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To explore the spatial-temporal evolution and driving factors of cultivated land multifunctional coupling coordination development, this paper applying the data of 30 provinces in China from 2000 to 2018 evaluated cultivated land production-living-ecological functions and revealed the spatial-temporal evolution of cultivated land multifunction with kernel density estimation and visualization mapping. Furthermore, this paper adopted coupling coordination degree model to analyze the cultivated land multifunctional coupling coordination development. Finally, this paper explored driving factors and driving mechanism of cultivated land multifunctional coupling coordination development by geographical detector. The results showed that: 1) from the perspective of temporal evolution, cultivated land production function level showed a fluctuation evolution trend of “rising-falling-rising”, the living function level showed an evolution trend of “rising-falling”, and the ecological function level increased slightly. All cultivated land functions had polarized characteristics. From the perspective of spatial pattern, the cultivated land production function level changed within [0.030, 0.608], showing a non-equilibrium spatial pattern of “high in the east, low in the west”. The living function level changed within [0.042, 0.672], showing a non-equilibrium spatial pattern of “high in the north, low in the south”. The ecological function level changed within [0.058, 0.897], showing a non-equilibrium spatial pattern of “high in the west, low in the east”. The areas with high level of production and living function were concentrated in the Northeast Plain, the Huang-Huai-Hai Plain and the Yangtze Region. The areas with low level of production function were located in the northwest and southwest regions, and the areas with low level of living function were located in the Beijing-Tianjin, Yunnan-Guizhou and southern regions in China. The area with high level of ecological function areas were located in the northeast and southwest regions, while the low-level areas were located in the Beijing-Tianjin-Hebei region, the Yangtze River Delta region and the central region of the Yangtze River. 2) The cultivated land multifunctional coupling coordination level changed within [0.093, 0.554], and the overall level had steadily improved but was still low. The cultivated land multifunctional coupling coordination levels of most provinces were still out of balance. The spatial pattern of cultivated land multifunctional coupling coordination level showed an evolution trend of agglomeration and promotion. In detail, the cultivated land multifunctional coupling coordination level of the northeast China, Beijing-Tianjin-Hebei region and the Yangtze River Delta were relatively high, while that was low in the northwestern part of China. 3) The evolution of cultivated land multifunctional coupling coordination level was significantly affected by the business entities conditions, agricultural development level, industrial development level and urbanization level. In short, the driving force of the business entities conditions and urbanization level were more significant than that of the agricultural development level and industrial development level. Moreover, the interaction type of two driving factors was two-factor enhancement or nonlinear enhancement, which indicated that the driving force of various factors had obvious divergence and interaction of factors positively strengthened the single-factor driving force, indicated that the divergence and interaction of various driving factors positively strengthened the single-factor driving force. In conclusion, the research results provide the guiding effect for deepening the study on cultivated land multifunction and decision support for promoting the differential governance of cultivated land resources and mutual promotion of cultivated land functions. To explore the spatial-temporal evolution and driving factors of cultivated land multifunctional coupling coordination development, this paper applying the data of 30 provinces in China from 2000 to 2018 evaluated cultivated land production-living-ecological functions and revealed the spatial-temporal evolution of cultivated land multifunction with kernel density estimation and visualization mapping. Furthermore, this paper adopted coupling coordination degree model to analyze the cultivated land multifunctional coupling coordination development. Finally, this paper explored driving factors and driving mechanism of cultivated land multifunctional coupling coordination development by geographical detector. The results showed that: 1) from the perspective of temporal evolution, cultivated land production function level showed a fluctuation evolution trend of “rising-falling-rising”, the living function level showed an evolution trend of “rising-falling”, and the ecological function level increased slightly. All cultivated land functions had polarized characteristics. From the perspective of spatial pattern, the cultivated land production function level changed within [0.030, 0.608], showing a non-equilibrium spatial pattern of “high in the east, low in the west”. The living function level changed within [0.042, 0.672], showing a non-equilibrium spatial pattern of “high in the north, low in the south”. The ecological function level changed within [0.058, 0.897], showing a non-equilibrium spatial pattern of “high in the west, low in the east”. The areas with high level of production and living function were concentrated in the Northeast Plain, the Huang-Huai-Hai Plain and the Yangtze Region. The areas with low level of production function were located in the northwest and southwest regions, and the areas with low level of living function were located in the Beijing-Tianjin, Yunnan-Guizhou and southern regions in China. The area with high level of ecological function areas were located in the northeast and southwest regions, while the low-level areas were located in the Beijing-Tianjin-Hebei region, the Yangtze River Delta region and the central region of the Yangtze River. 2) The cultivated land multifunctional coupling coordination level changed within [0.093, 0.554], and the overall level had steadily improved but was still low. The cultivated land multifunctional coupling coordination levels of most provinces were still out of balance. The spatial pattern of cultivated land multifunctional coupling coordination level showed an evolution trend of agglomeration and promotion. In detail, the cultivated land multifunctional coupling coordination level of the northeast China, Beijing-Tianjin-Hebei region and the Yangtze River Delta were relatively high, while that was low in the northwestern part of China. 3) The evolution of cultivated land multifunctional coupling coordination level was significantly affected by the business entities conditions, agricultural development level, industrial development level and urbanization level. In short, the driving force of the business entities conditions and urbanization level were more significant than that of the agricultural development level and industrial development level. Moreover, the interaction type of two driving factors was two-factor enhancement or nonlinear enhancement, which indicated that the driving force of various factors had obvious divergence and interaction of factors positively strengthened the single-factor driving force, indicated that the divergence and interaction of various driving factors positively strengthened the single-factor driving force. In conclusion, the research results provide the guiding effect for deepening the study on cultivated land multifunction and decision support for promoting the differential governance of cultivated land resources and mutual promotion of cultivated land functions. [ABSTRACT FROM AUTHOR]

Assessing the sustainable development of agriculture is a hot topic in global agricultural research and an important task of rural revitalization and agricultural upgrading in the new era. Reform and opening up promote the rapid development of the agricultural economy, but the conflict between agricultural development and agricultural resources and ecological environment is serious. Since the 18th National Congress of the CPC, the sustainable development of agriculture has been given more prominence. It is of great significance to study the evaluation of agricultural sustainable development. Firstly, this paper studies the relevant literature on agricultural sustainable development evaluation at home and abroad. Based on wavelet transform, support vector machine(SVM), genetic algorithm (GA)and ant colony optimization(ACO) algorithm, a combination evaluation method of wavelet and intelligent optimization support vector machine is proposed. Secondly, by referring to the existing evaluation index system and combining with the actual situation of China's agricultural development, the alternative index set of agricultural sustainable development evaluation is established. Using SPSS software, the significance and correlation of 150 primary indexes are analyzed, and an evaluation index system including 62 indexes is established. Thirdly, using one-dimensional discrete stationary wavelet analysis, data denoising processing, genetic algorithm, ant colony algorithm, optimize the parameters of support vector machine, get better penalty parameters, kernel function, insensitivity coefficient, and then train the support vector machine. Fourth, taking 31 provinces (municipalities) in China as an example, this paper evaluates the agricultural sustainable development by applying the wavelet-GASVM model and the wavelet-ACOSVM model, and using the GA-SVM model and the ACO-SVM model to evaluate the agricultural sustainable development of 31 provinces (municipalities) in China. Fifthly, the reliability of the wavelet intelligent optimization SVM method is verified by changing the number of test sets and conducting multiple tests. The evaluation and simulation results show that: 1) The mean square error of agricultural sustainable development evaluation of Wavelte-GASVM is 9.641×10-5, and the correlation coefficient is 0.980; however, under the same training set and test set, the mean square error and correlation coefficient obtained by GASVM are 0.006 and 0.979, respectively. 2)The mean square error of Wavelet-ACOSVM agricultural sustainable development evaluation was 9.318×10-5, and the correlation coefficient was 0.972; the mean square error MSE and correlation coefficient of ACO-SVM are 0.016 and 0.953, respectively, under the same training set and test set. 3) Change the number of test sets and perform several tests and compare the results of GASVM model and ACO-SVM model before and after wavelet denoising respectively. It can be seen that under the GASVM model, the mean square error of the running results after wavelet denoising is smaller than that before wavelet denoising, and the correlation coefficient is larger than that before wavelet denoising, and the running time is shorter. Under the ACOSVM model, the mean square error of the running result after wavelet denoising is also smaller than that before wavelet denoising, and the correlation coefficient is larger than that before wavelet denoising, and the running time is shorter. Conclusion: The prediction accuracy and convergence speed of agricultural sustainable development evaluation by wavelet-GASVM and wavelet-ACOSVM are better than GA-SVM and ACO-SVM, respectively, and the effect of agricultural sustainable development evaluation by wavelet-GASVM is more ideal. This study provides a method reference for agricultural sustainable development assessment. [ABSTRACT FROM AUTHOR]

Vigorously promoting photovoltaic power generation meets the requirements of energy structure transition, which contributes to environmental protection. Abundant land resources in rural areas provide inherently convenient conditions for photovoltaic power generation. Rural photovoltaic projects provide a sustainable, clean, and low-carbon power supply for production and life, which increases positive ecological values, such as reducing carbon emissions by helping farmers wean off traditional fossil fuels, creating employment opportunities, etc. However, there are also some negative ecological values, such as the construction of photovoltaic power stations causing soil-water losses and construction occupations, which not only reduce the planting incomes of farmers, but also damage rural ecosystems. Therefore, ecological compensation for participators in the photovoltaic project, i.e., photovoltaic power station construction enterprises, farmers, and village collectives, is required to balance the participants' benefits and losses. However traditional compensation methods cannot decide the accurate compensation standards for participators. Hence, referring to the ecosystem service values in the Millennium Ecosystem Assessment, an ecosystem service assessment index system (ESAIS) that includes economic, social, and environmental aspects is proposed in this paper. Based on the proposed ESAIS, the calculation modes for economic values (e.g., electric energy, construction incomes, etc.), social security values, and environment values (e.g., energy conservation and emission reduction, soil-water losses, etc.) are proposed based on market valuation methods, shadow project approaches, opportunity cost methods, etc., can be employed to quantitatively analyze the ecological values of participators. On this basis, the relationship between benefits and expenditures among the participators is established. Then an optimal decision-making model for ecological compensation is introduced to minimize the proportion of low-income farmers with the constraints of the balance of payments, which contributes to achieving win-win cooperation among the participators and sustainable energy development. Based on actual data from rural photovoltaic projects in China, case studies are carried out to verify the proposed ecological compensation model. Under the premise of ensuring reasonable profitability for all participators, the proposed model maximizes the contributions of beneficiaries in the ecological compensation schemes, which contributes to preventing farmers from returning to low income. Compared to traditional compensation methods that compensate farmers based on production inputs, direct losses, or waste disposal fees, the proposed method not only guarantees all participators have positive ecological values and environmental values after compensation, but also increases all farmers’ income levels by maximizing their incomes. Hence, the proposed model contributes to the realization of rural revitalization strategy and sustainable development, which has directive significance for economic advancement in underdeveloped regions worldwide. [ABSTRACT FROM AUTHOR]

In recent years, under the guidance of China's green energy development strategy, a large number of photovoltaic, wind power and other DGs have been connected to the rural distribution network. The current rural distribution network structure, DG grid-connected location and capacity, line transmission capacity and other system conditions are in conflict with the ever-increasing rural power demand. DG output and load demand are continuously changing with time. The large-scale access of DGs and EVs has made the “source-load” side of the rural distribution network present significant uncertainty. The traditional topology of rural distribution network cannot cope with the impact of this “source-load” double uncertainty. Therefore, it is urgent to study a new method of dynamic reconfiguration for rural active distribution network. This paper establishes a dynamic reconfiguration model of active distribution network with DG consumption and line loss as objective functions. Taking into account the time-varying characteristics of “source-load”, this paper proposes a new method of dynamic reconfiguration of rural active distribution network based on regional division, and designs the process of this dynamic reconfiguration method. In order to improve the efficiency of solving the problem of dynamic reconfiguration of active distribution network, a regional division method is proposed for the first time. The regional division method includes two parts: The initial division of regions and the optimized division of regions. The dynamic reconfiguration method of active distribution network based on area division mainly includes the following four steps. Firstly, the distribution network structure is divided into several initial regions which include main line regions and branch line regions based on the regional initial division method. Secondly, with the goal of promoting the flexible and efficient combined application of DGs between regions, the result of regional initial division is optimized dynamically based on the breadth-first traversal algorithm in the graph theory algorithm. Thirdly, based on the obtained results of dynamic regional optimization, the depth-first traversal algorithm is used to test and modify the DNR scheme to meet the topology constraints of the distribution network. At this time, all feasible DNR schemes can be obtained. Finally, the fast non-dominated sorting strategy is adopted to select the best network reconfiguration scheme that meets the constraints such as node voltage. To validate the performance of the proposed method, it is tested on the well-known IEEE 33-node and PG&E 69-node distribution system. The simulation result of 33-node distribution system shows that the loss reduction effect of the proposed method is very good. Especially at 14:00, the loss reduction effect of the distribution network was the most obvious, which was reduced by 71.41%. At this time, the effect of increasing the utilization rate of DG consumption is also obvious. On this basis, the proposed method on the consumption of each DG was deeply analyzed in this article. Result shows that the proposed method can achieve complete consumption of DG. The voltage of each node under the network structure obtained by the regional optimization division method meets the voltage quality requirements. In addition, the average daily DG consumption rate of the PG&E 69-node distribution system was increased by 16.09 percent point, and the daily line loss was reduced by 55.32%. The effectiveness of the proposed method is verified by the simulation of these two case studies. The simulation results show that the proposed method can fully switch and adjust the ability to improve the absorption capacity of the distributed power, reduce the line loss, suppress the fluctuation of the distributed power, and keep the node voltage smooth. [ABSTRACT FROM AUTHOR]

At present, the problems of energy depletion and environmental pollution caused by non renewable energy such as oil and coal have seriously hindered the sustainable development of our society. Biomass energy is a reliable low-carbon alternative energy with renewable, clean and other characteristics. Therefore, the energy transformation to renewable energy is crucial to China's development. Research shows that China has rich biomass resources. For example, agricultural wastes can be used to produce biogas by anaerobic fermentation of agricultural wastes straw, which can reduce a lot of carbon emissions. Therefore, it is of great significance for China's development to make full and reasonable use of this resource. This paper discusses two types of biogas power generation technologies using straw as raw material, namely, traditional biogas direct combustion power generation technology and biogas fuel cell power generation technology. Based on life cycle assessment (LCA) and time value dynamic analysis method, the feasibility of two types of biogas power generation technologies is comprehensively evaluated from both environmental and economic aspects. The feasibility of this technology is compared with that of coal-fired power generation technology, and the feasibility of straw biogas power generation technology in both economic and environmental aspects is discussed. In the feasibility analysis of environmental benefits, three potential values of environmental impact categories are considered: global warming (GWP), environmental acidification (AP) and human toxicity (HTP). The environmental impact potential of the three power generation technologies is calculated according to the equivalence factor of each environmental category. After the environmental impact potentials are standardized, the total environmental impact loads of different environmental categories are obtained. The analysis of the total environmental impact is consistent with the judgment of the environmental benefits of the three power generation technologies. The economic feasibility analysis adopts the dynamic analysis method of time value, and selects the dynamic investment payback period, internal rate of return and net present value as the analysis indicators. According to literature review, find representative power plants, and calculate dynamic payback period, net present value and internal rate of return by referring to capital input and output data of power plants. According to the calculation results, the economic feasibility of different power generation technologies is comprehensively analyzed. The results show that the biogas fuel cell power generation technology is the best in terms of total environmental impact, and the total environmental impact load is 8.55×10-4, followed by biogas direct combustion power generation technology, with a total environmental impact load of 2.15×10-2。 Compared with coal-fired power generation technology (2.97×10-1), the emission reduction rate reached 99.71% and 92.76% respectively. In terms of economic benefits, when the dynamic payback period and NPV are taken as indicators, the payback period of the straw biogas direct fired power generation project is the shortest (12.03 years), the NPV in the operation period can reach 1 361 246 Yuan/MW, and the economic benefits are the best; The second is coal-fired power generation project (14.5 years), with a net present value of 423 933 Yuan/MW; The dynamic payback period of biogas fuel cell power generation project is more than 20 years, and there is no surplus during operation. Therefore, compared with biogas fuel cell power generation technology, biogas direct combustion power generation technology has more significant economic benefits. This shows that biogas direct fired power generation technology will remain one of the best power generation technologies to replace coal-fired power generation in the future. [ABSTRACT FROM AUTHOR]

