economy model, the “online car-hailing” operation model has promoted the emergence of “online-hailing agricultural machinery”. This new ...supply and demand model of agricultural machinery has brought greater convenience to the marketization of agricultural machinery services. However, although this approach has solved the use of some agricultural machinery resources, it has not yet formed a scientific and systematic scheduling model. Referring to the existing agricultural machinery scheduling modes and the actual demand of agricultural production, based on the idea of resource sharing, in this research, the soft and hard time windows were combined to carry out the research on the dynamic demand scheduling strategy of agricultural machinery. The main conclusions obtained include: (1) Based on the ideas of order resource sharing and agricultural machinery resource sharing, a general model of agricultural machinery scheduling that meet the dynamic needs was established, and a more scientific scheduling plan was proposed; (2) Based on the multi-population coevolutionary genetic algorithm, the dynamic scheduling scheme for shared agricultural machinery for on-demand farming services was obtained, which can reasonably insert the dynamic orders on the basis of the initial scheduling scheme, and realize the timely response to farmers’ operation demands; (3) By comparing with the actual production situation, the path cost and total operating cost were saved, thus the feasibility and effectiveness of the scheduling model were clarified.
Aim of study: To determine the optimal working speed of a gear-driven rotary planting mechanism for a self-propelled riding-type onion transplanter in order to choose an adequate forward speed for ...effective onion (Allium cepa L.) seedling planting. Area of study: Daejeon, Korea. Material and methods: The gear-driven rotary planting mechanism was composed of six planting hoppers that received free-falling onion seedlings through the supply mechanism and deposited them into the soil. To determine the optimal working speed for accurate transplantation of the seedlings, mathematical working trajectory modelling of the planting mechanism, virtual simulations, and validation field experiments were carried out. Main results: According to the model simulation, a forward speed of 0.15 m s-1 of the transplanter and a rotating speed of 60 rpm of the planting mechanism were favourable for seedling uprightness and minimum mulch film damage. For the proposed transplanting mechanism, the free-falling distance was calculated as 0.08 m, and the accuracy for the seedling deposition into the hopper was demonstrated as 97.16% through the validation test. From the field tests, a forward speed of 0.15 m s-1 combined with a transplanting frequency of 60 seedlings min-1 was found to be optimum for obtaining a high seedling uprightness (90o), a low misplant rate (7.66%), a low damage area on mulch film, and low power consumption (36.53 W). Research highlights: The findings of this research might be helpful in improving the design of the onion transplanting mechanism and accelerating the automation process for seedling transplantation.
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