Agriculture is crucial for economic development. Losses in agricultural production were caused by a variety of circumstances, but pests and illnesses are among the most important. The use of plant protection machinery to spray pesticides is still the most effective method of pest control at present. Traditional agricultural sprayers were inefficient and time-consuming, which caused pesticide waste and environmental contamination. In the process of spraying pesticides, farmers are directly exposed to pesticides, which is easy to cause bodily harm or even poisoning. With the steady progress of China's agricultural modernization, robots are widely used in agricultural plant protection work. Intelligent pesticide spraying robots are an effective method to solve the problem of applying pesticides in complex environments such as hills, orchards, fields, and greenhouses, which is more efficient and accurate. Intelligent spraying robot not only saves labor but also reduces the improper use of resources and environmental pollution. It is conducive to our better reaching of the goal of agricultural sustainable development. In this study, the research progress analysis of an intelligent pesticide spraying robot focuses on four respects: mobile chassis design, spraying the device design, navigation technology, and target detection technology. This paper discusses the factors limiting the development of intelligent pesticide-spraying robots for the primary technologies applied to various operation scenarios. Firstly, the mobile chassis design of the spraying robot was analyzed from the ground spraying robot and aerial spraying robot. The study and development of wheel-track composite robot chassis can integrate the advantages of wheeled chassis as well as a tracked chassis, which will be the research trend of ground intelligent spraying robot. Plant protection UAV is unrestricted by terrain, and can be applied to a variety of scenarios, which will be the key orientations for future research. Secondly, the spray devices required by the spraying robot in different spraying scenarios were summarized. It mainly includes an adjustable boom sprayer device, electrostatic spraying device, targeted spraying device, air-assisted spraying equipment, and profile modeling spray equipment. The most commonly used navigation methods are analyzed, including Global Positioning System (GPS) navigation, visual navigation, inertial navigation, multi-sensor fusion navigation, laser radar navigation, odometer, geomagnetic navigation, etc. Additionally, the detection methods of various pesticide spraying robots are evaluated from the perspectives of crop detection and pest detection. The deep learning algorithm can automatically extract the image features of crops, make use of the information, and exactly identify the location of crop pests and diseases, to quickly respond to achieve accurate spraying. Finally, the development trend of intelligent pesticide application robots for precise application is presented. Six requirements or prospects were proposed for the intelligent pesticide spraying robot development in the future, including to improve the response speed of the spraying robot, to improve detection accuracy, to design lightweight chassis, to reduce the development cost of the spraying robot, and to integrated air-ground spraying technology. In conclusion, intelligent and precise application robots have the potential to significantly improve the quality of precision agriculture operations by facilitating intelligent decision-making on operational parameters before actual operation. [ABSTRACT FROM AUTHOR]

It is needed to solve the problems such as relatively low input-output ratio and environmental pollution for Chinese agriculture, with the large amount of agricultural production and consumption. In the background of changing international situation and frequent natural disasters, transforming traditional agricultural production methods in China is an urgent. Driven by emerging technologies such as artificial intelligence, internet of things, cloud platform, automatic control, and new generation communication and so on, precision agriculture came out and was undoubtedly an effective way. Precision agriculture has become a common choice for developing sustainable and high-yield agriculture around the world. In order to obtain the development orientation of precision agriculture and successful practices in the world, this paper reviews the studies on precision agriculture developing status. The aim of this paper is to refine the experiences of precision agriculture developing in the main developed countries and regions and take a look at the precision agriculture development in China. Adopting the method of systematic literature analyzing and summary, Section 1 studies the development status of precision agriculture in the main developed countries and regions, such as America, Japan, European Union and Israel. The idea of precision agriculture was first proposed in America. Until today, America has developed mature precision agriculture system, which benefits from the highly developed technologies. Considering the serious contradiction between large population and less farmland, during 1970s, Japan took measures of consolidating farmland on a large scale and building farmland infrastructure and so on to improve the agricultural production conditions. The agricultural community was also formed to operate collaboratively the agricultural production. The development of precision agriculture in European Union is driving by digital technologies. The water-saving agriculture represented by drip-irrigation and sprinkler-irrigation has made remarkable results in Israel. The development experiences of precision agriculture in the main developed countries and regions enlighten us that: 1) the leading by government is the key; 2) the informatization construction is the foundation; 3) the advanced technology is the core; 4) the cultivation of new type of farmers is the guarantee. Section 2 analyzed the basements and weaknesses for developing precision agriculture in China. The weaknesses are the emphasis in this section. First, the farmland in China is scattered and the infrastructure is not perfect. Taking the informatization perspective, even though number of agriculture related information systems exist, the data and information are not interoperable between these systems. Second, at the present stage, we cannot acquire the temporal and spatial continuous agricultural information due to the rarity domestic satellite data and ground sensors for agriculture monitoring. Third, automatic variable operating system and equipment are lacking since the technology integration of information technology, communication and agricultural machine has not been achieved. Fourth, insufficient high-quality agricultural talents. Facing these weakness and Chinese conditions, Section 3 provided five suggestions to develop precision agriculture in China. Firstly, our government should overall plan and give guarantee in police making, infrastructure construction and financial support, etc. Secondly, we should improve the agricultural production condition through expanding moderately the operating scale of farmland and constructing the field infrastructure net and the national agricultural information platform. Thirdly, the key technology research, such as the information retrieval using remote sensing and technology integration of communication, automatic controlling, spatial information and smart machinery must be focused. Fourthly, the new type of personnel in agricultural field can be cultivated. Fifthly, pilot demonstration can be carried out according to the regional difference. [ABSTRACT FROM AUTHOR]

The land consolidation project is one of the most important approaches to ensure national food and ecological security. An academic journal “Transactions of the Chinese Society of Agricultural Engineering” launched a column of “Land Consolidation Project” in 2002, in order to promote the research of land consolidation project. This column was renamed the “Land Resource Guarantee and National Land Ecological Security” from the 9th issue of May 2020, with the continuous expansion of research fields in the modern land consolidation project. In this study, the bibliometrics was utilized to statistically analyze the papers published in the “Land Consolidation Project” column of “Transactions of the Chinese Society of Agricultural Engineering” from 2002 to 2020. Great research progress was highlighted in the different research directions, and then the future focus was proposed in the field of land resource and national ecological security, with emphasis on China's strategy of food and ecological security. The results showed that the research directions of land consolidation project mainly included land use, land evaluation, agricultural land consolidation, cultivated land quality and safety, 3S and land information technology, industrial and mining wasteland reclamation, rural residential area consolidation, land ecology, land restoration, basic farmland construction and protection, land saving, rural spatial pattern and development, cultivated land development, as well as urban land consolidation. Furthermore, land evaluation, agricultural land consolidation, and cultivated land quality and safety had become hot topics, where the publications accounted for 10.52%, 10.16%, and 8.51%, respectively. 5-keyword clustering was formed, such as the land evaluation, agricultural land consolidation, cultivated land quality and safety, 3S and land information technology, as well as industrial and mining wasteland reclamation. Additionally, 10 groups of cooperation networks were formed in the leading research fields using the cooperation network of research authors generated by VOSviewer. More importantly, the published papers in the “Land Consolidation Project Column” had covered all directions of the land consolidation project. Ecological land consolidation and land-use security pattern were established in recent years, where the ecological effect of land consolidation was analyzed using the theory of landscape ecology. Moreover, many efforts have been made on the ecological design and restoration technology of single land consolidation project, together with the pattern evolution and layout optimization of rural residential areas. In the future, much more attention can be paid to the land resource security and national land ecological security, particularly to the theories and mechanisms in the “systematization, ecologicalization, informationization and intelligence” for the protection and restoration of the regional ecosystem, to realize “overall protection, unified restoration and comprehensive management” of “mountain-water-forest-field-lake-grass”. Consequently, the ecological security pattern of national land can be built, once the research on the intelligent management of one map of natural resources was implemented using the state-of-the-art big data in intelligent agriculture [ABSTRACT FROM AUTHOR]

Unmanned Aerial Vehicles (UAV) have widely been served as a new technology in agricultural aviation plant protection and pest control in China. However, it is highly demanded to improve the accuracy of UAV spraying pesticides and operational efficiency. In this study, a Variable Rate Application (VRA) of a centrifugal spraying system was designed for precise placement and timing of pesticide application in specific field conditions using the network Real-Time Kinematic (RTK) technology. STM32F103 single-chip microcomputer was used for the core controller. A serial port of controller was selected to obtain the global position system (GPS) information. A network modular Data Terminal Unit (DTU) was connected to realize the network RTK technology via the serial port of the controller. The control voltage was used to tailor the speeds of the centrifugal nozzle motor and peristaltic pump. A Pulse Width Modulation (PWM) was used to control the output voltage from the core controller to the armature of motors in this system. The speed of the centrifugal nozzle motor determined the output droplet size, while the speed of peristaltic pump determined the flow rate and amount of spray fog. The agricultural dataset before the system working was acquired using the airborne multispectral camera, ground object spectrometer, and handheld GPS. A prescription chart was also constructed using ArcGIS software. In the system working, the GPS modular was used to capture the location longitude and latitude data for the system to read and analyze. The system was always real-time searching the UAV geographical position during the spraying pesticides process using the GPS data, and then matching the position using the orthogonal grid. Meanwhile, the system was used to real-time tailor the changes in the duty cycle of output PWM, after matching the decision of the prescription map. The speeds of the centrifugal nozzle motor and the peristaltic pump were then to control the particle size and application amount of the UAV. The operation data was finally uploaded to the monitoring platform for real-time display and storage. Several spraying experiments were carried out in the research base of South China Agricultural University in Zengcheng City, Guangdong Province of China. The airborne spraying device was carried on the MG-1p plant protection UAV using a developed DJI Drone. The sampling points of droplets were set to match the planting density of crops, where the water-sensitive paper was used to collect the droplet data. After UAV operation, the water sensitive paper was collected into a plastic bag for later use. An hp4678 scanner was selected to map the collected water-sensitive paper after the experiment. A DepositScan software was utilized to analyze the water-sensitive paper in each sampling area after image acquisition. A detailed dataset was obtained, including the deposition amount, coverage density, and particle size of droplets. The data demonstrated that the accuracy of the device was within 0.6 m at the operating speed of 2 m/s. The application effect was finally stabilized within 2.2 m in the case of continuous operation. Particle size varied smoothly in the boundary area of prescription, as the rotating speed of the centrifugal nozzle increased. The findings can provide a sound basis for the improvement of variable application technology of plant protection UAV in precise agriculture. [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]

Cotton, one of the main commercial crops in the world, mostly distributes in several major growing regions, including Xinjiang of western China. An important renewable biomass resource, the cotton stalk has received most attention to serving as the poultry feed, paper making, environmental protection materials, and biomass briquette fuel. Particularly, the highly efficient recycling of cotton stalk can be widely expected to bring enormous economic and ecological benefits. However, most previous treatments are focused on pulverizing cotton stalks and returning to the field. A great challenge is still posed on the current pulling machines for cotton stalks, with emphasis on operational requirements, leakage, and breaking rate. In this study, a novel horizontal-roller cotton stalk pulling machine was proposed to efficiently implement the pulling of the whole cotton stalk after harvesting. The machine was mainly composed of traction, gearbox, stalk conveying, transmission system, machine body, road wheel, spacing regulating mechanism, stalk pulling, dam-board, and support frame. Specifically, the power input shaft of the gearbox was connected to the power output shaft of a tractor. In working, the power was transferred to the chain drive by the power output shaft of a gearbox, and then to realize the stalk conveying and pulling operation under the rotation of the toothed belt and the opposite rotation of the stalk pulling roller. A systematic kinematic analysis was conducted to determine the influencing factors in the working process. A field test was also carried out in a farmland in Korla City, Xinjiang Uygur Autonomous Region of China in October 2019. The soil firmness was 467 kPa, and the moisture content of the soil was 15%-20%, due to the perennial drought and little rain in the study area. The average height of cotton stalk was 700 mm, while, the plant spacing was 50 mm in a wide and narrow close planting mode. The power was from a CFD604A wheeled tractor with a calibrated power of 44.2 kW. The test was performed on the national standard of a harvester combine test(GB/T 8097-2008). A three-level quadratic regression orthogonal test was designed, where the forward velocity of the machine, the rod velocity of the deflector, and the speed of the stalk pulling roller were selected as the influencing factors, whereas, the leakage rate and plucking rate were the response factors. A response surface method was utilized to establish the regression equations for the relationship between the factors and assessment indexes. An optimal combination of parameters was obtained, while an experiment was also conducted to verify the mathematical model. The test results demonstrated that there were great effects of factors on the performance of horizontal-roller cotton stalk pulling. The significant effects on the leakage rate were ranked in a decreasing order: the forward velocity of the machine, the rod velocity of the deflector, and the speed of the stalk pulling roller. Correspondingly, the significant effects on the plucking rate were ranked in a decreasing order: the speed of the stalk pulling roller, the rod velocity of the deflector, and the forward velocity of the machine. The verification test indicated that the leakage rate of the cotton stalk was 5.24%, and the plucking rate was 3.75%,when the forward velocity of the machine was 0.68 m/s, the rod velocity of the deflector was 1.75 m/s, and the speed of the stalk pulling roller was 221 r/min. The optimal combination was better consistent with the predicted one in model optimization, indicating a reasonable structural design. The findings can provide a sound reference for the structural design and optimization of operation parameters in the horizontal-roller cotton stalk pulling machine. [ABSTRACT FROM AUTHOR]

The Diameter at Breast Height (DBH) (at a height of 1.3 m on the bole of a tree) has been one of the most important indicators during tree measurements in forestry resource inventory. However, the current DBH measurement cannot fully meet the requirement in recent years, due to the low portability, precision, efficiency, applicability, and stability, together with the complex operation, rudimentary software, high costs, and short range. In this study, an innovative device was developed to accurately, efficiently, and conveniently measure the tree DBH suitable for the complex tree shapes and the different diameter classes, while cost-saving in the office-field work survey. The specification of the device was as follows (size: 8.35 cm×5.80 cm×5.55 cm; weight: 230 g; resolution: 0.01 cm; linear range: 0-150 cm; battery capacity: 4 000 mAh input vatage: 3.7 V, output votuge: 5 V; micro-processor chip: STC15W4K48, 8 bits; encoder type: PD-1503-SDI, 12 bits). A Tunnel Magneto-Resistance (TMR) rotary encoder was also combined with the low-cost, small size, and light weight electro-mechanical structure, and high-resolution processing. As such, the measurement device was achieved in the electronization, digitization, portability, and integration of office and filed work for the tree DBH. A supporting system software was also developed, including the embedded software, mobile terminal application, and Web terminal application. In the process of an individual tree survey, the electro-mechanical structure of the device firstly converted the mechanical parameter of tree DBH to the magnetic signal, and then the magnetic signal was converted to an electrical signal. Secondly, the electrical signal was converted into the DBH measurement data using the processing integrated into the embedded software. Thirdly, the operation flow was better applied to measure the trees with special shapes and large diameters using multi-function key combinations. After all individual tree surveys, the DBH measurement data was transmitted by Bluetooth in the device to the Android application, and then uploaded to the database managed by the Web application. The measurement accuracy and operation efficiency of the device were verified to select the 196 standing trees with many tree species and a small sample plot of 42 standing trees in the Botanic Garden of Beijing Forestry University, China. The test results showed that the device presented a higher accuracy to measure the standing trees of different diameter classes than before. The total tree DBH measurement data from different diameter classes (weight: 1 092 g; resolution: 0.001 cm; linear range: 0-500 cm) indicated the mean absolute error (MAE) of 0.08 cm, Mean Absolute Percentage Error (MAPE) of 0.37%, Root Mean Square Error (RMSE) of 0.12 cm, and Relative Root Mean Square Error (RRMSE) of 0.54%, compared with an electronic draw-wire displacement sensor. In addition, a high measurement efficiency was achieved, where the average measurement time per person of each tree was 9.3 s from the efficiency test. The devices demonstrated nearly two times faster than the traditional diameter tape (weight: 42 g; resolution: 0.01 cm; linear range: 0-200 cm), while one time faster than the electronic draw-wire displacement sensor. Additionally, the price of the device was only 260 RMB, due to a 12 bits encoder (price: 135 RMB). In conclusion, this device behaved at a low cost and less labor consumption, fully meeting the technical requirement of accuracy for the Continuous Forest Inventory (CFI) in China. Therefore, the finding can provide broad application prospects in forestry resource inventory. [ABSTRACT FROM AUTHOR]

China is the major producer and consumer of pork all around the world. In China, pork production has accounted for more than 60% of meat production for a long time. Nowadays, the pig industry has gradually shifted from decentralized and extensive breeding to intensive large-scale breeding, promoting production efficiency. At present, as people's demand for the quantity and quality of pork is increasing, China's pig industry faces the problem that the output and quality of pork can not meet people's daily needs. With the rise of artificial intelligence technology in recent years, deep learning technology has been developed rapidly and widely used in image and audio recognition, natural language processing, robotics, bioinformatics, chemistry, finance, and other fields. It is also an essential tool in developing precision livestock farming. The body condition, behavior and health status of pigs could directly affect the income level of pig farms, so through using deep learning technology, we can quickly and accurately acquire the relevant information about pigs, and carry out precise management to improve the feeding efficiency and welfare levels of pigs. This paper expounds on the research progress and application status of deep learning technology used in target pig detection, pig image segmentation, pig body condition and abnormal monitoring, as well as pig behavior recognition. Then we put forward the improvement strategy of deep learning technology used in the process of pig feeding, which make it easier for researchers to understand. At the same time, we summarize and analyze the data sources and datasets, application scope, and model optimization of previous works using deep learning technology in pig breeding. In the field of data sources and datasets, mobile computer vision systems are currently more suitable than systems with many fixed cameras when they are applied in pig houses, therefore, further research could focus on how to use deep learning technology to mobile computer vision systems. Deep learning technology requires a large amount of data to learn data features, which is a massive disadvantage for pig applications. To get pre-training weights suitable for agricultural data sets, a large number of public datasets and a unified dataset standard suited to the pig field should be established. In terms of application scope, due to the short application time of deep learning in the process of raising pigs, many critical occasions are not involved or seldom involved in existing research, so the application scope of deep learning should further expand. In model optimization, optimizing the model to meet the needs of practical application scenarios is the direction of future research. Optimizing the model to achieve a better balance between size and model performance requires further study. Optimizing the model to locate the start and end time of the behavior in unclipped video and recognize the behavior of target pigs is the challenge in identifying the behavior of pigs in future. China's research on deep learning is at the top level, so the application prospect of deep learning in pig farming is highly expected. Combined with the actual production scene of pigs, deep learning technology will significantly contribute to the development of precision livestock farming. [ABSTRACT FROM AUTHOR]

Landscape patterns have been integrated into the crop planting process, thereby developing the potential ornamental value of field crops, such as rape and wheat. A seed tape-weaving machine can be used to knit the seeds of crops into a specific paper tape for mechanized or ornamental planting. In this machine, the seeds are sucked into the paper tape at a constant speed via a vacuum pump, where the paper tape is bound together with biodegradable cotton thread. In this study, an improved weaving machine of seed tape was designed to mix the rape-wheat seeds for a landscape. The pattern automatically realized the regular arrangement of rape and wheat seeds in the seed tape. The key components were also designed for the typical weaving process of mixed seeds, including the air-suction seed-metering device and seed guiding tubes. Taking the commercialized rape seeds of Zhongshuang No.9 and wheat seeds of Zhengmai No.9023 as the test objects, four types of experiments were conducted: the seed metering performance test, the paper feeding accuracy test, the pattern weaving performance test, and the field test. The structural and operating parameters were also optimized for the better weaving effect in the improved weaving machine of seed tape. In the seed metering performance, the results showed that the main influencing factors were the negative air pressure, followed by the diameter of suction holes, and the motor speed in the air-suction type seed metering device. In rape seeds, the air-suction type seed metering device worked on the condition with the negative air pressure of 2 500 Pa, the suction hole with a diameter of 1.2 mm, and the motor speed of 3 r/min. In wheat seeds, the better seeding performance was achieved, where the airflow negative pressure of 2 500 Pa, the suction hole with the length of 3.9 mm×1.9 mm, and the motor speed of 3 r/min. Specifically, the seeding qualification rate was 94.1% and 92.2%, the multiple rates were 1.8% and 3.1%, and the miss seeding rates were 4.1% and 4.7%, for the rape and wheat seeds, respectively, indicating that both seed metering devices achieved the best seeding performance. The weaving performance test showed that: i) There were good uniformity and even quality of paper feeding, where the variation coefficient of plant spacing was less than 6%; ii) When the total number of weaving points gradually increased in the range of 100 to 900, the variation coefficient of relative position in the pattern decreased first, then stabilized, and finally stabilized at about 17%; iii) The variation coefficient of weaving area first decreased and then stabilized, and finally stabilized at about 8%; iv) The accuracy of pattern weaving gradually increased, and then stabilized. The field test was performed on a 30×30 size pattern of five points star in a square. The results showed that the variation coefficient of relative position in the pattern was 18.26%, and the variation coefficient of weaving area was 10.87%. A better visual effect was achieved in the formed pattern. The improved weaving machine can be expected to improve the work efficiency, while reducing labor intensity and error probability, for the mechanized planting of field crops in landscape patterns. The findings can provide a new idea and solution for the modeling and implementation of landscape patterns with field crops, like rape and wheat, further to promote the development of rural tourism in China. [ABSTRACT FROM AUTHOR]

Improving root structure of crops is an effective way to solve the conflict between food production and environment. However, traditional root research methods (such as excavation) are time-consuming, labor-intensive, destroying the in-situ state of roots and point based, which make them difficult to meet the requirements to obtain root information for cultivation and breeding. Therefore, it is urgent to develop in situ non-destructive method for detecting the root. While, some progress has been made in the non-invasive detection of roots in developed countries, the related research is limited in China. Hence, this paper summarized the research status of in situ root non-destructive detection technology and then took the ground penetrating radar and electric capacitance method as examples, which can detect crop root in field non-invasively, to systematically review the principles, applications, unsolved questions and future research focus. Both ground penetrating radar and electrical capacitance can use linear models to predict root size (such as root length, diameter and biomass etc). Besides that, ground penetrating radar can also measure root parameters by nonlinear model and forward model. However, ground penetrating radar was extensively used to measure the coarse root not in fine root detection. So far, there is limited literature to summarize the model for ground penetrating radar to predict crop root parameters. As contrast, electrical capacitance method was widely used to measure crop roots. But in recent years, it was questioned that the feasibility of measuring root, which mainly consists of two aspects: as the leakage of electric current from the near root base, root system can't be detected; the stem and root system form a series circuit with the growth medium as the boundary, In the series circuit, the value of the capacitor is mainly determined by the value of the smaller capacitor, because the capacitance of the stem is less than that of the root, so the value measured by the capacitance method reflects the information of the interface between the stem and the substrate. Therefore, this paper focuses on: (1) the principle of ground penetrating radar and electrical capacitance for phenotyping roots and the summary as well as comparison of models for predicting root parameters; (2) the applications of ground penetrating radar and electric capacitance for measuring root system, analysis of main influencing factors for measuring root system and particular discussion about the electric capacitance feasibility in detecting roots; (3) the comparison between ground penetrating radar and electrical capacitance. The main focus of future research is to improve the accuracy of ground penetrating radar measurement of crop roots and to verify the feasibility of electrical capacitance method for root measurement. Hence, four suggestions were made for the future development: (1) improving the accuracy of ground penetrating radar in detecting crop roots; (2) clarifying the principle of electrical capacitance to detect root system; (3) measuring more root traits; (4) considering the knowledge of physics, mathematics, plant physiology, breeding and other related subjects in application. Furthermore, as the spatial variation of soil water moisture is consistent with the distribution of root system, rapid monitoring the spatial changes in soil moisture by ground penetrating radar and electrical resistivity tomography may provide information of root distribution. Therefore, this paper also briefly reviews the application of these two techniques in soil moisture detection. Overall, this review aims to provide important references for domestic researchers. [ABSTRACT FROM AUTHOR]

Cotton is an important strategic material. With the increase of cotton planting costs, improving the level of mechanized harvesting has become an important way to improve the economic benefits of cotton planting. The main cotton harvesting machinery used in China is the horizontal spindle type cotton picker. In the process of production practice, the domestic cotton pickers have problems during high-speed operation, such as improper matching of picking speed ratio coefficient, badly gear worn and poor reliability of picking head transmission system. In view of the above problems, this paper optimized the transmission system of picking head based on the comprehensively consideration of the operating speed, transmission system reliability, operation quality and other factors, aiming to increase the operating speed of the cotton picker, improve the reliability of the picking head transmission system and the operation quality of picking head. According to the structure and working principle of the horizontal spindle type cotton picking head, the transmission route and transmission ratio of picking head transmission system of cotton picker were analyzed and calculated firstly. Then, the picking mechanism and picking conditions, such as the range of picking speed ratio coefficient of cotton picker, the actual number of turns needed to pick cotton petals and the picking time of spindle, were determined through virtual simulation technology and theoretical analysis and calculation. Meanwhile, the roller power gear in the transmission system of the picking head was selected as the optimization object, the tooth number of roller power gear, modification coefficient of the upper gear on clutch, modification coefficient of roller power gear and addendum height coefficient were selected as design variables, and the objective function and constraint conditions were established. The Genetic algorithm and 1stOpt software were used to optimize the transmission system of picking head. The optimization results were as follows: the number of teeth for the roller power gear was 72, the modification coefficient of the upper gear on the clutch was -0.14, the gear modification coefficient for the roller was 1.208, and the addendum height coefficient was 1.25. A cotton picking performance test bench was built combining the operation requirements of the cotton picker. The operation performance of picking head before and after optimization was verified on the test bench with the factors as follows: picking roller speed was 113-143 r/min, the operation speed was 5.93-7.20 km/h. The results showed that the working speed of the picking head was increased from 6.4 to 7.2 km/h, increased by 3.6%, and the work efficiency increased from 4.86 to 5.47 hm²/h, increased by 12.5%. Under the working speed of 7.2 km/h, compared with before optimization, the collection rate increased from 90.4% to 93.7%, increased by 3.6%, and the impurity rate decreased from 10.28% to 9.72% and decreased by 5.4%, which verified the rationality of the optimization of the picking head transmission system in this paper. The study can provide a reference for the development of picking head of cotton picker. [ABSTRACT FROM AUTHOR]

Agriculture and rural development in China have entered a new stage with the rapid globalization, urbanization, and the shift in consumer demand. A new style of consumption is forming the value of rural diversification. In order to promote the rural reform and modern agriculture, the rural revitalization and urban-rural integration, a Rural Revitalization Strategy has been released at the 19th National Congress of the Communist Party of China, particularly on a series of policies, such as the Rural Revitalization Strategy Plan (2018-2022), the active use of idle homesteads and housing bases. To revitalize countryside, the diversification of rural functions is becoming a new topic of rural space research in China. There are diversified research trends in previous studies on rural space, such as multi-functional transformation, rural revitalization, and rural space commercialization, social and cultural differentiation. However, most research interests are still focused on the new rural construction, such as hollow village, rural renovation, possibly due to the insight was confined by the urbanization process and the stage of rural development in China. The further explore is also lacking in consumption-oriented modern leisure for the rural functions. In the counter-urbanization of developed countries, the diversification rural space has become hot research directions, such as urban-rural migration, consumption of rural areas. In this paper, the combination of conventional reading method and knowledge mapping analysis in CiteSpace document analysis software was used to sort out the research context of international rural spatial diversification, and then to identify research hot spots, finally to extract the explanation of research topics. The results show that (1) international rural space has undergone a series of transitions from rural production relations, rural reconstruction, rurality to rural functions transformation, urban-rural integration, social policy changes, continuous resource management to urban-rural immigration, consumption differences, rural space reproduction, and rural gentrification. The attention and its intensity on diversification research are increasing rapidly, while the research focus and hotspots are constantly updated. The degree of diversified research attention has increased rapidly. (2) In recent years, the research results and influence of developing countries represented by China have been growing rapidly, and the overall research shows a spatial pattern of "Western Europe as the core, North America and Asia as the two wings". (3) Five topics, including rurality, rural function transformation, rural space reproduction, urban-rural immigration, rural gentrification, have dominated the current international rural spatial diversification research. Compared with international research experience, this paper proposed that the future strength can be focused on the theoretical system of rural spatial diversification in China, the process and mechanism analysis, and micro analysis, thereby to provide valuable reference for further research on rural revitalization. [ABSTRACT FROM AUTHOR]

In north China, the ploughing operation of high-power tractor based on electro-hydraulic suspension system is the most common and important agricultural process in the field agricultural production. Due to the complex field working environment, the change of tillage depth and the fluctuation of soil specific resistance, the working load of tractor unit fluctuates greatly during ploughing operation, which is easy to cause excessive sliding of driving wheel， and seriously affects the traction efficiency and traction of the operation unit. In order to solve the problem of excessive driving wheel slip of high-power tractor for ploughing, taking the high-power tractor ploughing unit with electro-hydraulic hitch system as the research object, a sliding rate control method based on sliding mode variable structure control was proposed this paper. Firstly, in view of the strong nonlinear characteristics of the complex system of "tractor-farm tools-soil", the nonlinear dynamics model of tractor driving wheel sliding for ploughing was established based on tractor motion characteristics and the theories of vehicle dynamics. Then, the exponential reaching law was used to design the sliding rate nonlinear control algorithm based on sliding mode variable structure control theory. Especially, taking the hydraulic pressure of hydraulic cylinder as the equivalent control quantity, the control law of sliding mode variable structure control was derived after simplifying the hydraulic system. Through MATLAB/Simulink simulation, the reliability of the nonlinear dynamic model and control algorithm in the step change of soil specific resistance was verified. According to the soil data obtained from a specific site, the soil specific resistance was set as pulse signal, and the stable value was 30 000 N/m². At the beginning of the simulation, a soil specific resistance with an amplitude of 8 000 N/m², a period of 10 s and a duty cycle of 50% was added to block the impulse signal. The results showed that the slip rate of the driving wheel was always near the sliding surface, the steady-state error was 0.002, and the control overshoot was 0.008. Furthermore, the field test platform for automatic slip rate control system was built on Lovol-TG1254 tractor, and the field comparison tests between SMVSC control and Fuzzy PID control were carried out under the tractor speed of 2.17 m/s. The test results showed that compared with the fuzzy PID control, the mean absolute deviation of slip rate under the SMVSC control decreased by 27%, the maximum deviation decreased by about 49%, and the fluctuation range and control deviation of slip rate were smaller. The change of depth was 5.26 cm, which decreased by about 27% compared with that of the fuzzy PID control, the change of hydraulic cylinder displacement was 1.15 cm, which decreased by about 36%, and the adjustment change of traction was 1 293.35 N, which decreased by about 42%. The control deviation of the driving wheel sliding control method proposed in this paper was small, it can provide theoretical basis and technical support for improving the quality of ploughing operation. [ABSTRACT FROM AUTHOR]

Corn stalks have been traditionally disposed of by in-situ incineration or for the production of animal feed, due to the main crop residues in northeastern China. However, the conventional treatments of corn stalks have posed a great threat to the environment and resource utilization in recent years. Alternatively, biomass materials (corn stalks) can be widely expected to replace wood preparation in paper production. Different pretreatments can be utilized to improve the quality of pulp made from corn stover. The common-used pulping pretreatment can include various physical, chemical, and biological reactions. This study aims to explore the possibility and feasibility of a co-culture procedure of anaerobic microorganisms and yeast to pretreat the corn stalks. The culture medium was firstly prepared in the experiment, and then the resulting goat rumen fluid was filtered and centrifuged, where the centrifuged supernatant was used for the identification. After that, the supernatant of rumen fluid (anaerobic fungi: Pecoramyces sp.) and Saccharomyces cerevisiae S1145 were added to the medium for the simple co-culture. The components of the naturally air-dried corn stalks were separated, where the corn stalk husks were collected, crushed, and sieved, and the shredded husks (as a substrate) were added to the medium for the simple co-cultivation at 39°C for 72 hours. The results show that the Saccharomyces cerevisiae presented the ethanol in the metabolites of fermentation broth under the action of rumen fungi, indicating that the rumen fungi and yeast were co-cultured in vitro. The content of Saccharomyces cerevisiae was greatly contributed to the metabolism. The ethanol content in the product reached the maximum when adding 5ml of Saccharomyces cerevisiae, accounting for 32.09% of the total metabolite content. The ethanol content was increased by 23.04 percentage points with Saccharomyces cerevisiae, compared with the control without. The co-culture process of anaerobic fungi and Saccharomyces cerevisiae was utilized to pretreat the corn stalk bark, where the Saccharomyces cerevisiae was improved the ethanol production. The enzyme preparation was normally used to enzymatically hydrolyze plant cellulose in the conventional second-generation cellulosic ethanol production. Nevertheless, the enzyme preparation cannot be reused during processing, leading to the high production cost of cellulosic ethanol. Taking the rumen of ruminants as a bionic object, the living environment of anaerobic microorganisms was simulated in vitro to create the conditions for the sustainable production of cellulosic ethanol. Consequently, this experiment provided a new way to treat the corn stalks. The corn stalks after biological treatment can be used to produce the biomass pulp. The experiments have verified that the rumen anaerobic microorganisms and Saccharomyces cerevisiae can self-reproduce the corn in an artificial biomimetic environment, indicating the feasibility of straw to produce ethanol. The treatment and reuse of corn stalks can greatly contribute to the economic benefits of corn stalk pulping, while reducing the overall cost consumption for the high resource utilization. [ABSTRACT FROM AUTHOR]

High-clearance plant protection machine plays an important role in the large-scale chemical fertilizer spraying machinery in China. The wheels of high-clearance plant protection machine must be driven along the ridge during the working process. However, the driver's vision is blocked by corn plants, which is easy to cause corn seedlings damaged by tires. In view of the serious phenomenon of seedling injury during the operation of high-clearance plant protection machine, a method of real-time extraction of navigation line between the corn rows based on a dynamic Region of Interest (ROI) was proposed in this paper. According to the different growing periods of corn, the videos were collected when the average height of corn plant was 30, 50 and 70 cm under different light conditions. Through reducing the influence of light by pixel normalization, segmenting the image of corn and background by green image processing algorithm and the maximum class square error method, the images were enhanced and removed by morphological processing. Firstly, the collected image was divided into 10 image bands, and each image band was processed by vertical projection method to locate the center lines between crop rows in the first frame of the video. The approximate position of the static ROI was determined and marked based on the perspective principle of camera and geometric information of the corn seedling belts. It took 473.7 ms to divide the static ROI, which does not affect the real-time performance of navigation since the determined of static ROI was prior to the navigation operation. Secondly, the static ROI was applied in the second frame of video, in which the navigation line between the corn rows was obtained by sub-regional feature points clustering algorithm. According to the geometric information of navigation line and ROI, the ROI was updated and optimized. Then the updated ROI was applied to the navigation line extraction of the next video frame. 225 consecutive videos were selected to divide the ROI manually, and the dynamic ROI obtained by proposed method was compared with the artificial ROI. The pixel deviation between the artificial ROI and the ROI was about 10 pixels, which shown that the algorithm had good convergence and met the requirements of navigation accuracy. Finally, a comparative experiment of artificial navigation line extraction and the algorithm in this paper by randomly selecting 100 frames of image. The results showed that the algorithm proposed by this paper could automatically obtain the dynamic ROI, the average error of navigation line extraction between manual and algorithm in this paper was 1.157°, and the accuracy rate of corn seedling belt recognitionwas 96%, and the average processing time of a real-time image with a resolution of 1 920 pixels×1 080 pixels was 97.56 ms. July 16, 2019, the navigation experiment was carried out in corn field, and the heading angle was used as the input signal of the automatic steering control system. The results showed that the wheels of high-clearance plant protection machine walked along the corn rows, and the wheel angle floated up and down at 0°. The algorithm proposed in this paper can meet the accuracy and real-time requirements of the automatic walking for high-clearance plant protection machine in corn. [ABSTRACT FROM AUTHOR]

Modern mechanical equipment is very important to agricultural production. The introduction of modern machinery and equipment into the production process of traditional Chinese medicine is an effective way to solve the contradiction between the expansion of production scale of traditional Chinese medicine industry and the reduction of labor force. The mechanization development of traditional Chinese medicinal materials production is in the initial stage. The main goal at this stage is to realize the "from scratch" of the relevant technical equipments. However, due to the varieties of traditional Chinese medicine, complex production process, regional differences and other factors, it is difficult to judge the demand for mechanized production of traditional Chinese medicine and lack of methods. How to evaluate and analyze the the differences in the demand for mechanized development is of great significance to the research of technical equipment, the implementation of supply side reform and the promotion of the production and development of traditional Chinese medicine. According to the characteristics of traditional Chinese medicinal materials production, combined with the analysis of degree of mechanized operation, status of technology and equipment and levels of user demand, this paper constructs the evaluation index system for the development of technical and equipment of traditional Chinese medicinal materials production. The degree of mechanized operation indicates the ratio of mechanized operation area to the total planting area. The status of technology and equipment is alculated by weighting the five indexes of advance ment, economy, applicability, reliability and security. The levels of user demand is divided according to the proportion of users with demand, users with demand but no machinery available and the proportion of users with demand in different production process. Then an evaluation model combined with entropy weight method and hierarchical cluster analysis method is formed, and after classifying by the hierarchical cluster analysis method, the model is expressed functionally based on the Fisher discriminant method. In empirical research, the demonstration base of national comprehensive experimental station of traditional Chinese medicinal materials is selected as the research object, eight production processes of sowing, transplanting, fertilization, intertillage, plant protection, harvesting, cleaning and drying are selected for evaluation Through the investigation in 23 provinces of China, the production processes of traditional Chinese medicinal materials production are categorized into three types. The harvest, intertillage, and transplanting belonged to the type A, which have the highest demand level. The seeding is classified as type B, and the drying, cleaning, plants protection and fertilization are type C. The phenomenons of “no machinery available” and “unsuitable to use” are obvious for type A, and there is an urgent demand for the development of technology and equipment, the evaluation results are consistent with the investigation results. According to the further calculation results based on discriminant Function I, the central values of type A, type B and type C are -2.868, 1.904 and 1.675 respectively, which shows that the evaluation model of development demands classification can be accurately expressed by quantitative mathematical functions. The machinery of the type A production processes represented by harvest should be developed in priority in traditional Chinese medicinal materials production. The research and development of special machinery for the production of traditional Chinese medicinal materials should take the road of combining independent innovation research with the introduction of other main grain production machinery. The model proposed in this paper reflects the reasons and details at the same time of forming classification, which can provide reference for the development demand evaluation of other crops or regional agricultural machinery technology and equipment with backward mechanization development. [ABSTRACT FROM AUTHOR]

With the implementation of clean energy heating project in rural areas of northern China, the pollution of coal-fired heating in winter has been greatly improved. However, the use of large-scale electric heating equipment put forward new challenges to the power supply reliability of low-voltage distribution network. Especially in rural power grid, the load is heavy in winter and low in other seasons. It is one of the effective measures to achieve optimal resource allocation and improve the power supply quality of the distribution grid to exploit the demand response potentialities of electric heating loads, and motivate electric heating loads to actively respond to demand response programs (DRP) for peak-load shifting. Therefore, a load optimal control strategy for rural electric heating equipments based on demand side peak load regulation was proposed in this paper. A market transaction model was designed for third-party agency companies to represent coal-to-electricity users in the peak shaving market. The agency company made the centrally control strategies of electric heating users’ equipment according to the peak shaving volume and corresponding price obtained from the peak shaving market bidding. The electric heating users were classified based on the controllability of each user by the agency company. Each kinds of users could get different compensation price to encourage them to participate in the demand response programs for peak-load shifting. In this market model, a multi-objective optimization model was established to control the users’ air source heat pump. The goals of the optimization model were to meet the user's temperature demands to the maximum extent and to maximize the benefit of the agent company. Meanwhile, user's comfort requirements for indoor temperature were considered in this model, and the user classification compensation mechanism was introduced to improve the user's initiative to participate in peak load regulation. Taking the load data of electric heating users in Pinggu District of Beijing as an example, the simulation analysis was carried out. The results show that the total load reduction of all electric heating equipment was 159.773 kWh, there was no over-control for anyone user, the load reduction of each user fluctuated around average reduction of 7.989 kWh, the peak valley of the user's power consumption curve was changed, the optimal control strategy proposed in this paper played the role of peak load reduction and valley filling, which can relieve the pressure of the upper power grid during peak load period. The indoor temperature of the users was (18±1) ℃, which meet the demand of comfortable temperature for heating in winter. Compared with the target of not considering the benefit, the one-day compensation cost of the agency company was saved 31.9%, and the users with the highest degree of control got the most compensation income, the peak load regulation strategy could encourage the users to participate in the peak load regulation actively. [ABSTRACT FROM AUTHOR]

Pomegranates are one of the economic fruits in China. The timely detection of pomegranate diseases and the corresponding preventive measures are important to increase crop yields and reduce economic losses. To tackle the issues that traditional edge detection operators usually resulted in low accuracy of the detection of pomegranate diseases and its contour, low anti-noise capability, and created false edges, this study presented an improved Prewitt operator with an adaptive threshold. Firstly, in the image pre-processing stage, the pending image was enhanced by high-frequency emphasize filter, and the high-frequency component, which represented to the details of the pomegranate sample in the image, was increased by the filter. On the contrary, the low-frequency component, which represented to the background of the pomegranate sample, was attenuated to facilitate the following image processing. Since the most original images contained the Gaussian noise, bilateral filtering was used to process the noise present in the image. The weighted average of the brightness values of adjacent pixels was used to represent the intensity of a pixel. The weighted average method was used based on Gaussian distribution. The weight calculation took into account both the Euclidean distance between the pixels and the radiation difference in the pixel range domain to better maintain edge feature information. Secondly, a fifth-order convolutional mask was proposed. The weights of the elements in the mask were set according to the properties of the Gaussian noise probability distribution to reduce the effect of noise on the algorithm. The weight of the central element of the convolutional mask was increased so that the edge information of the image had higher contrast. In terms of gradient calculation, eight direction templates were used to perform the convolutional operation of the image, then the gradient values of each direction were calculated. After that, the corresponding gradient values were obtained, and the gradient values of eight directions were combined into eight groups according to the rule of orthogonality. As a result, there was 90 degrees difference between each group of gradients. Then calculated the L2 norm of each set of gradients, and used the largest value of L2 norm as the gradient of the current pixel. It was shown that it was only necessary to calculate the convolutions in half the direction due to the convolutional results in opposite directions were inverse to each other. The gradients of the rest of the direction could be obtained by its symmetric property. The adaptive threshold was implemented through the minimum error method to decrease the probability of false detection and prune irrelevant details. The mean and variance of the target and background were calculated, meanwhile, the minimum error objective function was obtained according to the principle of the minimum error classification. The value that minimizes the objective function was taken as the optimal threshold. To demonstrate the effectiveness of the method in this paper, 607 test images were manually collected as samples in the natural environment from different angles and different illumination conditions. To further reduce the interference of light changes and suppress background noise, the pending images were converted into grayscale images. Therefore, the algorithm was tested using the converted grayscale images. The experimental results showed that the algorithm proposed in this study achieved a better definition at the edge of the lesion. Compared with the traditional edge detection operator, it achieved a higher recognition accuracy and lower running time. The peak signal to noise ratio of the obtained image was higher, and the obtained edge was complete and accurate. The algorithm proposed in this paper could quickly and accurately detect the area of pomegranate lesions, providing a fundamental reference for the future prevention of pomegranate diseases. [ABSTRACT FROM AUTHOR]

Rational construction of a well-facilitated farmland become necessary for food security and modern agriculture in China. In farmland construction, the automatic management of spatial data can benefit to accurately distinguish well-facilitated farmland from the various land types. Various discriminating ways of well-facilitated farmland are adopted due to the different influence factors of agricultural production in in different regions, where the spatial distribution and structural features of well-facilitated farmland are quite different from place to place across the country. Most of the previous studies focus mainly on policies, benefit evaluation, preliminary planning and design in the well-facilitated farmland construction. There is still lacking on the studies of the discrimination and analysis for the regional structural features of the well-facilitated farmland. In this paper, a framework of an index system was constructed to identify the spatial distribution and structural features of the well-facilitated farmland using the law of spatial differentiation together with the related national standards and strategic planning, ranging from the scale and shape of farmlands, irrigation and drainage facilities, traffic accessibility, and farmland protection ratio. The identifying system was designed on the basis of the index framework with C#. NET and Arc Object. Subsequently, the proposed system was verified for its availability by taking a case study of a Loess Plateau and a southern mountainous region. The results were as follows: (1) In the Loess Plateau area, the standard rate of the farmland scale, farmland shape, irrigation and drainage facilities, traffic accessibility was 87.01%, 83.12%, 80.52%, 90.91% and 83.12%, respectively. The well-facilitated farmland area can be identified by the system was 38.33 hm² with the total discriminating precision was 94.38%. There were some farmlands that did not meet the requirements of the well-facilitated farmland, such as incomplete irrigation and drainage facilities, the irregular shapes of the fields that distributed in the branch furrow and furrow head around the farmland. (2) In the southern mountainous area, the standard rate of all spatial features was 100%. The well-facilitated farmland area that identified by the system was 30.07 hm², which was 10.34 hm² higher than that of the state-approved well-facilitated farmland. The high identified areas can be because some fields that meet the requirements of well-facilitated farmland have not been classed as the permanent basic farmland in some administrative regions. When regardless of this classification, the total discrimination precision was 100%. This index system can be used in different scenarios, such as macro monitoring and evaluation, project design and inspection of the well-facilitated farmland. This system was also applied for the Northeast Plain, North China Plain, Loess Plateau and southern mountainous regions, while the key elements of the spatial features of well-facilitated farmland construction can be detected with a reliable discriminant resolution. When combining with the remote sensing technology, the index system can help automatic management to know the real-time spatial data of well-facilitated farmland construction. Therefore, the developed system can be successfully applied to identify the extract well-facilitated farmland in the construction area, and then to analyze the obtained spatial data in real time, finally to implement automatic management for well-facilitated farmland construction. Furthermore, the proposed system in this paper can offer a promising reference to the current comprehensive supervision platform, and improve the management effectiveness of well-facilitated farmland construction in modern agriculture. [ABSTRACT FROM AUTHOR]

Dividing farmland into different zones for facilitating management (management zone) at regional scales can help improve agricultural production in reforming agricultural technology implementation in China. Improving detailed prescription of the management zone division can provide guidance to farming and service optimization at regional scale.Appropriately selecting indexes in management zones can reduce the required data and can thus subsequently improve management.Available index selection usually relies on empirical knowledge of experts and /or multivariate statistical analysis. However, expert evaluation method could be bias, while the multivariate statistical analysis method cannot reduce the number of indexes compared to the original index set and thus need to supervise the data. In addition, most existing work on fragmentation of management zones focused on zone-dividing method rather than from index selection by removing indexes that lead to fragmentation. This paper aims to resolve these limitations with a proposed unsupervised filtering index selection method, based on the index correlation clustering (FSCC) using the concept of feature selection. FSCC reduces the original index set to obtain a subset called FSCC set. FSCC applies the correlation matrix of all indexes to cluster the original indexes set. It then selects all cluster centers as a representatives to form a new index subset as the FSCC set. The quantity of the indexes in the FSCC set was reduced,compared to the original index set, and the redundancy of the indices set was descended. To improve practical operability of the management zones, we applied the index optimization algorithm developed based on the consistency and integrity (CIO) to the FSCC set to remove indices which resulted in fragmentation. CIO couples Kappa Coefficient with fragmentation index to generate an optimization strategy for the FSCC sets. CIO screens the indices which lead to the fragmentation while, in the meantime, considering the consistency of the management zone results prior to and after the optimization. We applied the method to winter wheat in China, with factors that affect wheat growth, including meteorology, soil and topography, being divided at four regional scales. We first used the FSCC and the two traditional filter feature selection methods, Variance and Laplacian Score, to select index subsets for the four scales, and compared the resultant management zones produced from them. The CIO was then applied to the four scales produced by the FSCC. The results showed that the FSCC method preserves the diversity of the features in the original index set. It significantly removed the redundant indices and had a better performance in the management zones. The best performance shows that in Rugao 2.5 km Grain, FSCC less than 52.44%, 49.52%, 49.45% both of Variance and Laplacian Score in FPI, MPE, NCE. The CIO improved the management zones effect of the FSCC index set, which reduced the number of indexes and effectively removed the indexes that led to a number of isolated units or patches. Compare to FSCC, except Nantong 10km, CIO has an average decrease in FPI, MPE, NCE of 0.061, 0.078, 0.082. Usingthe four regional scales, FSCC and CIO presented in this paper were effective in selecting indices and have potential application in management zone division. [ABSTRACT FROM AUTHOR]

There is a complex interaction mechanism between land intensive use and regional ecological efficiency, and research on their coupling coordination is of great significance to promote urban sustainable development and construction of ecological civilization. Based on the definition of land intensive use and regional ecological efficiency, this paper established an evaluation index system to measure land intensive use and regional ecological efficiency respectively. Firstly, the entropy weight method and the non-expected output super-efficient SBM model were employed to evaluate and measure the land intensive use degree and regional ecological efficiency of 284 prefecture-level cities from 2004 to 2016 in China respectively. Secondly, the coupling coordination degree model was adopted to evaluate their coordination degree, and the paper analyzed the spatial-temporal evolution characteristics of coupling coordination degree.The spatial auto-correlation method was employed to measure the spatial correlation pattern of the coupling coordination degree between intensive land use and regional ecological efficiency. The results showed that the coordination of land intensive use and regional ecological efficiency of prefecture-level city was in a mild imbalance stage at present in the whole, and the coupling coordination degree between the two increased over the time.The spatial distribution of the coordination between land intensive use and regional ecological efficiency showed a pattern of “higher in the mid and east, lower in the west”; and the spatial distribution of the coupling coordination degree between the two had little transformation over the time.The global spatial auto-correlation results showed that there was a significant positive correlation of the coupling coordination degree between land intensive use and regional ecological efficiency, and the correlation degree between the two increased first and then weakened over the time.The results of local spatial auto-correlation analysis showed that there were four types of the coordination spatial association between land intensive use and regional ecological efficiency, these were the spatial positive correlation type including high-high aggregation (HH) and low-low aggregation (LL) and the spatial negative correlation type including high-low aggregation (HL) and low-high aggregation (LH).The results showed that spatial positive correlation type of HH and LH were mainly distributed in the east, and the spatial negative correlation type of HL and LL were mainly distributed in the middle region,the types of HH,LH and LL emerged as the shape of cluster and always had a powerful agglomeration, and the LH type distributed discretely; except for the HL type, the overall pattern of the spatial distribution of the other types were stable over the time relatively and only the number increased or decreased partially. The major findings derived from the study can be summarized as follows: it is necessary to implement scientific environmental economic and environmental technology policies, strengthen differentiated monitoring and management of cities, carry out district management and control rationally and promote technical and innovation cooperation between cities. Only in this way, can we enhance the coordination of land intensive use and regional ecological efficiency, then promote the sustainable development of the cities. [ABSTRACT FROM AUTHOR]

Due to the shortage of water resources, serious water pollution, improper use of water and the occupation of agricultural water rights by other industries, China's agriculture will face the risk of water shortage in the future. Due to the amount of water resources in North China is relatively small compared with that in South China, coupled with extensive operating methods and the low level of agricultural irrigation technology, water resources are wasted seriously, the problem of agricultural water shortage in North China is more serious. Optimal allocation of water resources is one of the main measures to alleviate the shortage of agricultural water resources, and is an important means to achieve sustainable use of water resources. Accurate prediction of regional agricultural water consumption is the key to optimal allocation of water resources. Grey model is a method to study “poor information”, “small sample” and uncertainty problems, which is widely used in economics, finance and other fields. The amount of historical data of annual agricultural water consumption is not enough, which is affected by many factors, and has concussion. Therefore, it is suitable to use grey model to predict agricultural water consumption. The oscillation characteristics of agricultural water consumption data series have a certain impact on the prediction accuracy of the model. To resolve these problems, an improved fractional grey prediction model is proposed in this paper. Based on the monotonically decreasing non-negative series which transformed from the oscillation series of the agricultural water consumption, a multi-objective optimization model was constructed according to the two objective functions of “maximum (or minimum) order” and “the best fit of historical data”, which was solved by the improved non-dominated sorting genetic algorithm II (NSGA-II) method. Agricultural water consumption in the test set for the research areas of Tongliao city (42°15′N～45°59′N, 119°14′E～123°43′E), Ordos city (37°35′24″N～40°51′40″N, 106°42′40″E～111°27′20″E) of Inner Mongolia autonomous region and Baoji city(33°35′N-35°06′N,106°18′E-108°03′E) of Shaanxi province was predicted by the grey model (GM(1,1)) model of fractional order reverse accumulation, the order of which was optimized according to the results of the test set fitting. The average error of the prediction was 2.23%,1.77% and 0.31%, respectively. In order to test the performance of the model, the model proposed in this paper was compared with the traditional GM (1,1) model, traditional autoregressive model and the combined model based on the wavelet analysis theory respectively. Among them, the average prediction error of GM(1,1) model for the three research areas is 5.55%, failed detection, and 1.28%. The average prediction error of autoregressive model for the three research areas is 3.34%, 4.17% and 6.49%. The average prediction error of agricultural water consumption in Ordos City of Inner Mongolia Autonomous Region based on the combination model of wavelet analysis theory is 2.87%. The results show that compared with GM(1,1) model, the prediction effect of the model in this paper is better, which depends on the objective function of “the best fitting of historical data” and the objective function of “the largest (or the smallest) order” to reduce the learning degree of the model for noise, because the model in this paper transforms the oscillating data and reduces the uncertainty of the data, so compared with the autoregressive model without data processing, the model in this paper is less affected by data volatility. In this paper, the idea of fractional order “in between” is used to improve the traditional gray model with positive integer as order, which can effectively improve the accuracy of the model. At the same time, the method of reverse accumulation is used to increase the use of new data. On the whole, for the prediction of agricultural water consumption in all research areas, the model in this paper has the minimum error, strong generalization ability and certain practicability, which can provide a basis for the prediction of regional agricultural water consumption and the allocation of agricultural water resources in northern China. [ABSTRACT FROM AUTHOR]

Due to the climate change and human activities, the global ecosystem has changed significantly, which leads to the continuous decline of ecosystem resilience at the regional and even global scale and constrains the sustainable development of ecosystems. The question about how to maintain the sustainable development ability of ecosystem and reduce the influence of uncertainties has attracted extensive attention of scholars at home and abroad. A theory based on ecosystem resilience has provided a framework for solving these problems, but at present, the research of resilience is in the initial stage. Based on this, this paper takes the documents in CNKI database and Web of science database as samples. In CNKI database, the subject is “ecosystem resilience”, and in Web of science core database, the topic is “resilience” & “ecological system” or “marine ecological resilience” or “wetland ecological resilience” or “forest ecological resilience” or “grassland ecological resilience” or “desert ecological resilience” not “social-ecological system” not “urban system” not “community system”. The Histcite citation visualization software is used to select 40 papers with the highest local citation score (LCS), generating citation chronicles of foreign ecosystem resilience literature, with a time span of 1990-2019, so as to analyze the development of resilience research in foreign countries. In the analysis of domestic research hotspot trends, it is mainly to analyze the quantity of keywords appearing at different stages, and to study the evolution of resilience content. At the same time, this paper also uses VOSviewer data processing software to perform co-occurrence and cluster analysis on keywords, and generates a network map of keywords co-occurrence relationship to understand the main research direction of ecosystem resilience at home and abroad. The findings are as follows: 1) On the whole, the research on ecosystem resilience at home and abroad is on the rise in quantity, and the documents are mainly from the United States. The journals published in the field of ecosystem resilience research at home and abroad tend to focus on ecology and resources. Research institutions include comprehensive colleges, and the universities of mining, teacher education, academy of sciences, and some administrative institutions. 2) At the international level, the focus is different at different stages. Judging from the emergent words, the early stage focuses on biodiversity protection and ecosystem stability. After 2010, more attention is paid to the research of practical policies on the resilience of specific ecosystems. According to the results of citation analysis, resilience is researched from theoretical discussion to specific case modeling, and the research object extends from marine ecosystem to forest ecosystem. The results of co-occurrence analysis and cluster analysis of key words show that the research topics of international resilience focus on biodiversity, basic theory, policy management and the stability of marine ecosystem (especially coral reef). 3) Compared with other countries, China's resilience research starts late, and the research direction of ecosystem resilience in China mainly includes three aspects: land reclamation, land investigation and monitoring means, and research on influencing factors. In recent years, social ecosystem resilience, and sustainability and stability of ecosystem have become research hotspots. [ABSTRACT FROM AUTHOR]

In Xinjiang region of China, the grape cultivation area needs to take soil buried cold-proof operation in winter to make the vines safely overwinter. However, the single soil buried cold-proof operation brings great difficulties to the subsequent soil clearing operations, such as incomplete soil mechanical clearing and low operation efficiency. The vineyards headed by Xinjiang change the cold-proof mode, and the cold-proof cloth is used to assist in soil buried cold-proof operation, which can play a better effect of heat preservation and moisture conservation and provide the possibility for complete soil clearing. But at the same time, there are some problems such as difficulty in recycling cold-proof cloth. In view of the problems in the above-mentioned soil clearing operation and the agricultural requirements of the trellis-type grape planting, combined with the operation requirements of the grape soil clearing under the cold-proof cloth assisted soil-buried mode, this paper designed the grape winter buried soil clearing and cold-proof cloth recycling machine, which is composed of a frame, a soil clearing component, a cloth recycling component and a hydraulic system, etc. This paper explained the structure and working principle of each part of the machine in detail, and analyzed the structure and parameters of key components. The tensile performance test of the cold-proof cloth used for one year was carried out to verify the feasibility of the cold-proof cloth recycling. The result showed that the tensile strength of the old cold-proof cloth was lower than that of the new cold-proof cloth, and the warp tensile strength was better than the across, but it was not enough to affect its recycling, based on this the correct direction of the cold-proof cloth using was determined, and the basis for the design of cloth recycling component was provided. Discrete element software EDEM was used to carry out simulation test of soil clearing operation. The simulation model consisted of soil ridge and soil clearing component modes in EDEM software. The soil clearing distance was used as the evaluation index of soil clearing effect, and the experimental factors were the curvature radius of the working face of the scraper, the blade numbers of the soil clearing impeller and its rotation rate. Under the condition of 2 km/h, the three-factor five-level simulation orthogonal test was carried out. The results showed that the order of influence of three factors on soil cleaning distance was that curvature radius, blade number and rotation rate. According to the variance analysis of test result, the curvature radius was the significant influencing factor, the blade number and rotation rate were the non-influencing factors, and the optimal parameter combination was that the curvature radius was 680 mm, the blade number was 4, the rotation rate was 500 r/min, and the clearing distance was 294.27 mm. The prototype was processed and the field verification test was carried out based on the optimal parameter combination. The test results showed that the soil clearing distance was 271 mm, and the relative error with the simulation test results was 8%. The buried soil was basically cleaned and the damage to the vines and the cold-proof cloth was small. The operation efficiency of the machine was more than 10 times of the manual soil clearing efficiency. This study can provide a new development idea for the operation of buried soil clearing in Xinjiang regions of China, and provide reference for the development of follow-up grape soil clearing machinery. [ABSTRACT FROM AUTHOR]

In recent years, hydrothermal liquefaction (HTL) has attracted great attention because it has obvious advantages, such as various substrate types, total conversion of organic components from biomass (fat, carbohydrates and proteins), etc., compared with other biomass conversion technologies. In addition, HTL do not need to dry the raw materials, even biomass with high moisture content (more than 70%) can be used to produce biocrude oil via HTL. This paper reviews the latest progress in the HTL study of biomass, describes the separation process during HTL, and concentrates on the characteristics and utilization of HTL products (Biocrude oil, aqueous phase, solid residues and gases). Biocrude production of several model components from biomass was investigated, the results showed that biocrude yield of lipid was the highest (above 80%), followed by protein (20%-30%), and the yield of carbohydrate is the lowest (less than 10%). The aqueous phase is the main by-product of biomass HTL. There was 20%-50% of the organic matter in the substrate transferred to the aqueous phase. Different from the biocrude oil and aqueous phase, the organic components in the solid residues are much lower, the solid residue mainly contained inorganic components (ash content > 50%). Furthermore, we summarized the key elements migration in HTL products. In the process of HTL, 62%-98% of Ca, Mg, Al, Fe, Cu, Pb, Cd and Zn in the raw materials are transferred to the solid residues. Biocrude oil can be used as fuels, or can be used to extract high value-added products, the aqueous phase can be utilized for microalgae cultivation, methane production through anaerobic digestion or hydrogen production via microbial electrolysis cells, the solid residue is able to be used as biochar after further treatment, and gas phase can be used as gas fertilizer in the greenhouse. At last, the research direction in HTL is prospected. At present, a lot of researches on HTL of biomass were performed, but still some problems need to be further explored, mainly in the following aspects: 1) Biocrude oil components are complex, GC-MS of the biocrude oil can only obtain the information of low boiling point compounds, lack of understanding for high boiling point macromolecular compounds in biocrude oil, FTICR-MS or other technologies can be carried out to get a comprehensive understanding of the compounds. 2) The conversion mechanism of biomass HTL needs to be studied. At present, only some characterization of the product is carried out to speculate its reaction path, while the reaction intermediates are not monitored, which can be deeply analyzed by some in-situ on-line monitoring methods. Biomass HTL can improve the quality of biocrude oil by catalytic hydrogenation, and then the biocrude oil can be utilized by distillation. Although the above bottlenecks need to be explored and studied by researchers, the production of biocrude oil by HTL is expected to solve the problem of energy shortage in China because of its remarkable advantages, especially as a liquid fuel, so HTL technology has great potential in the renewable fuel production. This paper can provide references for future HTL study of biomass and the downstream utilization of HTL products. [ABSTRACT FROM AUTHOR]

Green development of agriculture is a profound revolution in the concept of agricultural development and the inevitable course to achieve sustainable development of agriculture in China. This study reviewed the roles and challenges of agricultural engineering and technology on green development of agriculture and proposed the near future directions. The level of protection and utilization of agricultural water and soil resources in China has gradually increased, and the utilization rate of agricultural waste such as crop straws, animal manure, and agricultural membranes has increased greatly. However, problems such as water shortages and arable land degradation are serious. The utilization rate of chemical fertilizers and pesticides for food crops has been increasing year by year. However, the problems of excessive application of pesticides, and external pollution still need to be resolved. In the field of agricultural ecological protection and construction, a series of projects such as soil and water conservation, returning farmland to forests and grasses had been carried out and results were delightful. However, high-intensity and extensive production methods have caused problems such as the structural imbalance in agricultural ecosystems and functional degradation. The level of quality and safety of agricultural products in China has gradually improved. However, issues such as pesticide residues, resistance gene residues, and heavy metal pollution in a few regions are still not optimistic. To resolve these problems, this paper proposed possible technological innovation in agricultural engineering serving green agrarian development: 1) In the field of agricultural resource monitoring, the further research should focus on core technologies of monitoring, evaluation, and early warning analysis of cultivated land quality, biological resources, production environment, non-point source pollution, and land carrying capacity so as to build decision-making systems that could integrate real-time monitoring, remote diagnosis, early warning, emergency prevention and control, and command and dispatch. 2) In the field of utilization of water and soil resources, the future study should enhance the use efficiency of agricultural water resources by developing water-saving equipments, establish efficient water-saving modes, improve the efficiency of land resource utilization by focusing on construction of farmland ecosystems and rehabilitation of farmland pollution. 3) In regard to agricultural inputs, the focus should be on the transformation of fertilization application methods, the application of new fertilizer technologies, as well as high-yield and efficient fertilization technologies for crops. In regard to pesticide reduction and control, the key was to develop in-situ intelligent nutrient detection, enhance fertilizer reduction and efficiency based on fertilizer application limit standards, accelerate the revision of organic fertilizer industry standards, promote the use of new fertilizer products, and develop fertilizer reductions for different crops in different regions. 4) In terms of agricultural mechanization, the main direction of the future research was to focus on fields such as large-scale field planting, facility agriculture, cash crops and aquaculture of livestock and poultry, and resource-saving agricultural machinery, straw return to the field, intelligent agricultural equipment sensors, agricultural machinery navigation, and precision operations. 5) In terms of agrarian waste resource utilization, the next work should explore the theoretical system of agricultural waste resources recycling, biological transformation and pollutant removal mechanisms, and develop equipments related to returning crop straws to the field, maturation of anaerobic fermentation, pyrolysis carbonization, and collection and storage of agricultural waste resources and so on. This paper put forward to policy suggestions from 4 aspects: strengthening the concept of green agricultural development, establishing a technological innovation and extension system, improving the construction of a standard order and strengthening policy support. It is hoped to provide meaningful guidance for further improving China's agricultural engineering technology innovation level and promoting green agrarian development. [ABSTRACT FROM AUTHOR]

Greenhouses in remote areas have difficulty to access power. This paper aims to resolve this problem with a new system that can supply electricity to low-power devices such as energy-saving lamps, temperature and humidity monitoring system, digital equipment and other electrical equipment in greenhouses in remote areas. Current power supply to greenhouses uses distributed energy sources from wind and solar, which are not portable and susceptible to environmental changes. Under certain circumstances, power supplied from these systems is insufficient or even fails. As such, there is an increase in developing portable power generation systems. For example, in China, portable multi-purpose photovoltaic power generation system had been developed for agricultural production using remote-control system (programmable logic controller, PLC) to monitor pumping stations. There was also portable multi-power source power generation system to compliment wind power, solar energy and hand-cranked energy generation. Devices to generate power using the difference in temperature between human body and ambient environment exist, which are powerful enough to power LED lights. Another portable device is to generate thermal energy by burning combustibles in the field. All these portable devices have their pros and cons and the purpose of this paper is to present a new portable thermoelectric power generation system. The size of the system was 20 cm × 20 cm × 5 cm weighted 2580 grams, and its energy sources was from combusting biomass. A flat heat pipe was used for thermal conduction. We simulated performance of the system using the ANSYS, and set an experimental platform to test it. The experimental data showed that the highest temperature at the hot end of the system was 270.1 ℃, the maximum power output was 10.7 W, and the electrical efficiency was 5.73%. The results also revealed that the system had advantages of high hot-end temperature and high thermoelectric efficiency. It can generate electricity under extreme conditions in remote areas. Numerical and experimental analysis of various inputs and outputs indicated that the system is portable, the hot end temperature is high, and the thermoelectric efficiency is high. It provides a baseline for study of portable power generation system. [ABSTRACT FROM AUTHOR]

Soil wind erosion is the main cause of land degradation in arid and semi-arid areas in northern China, which is mainly affected by surface type, climate and so on. Strong soil wind-erosion will not only accelerate regional desertification and influence the quality of human life, but also cause serious ecological and environmental problems. Since the 2000 s, our country has gradually strengthened the control of land desertification and carried out a series of sand control works, which effectively improved the overall ecological environment of the sandy land. But in recent years, there are some common phenomenon that extensive grassland and brushland was turned into cultivated land in the southeast and southwest of Mu Us sandy land. However, in the dry and windy winter or spring, these new reclaimation land is usually so exposed that it is vulnerable to suffer from strong wind erosion. Therefore, it is great significance to study the characteristics of soil wind erosion in new reclaimation land and find out the control methods. Based on the above question, this paper selected the southern part of Mu Us sandy land (38°05′27″-38°13′58″N, 107°24′28″-107°37′30″E) as the research area, as well as set up 5 observation points on different surfaces, which were represented respectively by A, B, C, D and E. Point A was on the brushland, point B was on the middle of the grassland, and other three points were respectively on different parts of the cultivated land. On the day with strong wind activity, 12 groups simultaneous observation of wind and sand were made at these 5 points (A, B, C, D, E), with each observation time at least 20 minutes. After these observations, the material of the sand samplers were weighed with an electronic balance of 1/1 000, and the material of surface and sand samplers on cultivated land were analyzed by Mastersizer2000 Laser Particle Size Analyzer. The results showed that the soil wind erosion intensity increased exponentially after grassland and shrubland were cultivated; on cultivated land, with the increase of height, the sediment transport rate decreases with exponential function within 0-10 cm height and power function within 10-20 cm height. Due to the height of the sand collector used in this paper is 20cm, lower than the height of the sand flow layer. In order to obtain the total sediment transport rate of the surface of the cultivated land, this paper must calculate it through the function simulation obtained from the above result. After calculating the total sediment transport rate, fitting it with the wind speed. We found that the total sediment transport rate has a good power function relationship with the wind speed in the cultivated land with sufficient erodibility particles. Based on the formula of the relationship between wind speed and total sediment transport rate, as well as the wind speed data of the meteorological stations in the region, the wind erosion modulus of the new reclaimation land can be preliminarily calculated. The result shows that the wind erosion modulus of the new reclaimed land is 9 657 t/(km2·a). Through the results obtained in this paper, combined with the former research results, this paper argues that the emergence of new reclaimed land has an important impact on regional desertification, and its area should be used as an important index when evaluating regional desertification. Meanwhile, Controlling cultivated land area, establishing windbreak and sand fixation forest, as well as retaining stubble at a certain height can effectively control soil wind erosion in newly reclaimed land. [ABSTRACT FROM AUTHOR]

In order to explore the suitable technology for the reclamation of erosion gullies in the black soil area of the Northeast China. In this paper, Xinhua farm is selected as the research area which is located in Hegang City, Heilongjiang Province, China. Aiming at the cause of erosion gullies, a new technology of filling and reclamation erosion gully with coal gangue was introduced and the post effect of the new technology was studied, including, the technological process of filling and reclamation, the influence of the thickness change of reclamation filling materials on the drainage characteristics of the gully, the fertility status and heavy metals pollution degree in the reclaimed soil. This paper aimed to explore the feasibility and breakthrough points of the technology of filling erosion gullies with coal gangue. The results showed that: 1) The increase in soil layer thickness could weaken the drainage capacity of the gully, while the increase of mixed size coal gangue thickness and large size coal gangue could increase the drainage capacity of the gully in different degrees. The interaction between the soil layer thickness and large size coal gangue layer thickness obviously influenced the drainage capacity of the gully. When the thickness of soil layer, mixed size coal gangue layer and large size coal gangue layer were 53.42, 38.51, 90 cm respectively, the shortest outflow time was 145.129 s, the drainage capacity of simulated 2 m deep gully was the strongest in this mode. 2) After 4 years of gully reclamation, the soil bulk increased, the soil acidity improved, the content of total potassium was the same as CK, but the total nitrogen, total phosphorus and organic matter content were lower than CK. And then the comprehensive fertility of soil was less than CK, which is 66.71%-80.81% of CK, and the average level only reach to 72.75%. But it was slightly higher than that of the second accumulated temperature zone in Heilongjiang Province. 3) The content of Pb was basically the same as CK and background value of local control soil; however, as for Cr and Cu, they were higher than CK and background value of local control soil in the reclaimed soil of monitoring gully. But the content of Cr, Pb, Cu are not higher than the second level standard value of national environmental quality of China. . There are slight pollution and slight enrichment of heavy metals Cr, Pb and Cu in monitored gully reclamation soil, so coal gangue can be used as a material for filling erosion gully for reclamation. However, in the long term, attention should be paid to the problem of soil heavy metal enrichment during reclamation. [ABSTRACT FROM AUTHOR]

In recent years, China's pig industry has gradually shifted to the northeast. Compared with the rich feed resources and land resources in Northeast China, the cold environment reduces the feed conversion efficiency and the production performance of pigs. In the winter of northern China, pig producers often face a huge problem of heat preservation when they control the environment of piggery. The aim of this study is to explore the heat preservation of piggeries in Northeast China. According to the investigation, there were four types of piggeries in Jilin Province, which were brick wall piggery, concrete wall piggery, color steel wall piggery and greenhouse piggery. The simulated piggeries with brick wall, concrete wall and color steel wall were based on the experimental piggery of Jilin Agricultural University, the simulated piggery with greenhouse was based on a piggery in a pig farm, and the simulated pig farm area was based on a pig farm area. Based on Ecotect software, this paper took a typical piggery in a large pig farm in Jilin Province as an object, and studied the light and heat environment of piggery, and the light environment of pig farm production area. The daylight factor of different heights in the piggery and the lighting situation in the production area of the pig farm were studied. The thermal insulation performances of 4 kinds of piggeries with different walls were analyzed. The results were as follows: The daylight factor of each research height of the experimental piggery was higher than 2%, which met the green building standard. The production area of the pig farm had good daylight, and the solar radiation in Great Cold Day could reach 5.38 MJ/(m²·d), and the sunshine was sufficient. The building spacing of the pig farm met the epidemic prevention standard, and there was no shelter problem. By comparing the monthly energy consumption values of 4 kinds of piggeries with different building materials, the best insulation performance of piggeries was as follow: Clay porous brick piggery, foam concrete pig piggery, color steel piggery with phenolic sandwich board, low density polyethylene film greenhouse piggery. After considering the cost, it was recommended to use cinder brick masonry piggery, fly ash aerated block piggery, polyphenylene sandwich board color steel piggery and low density polyethylene film greenhouse piggery. The daily energy consumption of empty piggery in December was tested and verified. The relative error range was 0.74%-8.62% after data comparison, which verified the reliability of the model. The simulation values of energy consumption were in good agreement with the measured values. On the one hand, it verified the correctness and rationality of setting parameters in the software. On the other hand, it showed that Ecotect software was feasible in piggery building. This paper can provide theoretical basis for exploring the light and heat environment of the northern piggery, and provide more ideas for architects to optimize the design before the implementation of the plan. [ABSTRACT FROM AUTHOR]

As the core technology of mechanized conservation tillage, no-tillage sowing is a new type of agricultural cultivation method popularized in recent years, it directly sows in the field where the straw and roots of the former crops are left, which not only reduces water evaporation and soil erosion, but also can ensure the germination and growth of seeds, which is conducive to water storage and conservation, increasing production and income, and at the same time improving soil fertility to some extent. However, after the harvest of the former crops without any collection and removal treatment, the “full amount of straw field” has become the new normal state of China's cultivation. The traditional no-tillage seeding equipments are prone to easily increase the workload of straw crushing device when it entering the soil and extinguishing stubble, which causes the blockage and jamming of straw conveying device. In order to solve this problem, the back-throwing type no-tillage straw smashing planter was taken as the research object in this paper, and an automatic control system based on off-ground height of the straw smashing device was developed. Torsional deformation acquisition device was created based on a double fan-shaped through hole metal detection disc and proximity switch, which was installed at both ends of the driving shaft to effectively monitor the rotation speed of the driving shaft and the stagger angle caused by the change of torque load. The design was based on the 32-bit ARM CortexTM-M3 core microprocessor hardware platform, which constituted the data acquisition and output drive unit of the automatic control system, the driving shaft rotation speed and stagger angle was collected in real time, the change trend was analysed through the system software, and current working conditions was identified. According to the corresponding output control signal, the straw height adjusting mechanism timely corrects the off-ground height of the straw smashing and conveying device to stabilize the working load. The straw height adjustment mechanism was composed of a solenoid valve, a hydraulic cylinder, a fixed bracket and a supporting ground wheel. The hydraulic cylinder's high pressure driving oil was taken directly from the working tractor to improve the applicability of the device. The performance verification test showed that under the driving shaft’s rated rotation speed of 2 500 r/min, when the height of the straw crusher off the ground changed the working load, the automatic control system controled the rotation speed of the driving shaft between 2448 and 2632 r/min, the change of the stagger angle of the driving shaft was ± 0.002 4 rad, and the response delay time of the control signal to the change of the stagger angle was 0.24 s. The field operation comparison test showed that when the back-throwing type no-tillage straw smashing planter was equipped with automatic control system based on off-ground height of the straw smashing device, the passability of the machine was greatly improved, the occurrence of blockage was eliminated, the operation efficiency was increased by 52.9%, and the height of surface stubble was reduced by 43.4% after straw smashing operation. In conclusion, The design of this paper uses the change trend of the driving shaft rotation speed and stagger angle to identify the working condition, effectively eliminating the influence of mechanical structure parameters and material differences, and the mechanical structure is light and easy to install, which can provide reference for qualitative monitoring of torque load of agricultural machinery. [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]

To implement systematic evaluation of land carrying capacity for livestock and poultry manure, prejudge its development trend and inspect the implementation effects of different emission reduction policies, this paper conducts the design and simulates different scenarios of land carrying capacity system model for livestock and poultry manure. Based on analyzing various subsystems of social economy, livestock and poultry breeding, crop planting and land carrying, and their elements, we established a system dynamic model of land carrying capacity for livestock and poultry manure, taking Shijiazhuang City as an example, which was an important city of animal husbandry in north of China. The system operation results indicated that: The model had good stability and reality, the error between the simulated value and the measured value was generally less than 10%. Therefore the model was effective. The system dynamic model was used to simulate the carrying capacity of livestock and poultry farming land in Shijiazhuang City from 2007 to 2025 under different scenarios. Five scenarios were designed. Scenario1: Inertial trend development condition, adjusting the economic structure of the animal husbandry, the investment in environmental protection, the proportion of manure and fertilizer and the mode of coordinated development, the simulation results show that: the output scale of animal husbandry and planting has increased, but the output growth of planting is inferior to that of livestock and animal husbandry, making it difficult for planting to consume nitrogen and phosphorus emissions by animal husbandry, and bringing more land carrying pressure. Scenario 2: Adjusting the economic structure of animal husbandry, both nitrogen and phosphorus balance carrying capacity present a downward trend, but phosphorus balance carrying pressure still exists. Scenario 3: Adjusting the environmental protection governance investment, nitrogen balance carrying is in the loadable state. Although the phosphorus balance carrying pressure is obviously decreased, only 8 years are loadable. Scenario 4: Adjusting the manure use ratio, nitrogen balance carrying is in the loadable state. The phosphorus balance carrying with improvement over the initial situation is still overloaded. Under the coordinated development mode, both nitrogen and phosphorus balance carrying pressure present a downward trend, both nitrogen and phosphorus balance carrying capacity are at the loadable level. It can be found through comparative analysis that the coordinated development mode has the best effect. This study provides support for carrying out monitoring and evaluation of livestock and poultry pollution and establishes an assessment mechanism for livestock and poultry breeding pollution on one hand. On the other hand, this paper provides scientific basis for the regulation and control of animal husbandry development in major livestock cities and other resources and environment overloading areas. [ABSTRACT FROM AUTHOR]

In the rice area of the Northeast China, the large amount of rice straw with low moisture content is tough to chop. However, the existing method of chopping combined auxiliary slitting could not meet the requirements of chopping under such condition, which could cause some problems such as incomplete straw crushing and unqualified rate of straw crushing. It would affect the subsequent land preparation and transplanting operations and caused problems such as machine blocking, straw floating before transplanting and seedling floating during transplanting. In order to solve these problems, this paper designed a straw chopper based on the principle of differential sawing, which could realize the same direction with different speed between the saw disc blade and the crushing knife to achieve supporting sawing. The friction force and relative linear velocity of crushing straw were increased to improve the crushing effect. Structural parameters of saw disc blade, crushing knife and other key components were designed through theoretical analysis, and the structure and operating parameters of the machine were preliminarily obtained. In order to improve the wind velocity and straw feeding performance of the crushing chamber, three kinds of fan blade forms, namely facade fan blade, reverse fan blade and diverse fan blade, were designed to compare with no fan blade through simulation analysis. Simulation results by Fluent showed that the facade fan blade could improve the wind velocity in the crushing chamber and contributed to improving straw fluidity, and the verification test was in accordance with the simulation results. According to the movement track of crushing knife and saw disc blade, the rotation speeds of them were designed. The rotation speed of crushing knife ranged from 1815 to 2475 r/min, accordingly, and the saw disc blade rotation speed ranged from 605 to 825 r/min, to be specific, the ratio of rotation speed between saw disc blade and crushing knife was 1/3 constantly. The dynamics analysis of straw crushing process showed that rotation speed of crushing knife and the tilt angle between the saw disc blade could affect crushing performance. Therefore, a field experiment of two factors with three levels was designed by using the average length of straw crushing and the crushing qualification rate as an evaluation index. The test results showed that the crushing knife rotation speed and angle of slope had a significant impact on average length of straw crushing and straw crushing qualification rate. Considering straw crushing performance and energy consumption, the optimal combination was determined as follows: The crushing knife rotation speed was 1800 r/min and the angle of slope was 65°, the corresponding saw disc blade rotation speed was 600 r/min. The field test results under the optimized combination conditions were as follows: the average length of straw crushing was 9.58 cm, the proportion of straw under 10 cm was 93.23%, and the scatter unevenness was 20.89%, which met the quality requirements of straw crushing and scattering in the northeast rice region. In the paper, a comparison test between the differential sawing rice straw chopper and the ordinary straw chopper was carried out. The filed test showed that the average length of straw crushing of the ordinary straw chopper was 13.42 cm, and the proportion of straw under 10 cm was 71.5%, which was not as good as the differential sawing rice straw chopper, and there was no obvious difference in the scatter unevenness between them. After the chopping operation, the same plow was used for the plowing operation, and the straw burying rate was 98.92% of the differential sawing rice straw chopper while the ordinary straw chopper was 90.21 %. Its successful implementation could greatly improve the operation effect for chopping rice straw and stubble on one hand, and on the other hand provided better growing surface conditions for rice. The design of the machine provided a basis for the popularization and application of straw mulching technology in northeast China. [ABSTRACT FROM AUTHOR]

The FAO-56 Penman-Monteith estimates that the ET0 method is widely used, but multiple meteorological data are required for calculation. Developing an alternative method that can provide accurate or at least close to the FAO-56 Penman-Monteith ET0 estimate is one of the research hotspots in the field with as little meteorological data as possible. In this paper, combined with Canonical Correlation Analysis (CCA) and k nearest neighbor algorithm (k-NN), the potential evapotranspiration calculation method (CCA-k-NN) of self-optimizing nearest neighbor algorithm is proposed, and the potential evapotranspiration is realized by using less meteorological data. Estimate. The core idea is to use the CCA algorithm to find the meteorological data most relevant to the potential evapotranspiration, to realize the dimensionality reduction of the meteorological data when the ET0 is estimated later, and then use the k-NN algorithm to estimate the ET0. The Northwest China region was selected as a use case. The regional meteorological data were divided into training dataset, verification dataset and test dataset from time and space scales. The ET0 was estimated by the method in the three types of datasets respectively, and the FAO-56 Penman-Monteith as a reference, evaluated the estimation accuracy and applicability of the CCA-k-NN method. The results show that the CCA-k-NN method has a high correlation with the FAO-56 Penman-Monteith (correlation coefficient greater than 0.9), and has good estimation accuracy. The root mean square error and Mean Absolute Error are both less than 1 mm·d-1. On the spatial scale, the Nash-Sutcliffe coefficient of efficiency is greater than 0.5, and the Nash-Sutcliffe coefficient of efficiency on the time scale is greater than 0.8, the CCA-k-NN method is applicable at both space and time scales. At the same time, compared with other alternative methods, the algorithm has low time complexity O(n), which can effectively reduce the time cost when calculating large amounts of data. The FAO-56 Penman-Monteith estimates that the ET0 method is widely used, but multiple meteorological data are required for calculation. Developing an alternative method that can provide accurate or at least close to the FAO-56 Penman-Monteith ET0 estimate is one of the research hotspots in the field with as little meteorological data as possible. In this paper, combined with Canonical Correlation Analysis (CCA) and k nearest neighbor algorithm (k-NN), the potential evapotranspiration calculation method (CCA-k-NN) of self-optimizing nearest neighbor algorithm is proposed, and the potential evapotranspiration is realized by using less meteorological data. Estimate. The core idea is to use the CCA algorithm to find the meteorological data most relevant to the potential evapotranspiration, to realize the dimensionality reduction of the meteorological data when the ET0 is estimated later, and then use the k-NN algorithm to estimate the ET0. The Northwest China region was selected as a use case. The regional meteorological data were divided into training dataset, verification dataset and test dataset from time and space scales. The ET0 was estimated by the method in the three types of datasets respectively, and the FAO-56 Penman-Monteith as a reference, evaluated the estimation accuracy and applicability of the CCA-k-NN method. The results show that the CCA-k-NN method has a high correlation with the FAO-56 Penman-Monteith (correlation coefficient greater than 0.9), and has good estimation accuracy. The root mean square error and Mean Absolute Error are both less than 1 mm·d-1. [ABSTRACT FROM AUTHOR]

Source reduction and process control are the key links of comprehensive treatment of pig farm wastes, and pig house is the source of waste generation. In this paper, the effects of wasted water quantity of water dispenser, flushing water quantity of enclosure and dung method on harmful gases, sewage discharge and pollutant concentration in large-scale pig farms were expounded from three aspects, and three measures for emission reduction from the source of pollutants generated in the enclosure were put forward. Under the scientific feeding and management, according to the different stages of pig drinking water standard, the suitable drinking water and water flow speed can be allocated. According to the density of drinker, the suitable drinking water can be provided, and the drinkers were installed at the right place and height. In general, their behavior of lying down, eating, drinking and excreting was continuous. According to their excretion behavior, water dispensers were usually installed in the leaky floor area, the excretion area was located in the short side wall of the pen, and the separation mode of the pen was designed to be closed. It was suggested that the breeding and fattening stages should be separated from each other in the feeding process, and the appropriate feeding density should be designed so that pigs could only excrete at the fixed points. In the case of guaranteeing the minimum discharge of wasted water from drinking water appliances and flushing water from enclosures, the mode of manure scavenging was a relatively important factor affecting harmful gases, sewage discharge and pollutant concentration in enclosures in emission reduction measures of pollutant sources. Compared with the blister manure and water flushing manure, mechanical dry-dung cleaning process could reduce the harmful gas concentration, sewage discharge and pollutant concentration to the greatest extent. Under the conditions of pig farm, it was suggested that the floor of pig house should be designed as a semi-leaky seam floor and equipped with mechanical dry-dung cleaning technology, which could reduce the pollutant emission of pig house to a large extent. At present, the great breakthroughs had been made in the research of engineering technology for reducing pollutant sources in pig farms in China, but the popularization and application of this technology in pig production was still in its infancy. The related technical equipment in this field still faced many problems, such as insufficient matching, complex operation and management, high cost and poor stability. Therefore, it was suggested to vigorously develop the research and application of pig farm waste source reduction technology model, comprehensively consider the drinking water system, fence layout, fecal clearance mode and other engineering technologies, design and develop the mechanical dry-dung cleaning system and its supporting facilities and equipment. At the same time, the intelligent drinking water, excrement and deodorization could be developed by using electronic information technology such as Internet of Things, big data, artificial intelligence and so on. Such as waste reduction breeding equipment improved the stability of equipment and intelligent management level. The purpose of this paper was to provide technical support for reducing the total amount of pig wastes, reducing the cost of treatment and utilization, and realizing clean and healthy breeding, so as to promote the green transformation and upgrading of pig breeding industry in China. [ABSTRACT FROM AUTHOR]

Cotton stalk is an important renewable resource. China is rich in cotton stalk, if such a large amount of resources are recycled, it will produce huge economic benefits. But most of them are not recycled at present. In order to improve the mechanized recovery level of cotton stalk, study the influence of different parameters on the mechanized recovery of cotton stalk, and solve the outstanding problems such as high cotton stalk plucking rate and high cotton stalk leakage rate, this paper studied and designed a toothed disc cotton stalk harvester. The machine was consisted of suspension device, limit wheel, pull-out tooth plate, stalk discharge device, hydraulic motor, hydraulic pipeline and hydraulic control box. The key component of the machine was a toothed disc type stalk pulling device. During operation, the cotton stalk was lifted out through the toothed disc, and then the cotton stalk was discharged to the surface through the stalk discharge device. Leakage rate and plucking rate of cotton stalk were the main parameters to evaluate the performance of toothed disc cotton stalk harvester. In this paper, Box-benhnken central combination test method was used to study the working parameters of toothed disc cotton stalk harvester. Three-factor and three-level quadratic regression orthogonal test was designed. The three-dimensional model of response surface was established with the diameter of the toothed disc, the toothed disc speed ratio and the lifting height as the influencing factors. The influence of each factor on the quality of work was analyzed, and the influencing factors were optimized synthetically. The results showed that the lifting height and the toothed disc speed ratio had significant effects on the cotton stalk plucking rate (P< 0.01), while the lifting height, the diameter of the toothed disc and the toothed disc speed ratio had significant effects on the rate of cotton stalk leakage rate (P<0.01). The working parameters of the machine were deduced from the regression model optimization as follows: the lifting height was 66.2 mm, the diameter of the toothed disc was 627.59 mm, and the toothed disc speed ratio was 0.57. In November 2018, field test was carried out in the Yellow River Delta (Binzhou) National Agricultural Science and Technology Park. Test area was divided into 17 test plots, leakage rate and plucking rate of cotton stalk at each test plot were calculated. The results of the Daejeon experiment showed that when the lifting height was 70 mm, diameter of the toothed disc was 630 mm and the toothed disc speed ratio was 0.57, the cotton stalk plucking rate could reach 1.5% and the cotton stalk leakage rate was low to 3.0%. The test results showed that the theoretical results were coincident with the measuring results, and the error between them was less than 4%. The research results can provide references for the structure improvement design and operation parameters optimization of toothed disc cotton stalk harvester. [ABSTRACT FROM AUTHOR]

Green crop is generally used as the foreground in image segmentation of agricultural visual navigation system because of its obvious chromaticity difference from the basic image background. However, for the segmentation of maize stubble row, there are many backgrounds in the field harvested by combine harvester, such as naked land surface, maize residues, which has little color difference with the maize stubble row. To achieve accurate and quick segmentation of maize stubble row, an image segmentation approach of maize stubble row based on genetic algorithm and threshold filtering noise was proposed in this paper. Firstly, the RGB color space was selected to accomplish the segmentation, which is a basic color space and widely used in machine vision automatic guidance systems. Secondly, to reduce the difficulty of image segmentation, the region of interest (ROI) was selected by calculating the maximum of column gray value accumulation. Thirdly, the gray-scale image of the maize stubble row was obtained through the optimized gray-scale operator. Besides, the genetic algorithm was often used in global optimization, which was used to optimize the gray-scale operator. Specially, the maize stubble row image’s pixel was divided into 3 classes: land surface, residues in rows and stubble tip incision, and the 3 classes were selected as the sample to optimize the gray-scale operator by genetic algorithm. Then, the segmentation of single threshold method was used to segment the gray-scale image. Furthermore, the segmentation of single threshold method is widely used in image segmentation because of its high efficiency and convenience. Lastly, the morphological corrosion treatment (MCT) and threshold noise filtering algorithm (TNFA) were applied to guarantee the integrity of the maize stubble row region and the noise points on both sides of the maize stubble row removal. In order to verify the effect of the method proposed in this paper, 200 test images were captured from Zhuozhou Experimental Station of Conservation Tillage Research Center of Ministry of Agriculture in Baoding City, China in each October during 2014－2016. The acquisition was often on sunny day, aiming at collecting images under different natural lighting conditions, different positions in maize stubble row field. The results showed that the average relative object area error (ARAE) by our method was only 24.68%, while the AREA of the iteration method and the OTSU method were 90.67% and 86.42%, respectively. The average processing time of a test image based on this paper presented algorithm was 0.16s, which was much more time-consuming than the OTSU method (0.07s), while the processing time of our method was less than the iteration method (0.25s). Therefore, the method presented in this paper achieved better performance than other methods in maize stubble row segmentation, and was effective to segment the maize stubble row in the complicated backgrounds. The presented method can provide precise basis for detection of guidance line in maize straw covering field. [ABSTRACT FROM AUTHOR]

Quantitatively evaluation of satellite precipitation and potential evapotranspiration products with the high resolution, wide coverage and dynamic continuity is an important foundation for drought monitoring over mainland China. This paper examined the accuracy of products and the utility of drought monitoring using the newly released long-term (more than 30 years) satellite precipitation products (climate hazards group infrared precipitation with station, CHIRPS) data version 2.0 and potential evapotranspiration products (global land-surface evaporation: the Amsterdam methodology, GLEAM) dataset. We selected standardized precipitation evapotranspiration index (SPEI) and six statistical and classification measures indexes to evaluate accuracy and the utility of CHIRPS and GLEAM-Ep (potential evapotranspiration derived from GLEAM), with China Gauge-based Precipitation Daily Analysis dataset (CGDPA) and potential evapotranspiration calculated by Penman-Monteith (PM-Ep) as evaluation reference data sets. The results showed that CHIRPS and GLEAM-Ep performed well in eastern and southwest of China. However, their performance in western China was uncertain due to the sparsity of meteorological stations. SPEIs (SPEI value calculated by the CHIRPS and GLEAM-Ep) had a good performance on drought monitoring in eastern and southwestern China. Values of correlation coefficient (CC) between SPEIs and SPEIm (SPEI value calculated by the CGDPA and PM-Ep) were more than 0.6 in southeastern China, southwestern China, the middle and lower reaches of the Yangtze River region and northern China, especially in relatively humid areas, which the correlation coefficient values were more than 0.7 and the root mean-squared error (RMSE) values were less than 0.8. In order to further evaluate the performance of SPEIs in drought monitoring at spatial and temporal scales, the SPEIs3 (SPEIs at three-month scale) and SPEIm3 (SPEIm at three-month scale) in southeastern China, southwestern China, the middle and lower reaches of the Yangtze River region and northern China were compared. SPEIs3 had a better simulation effect on the evolution process of the ratio of drought area in those regions during1981-2016. And the success ratio of simulating drought duration was about 0.93, 0.57, 0.71 and 0.81, respectively. Moreover, SPEIs3 displayed a high accuracy over the four regions in capturing drought, which was the spatial distribution of typical drought events on specific month. In conclusion, SPEI based on long-term CHIRPS and GLEAM-Ep could be applied to monitor and evaluate drought in eastern and southwestern China. This paper can provide reliable reference for monitoring and warning of drought events and water resources management in those regions. [ABSTRACT FROM AUTHOR]

Cotton stalk is an important renewable resource. China is rich in cotton stalk, if such a large amount of resources are recycled, it will produce huge economic benefits. But most of them are not recycled at present. In order to improve the mechanized recovery level of cotton stalk, study the influence of different parameters on the mechanized recovery of cotton stalk, and solve the outstanding problems such as high cotton stalk plucking rate and high cotton stalk leakage rate, this paper studied and designed a toothed disc cotton stalk harvester. The machine was consisted of suspension device, limit wheel, pull-out tooth plate, stalk discharge device, hydraulic motor, hydraulic pipeline and hydraulic control box. The key component of the machine was a toothed disc type stalk pulling device. During operation, the cotton stalk was lifted out through the toothed disc, and then the cotton stalk was discharged to the surface through the stalk discharge device. Leakage rate and plucking rate of cotton stalk were the main parameters to evaluate the performance of toothed disc cotton stalk harvester. In this paper, Box-benhnken central combination test method was used to study the working parameters of toothed disc cotton stalk harvester. Three-factor and three-level quadratic regression orthogonal test was designed. The three-dimensional model of response surface was established with the diameter of the toothed disc, the toothed disc speed ratio and the lifting height as the influencing factors. The influence of each factor on the quality of work was analyzed, and the influencing factors were optimized synthetically. The results showed that the lifting height and the toothed disc speed ratio had significant effects on the cotton stalk plucking rate (P< 0.01), while the lifting height, the diameter of the toothed disc and the toothed disc speed ratio had significant effects on the rate of cotton stalk leakage rate (P<0.01). The working parameters of the machine were deduced from the regression model optimization as follows: the lifting height was 66.2 mm, the diameter of the toothed disc was 627.59 mm, and the toothed disc speed ratio was 0.57. In November 2018, field test was carried out in the Yellow River Delta (Binzhou) National Agricultural Science and Technology Park. Test area was divided into 17 test plots (each plots is 30 m×0.76 m), leakage rate and plucking rate of cotton stalk at each test plot were calculated. The results of the Daejeon experiment showed that when the lifting height was 70 mm, diameter of the toothed disc was 630 mm and the toothed disc speed ratio was 0.57, the cotton stalk plucking rate could reach 1.5% and the cotton stalk leakage rate was low to 3.0%. The test results showed that the theoretical results were coincident with the measuring results, and the error between them was less than 4%. The research results can provide references for the structure improvement design and operation parameters optimization of toothed disc cotton stalk harvester. [ABSTRACT FROM AUTHOR]

It has great significance to study the trade-off mechanism of productive and dwelling space of rural settlement and the optimized of its productive and dwelling space nowadays in China, which is one of the basic means to improve the rural habitat environment and adjust the inner structure of rural residential land. With the development of socio-economic, productive and dwelling space of rural settlements gradually diversified in developed areas such as suburban areas and industrial areas in eastern China, which present reciprocal tradeoffs. These changes distinguish from the abandonment and hollowing of productive and dwelling space of rural settlements in traditional agricultural area. However, current researches mainly consider the rural settlement as a single entity and tend to neglect its inner productive and dwelling space. This paper introduces the concept of ecosystem service trade-off, analyzes the trade-off between productive space and dwelling space of rural settlements in economically developed areas from the aspects of “types of trade-off, driving forces, effects,” and then this paper puts forward the idea of optimizing the productive and dwelling space of rural settlement. The results show that, the trade-off of productive and dwelling space of rural settlements which in developed areas, is caused by the diversification of farmers' livelihood and the development of non-agricultural industries in rural areas, farmers have a demand for living apace, industrial and commercial space, and choose various functional spaces according to their needs. According to the spatial combination of productive space and dwelling space of rural settlement, the trade-off types can be divided into residential-industrial space trade-off, residential-commercial space trade-off, residential-rental space trade-off, multi-space trade-off and so on. Land use versatility and the diversification of productive and dwelling space of rural settlement that driven by industrialization and urbanization is the premise of the productive and dwelling space trade-off of rural settlement. The types and its variations of productive and dwelling space trade-off of rural settlement are directly determined by the livelihood and life needs of farmers. While the land plan control by the government and the lack of village planning has exacerbated the process of the productive and dwelling space trade-off of rural settlement. The trade-off of productive and dwelling space of rural settlement improves the livelihoods of farmers and promotes the economic development and the vitality of rural areas, but also causes a variety of negative effects, such as the spatial clutter of rural settlements, the deterioration of human living environment and other problems. The reconstruction model of rural settlement as homogeneous space is far from the needs of farmers. In the future, under the background of the shortage of construction land in rural areas, it is necessary to meet the diversified demands of farmers and the optimizing of the productive and dwelling space of rural settlement by the multifunctional composite and functional improvement of land use of rural settlement. This paper puts forward the concept of productive and dwelling space trade-off of rural settlement, which provides a new perspective for the study of rural residential transition and a new idea for improving the rural space quality and the residential living environment, and promotes the formation of scientific and reasonable village planning. Above all these will serve for rural revitalization strategy in China. [ABSTRACT FROM AUTHOR]

Accurate and effective drought monitoring using remote sensing technology is essential for regional and global drought warning and forecasting. Especially, soil moisture (SM) is one of the key potential factors affecting agricultural drought. At present, most studies ignore the fact that soil moisture is a complex nonlinear coupling system，the research only using visible light, near infrared, short-wave infrared, thermal infrared and other remote sensing drought index has certain limitations in SM inversion. A new method of retrieving farmland SM of winter wheat at returning green stage based on MODIS and radial basis function neural network (RBFNN) is presented in this paper. Firstly, the adaptability of various MODIS-derived drought indices is analyzed in the period of seedling establishment of winter wheat, including soil water content, crop morphological change in water requirement, crop canopy water content and temperature and other parameters. Secondly, the correlation between the original remote sensing drought indices and the soil relative humidity 10 cm soil layer was analyzed. A comprehensive evaluation set of apparent thermal inertia (ATI), vegetation supply water index (VSWI), enhanced vegetation index (EVI), normalized difference infrared index band7 (NDIIB7), normalized multi-band drought index (NMDI) and temperature condition index (TCI) are selected to invert soil moisture of farmland. Finally, combining MODIS remote sensing drought index with RBFNN, the SM of farmland was retrieved synergistically, and the retrieved results were compared with those of BP-NN and linear regression (LR) models. The experimental study is conducted in Henan province of China, MODIS reflectance products (MOD09A1) and temperature products (MOD11A2) at returning green stage of winter wheat from 2001 to 2012 were used to extract remote sensing drought indices, and the global land cover product of MODIS (MCD12Q1) is selected to obtain cropland distributions. Soil moisture data is derived from the “China crop growth and development and farmland soil moisture ten-day dataset”, which contains the soil relative humidity of 10 and 20 cm soil layer observed every 10 days by 17 soil moisture stations. The results show that the average accuracy of SM inversion model using RBFNN and multiple drought indices is 93.27%, which is increased by 2.92 and 9.97 percentage points compared with BP-NN and LR model, respectively. Most of the data points of the three models are concentrated around the 1:1 line, which indicate that there is a good correlation between the predicted value and the measured value. Compared with BP-NN model and LR model, the deviation between predicted value of RBFNN model and the 1:1 line is the smallest, the higher the regression correlation coefficient is, the higher the determination coefficient is. SM is significantly correlated with ATI, NDIIB7 and VSWI in the early growth stage of winter wheat. Multi-band remote sensing drought monitoring indices can comprehensively reflect the changes of crop physiology and morphology under soil water stress, and also determine the retrieval accuracy of the humidity model simultaneously. In this paper, only winter wheat in returning green stage is selected as the research object, and the comprehensive evaluation index set selected is not suitable for SM inversion of other growth stages of winter wheat, the adaptability of different remote sensing drought indices in different growth stages needs further experimental study. The study provides a new case for regional SM inversion from remote sensing-based drought monitoring indices and neural network. [ABSTRACT FROM AUTHOR]

Peanut, which has high economic value, is one of the main oil crops in China. Freshly harvested peanuts usually had high moisture contents, which were about 40%-60%. If peanuts with high moisture content did not dry in time, it was easy to fever and mildew. So it is very important for peanuts drying in time. In this paper, three varieties of wet peanuts, Kainong 71, Kainong 8834-9 and Tianfu 3, were dried by hot air, which temperature was 35 ℃ and air velocity was 0.6 m/s. And the moisture contents of peanuts, peanut kernels and peanut shells were monitored during the drying process. The changes of free water, weak-bound water and bound water in peanut kernels during drying were studied by low-field nuclear magnetic resonance (LF-NMR) technology. The common law of internal moisture changes in peanut kernels during drying process was obtained. The mathematical relationship between the total percentage of moisture relaxation peaks in peanut kernels and their moisture contents determined by the national standard method was established. A rapid detection method of peanut moisture contents was proposed in this paper, which had a practical significance for peanut storage and processing. The results showed that regardless of the amount of oleic acid in peanuts and the size of the peanuts, the drying characteristics of the three varieties of peanuts were similar. The moisture contents of the three varieties of peanut and peanut kernel showed different downward trend compared to the peanut shell. The moisture contents of peanut shell first declined rapidly in the early stage (2-4 h), then slowly due to their fiber structure. The LF-NMR relaxation spectra of peanut kernels of the three varieties all had four main peaks, namely, free water peak, weak-bound water peak, bound water peak and oil peak. During the drying process, the free water peak areas of peanut kernels of the three varieties decreased gradually, and almost disappeared at the end of drying. The changing trends of the weak-bound water and bound water peak areas were obvious. The peak areas of oil peaks did not change significantly, indicating that the oil content in peanut kernels remained unchanged during drying process. The relaxation peak area ratios of peanut kernels of the three varieties in low-field NMR relaxation spectra also showed similar trends during drying. The percentages of bound water peak area and oil peak area showed an upward trend. The percentage of free water peak area showed a downward trend, which was very low at the end of drying, indicating that free water almost completely lost at the end of drying. The percentage of weak-bound water peak area firstly rose, then declined at the end of drying, indicating that some weak-bound water was lost. Therefore, free water and weak-bound water were the main kind lost water in the drying process. In addition, it could be judged that if the relaxation peak of free water disappeared or the peak was very small, the moisture contents of peanut kernels were below the safe storage moisture content. The R2 of equation established to predict the moisture content of peanut kernel is 0.888 4. The equation has been validated and the fitting results were good. Therefore, the LF-NMR technology can be used for rapid detection of moisture content in peanut kernels. [ABSTRACT FROM AUTHOR]

High-quality optical data is difficult to acquire in southwest China, due to the cloudy and rainy weather. The synthetic aperture radar (SAR) can work for all-time and all-weather, but the revisit period is usually long. Therefore, it is a high demand for the synergy of optical and radar data rather than a single remote sensing data source, particularly for the survey and assessment on the land resource, as well as the global change. This study performed an object-oriented guided segmentation on the difference images generated from 2016 and 2019 quad-pol Radarsat-2 data using the 2019 Sentinel-2 optical data of Meishan region. A Fractal Net Evolution Approach (FNEA) was first utilized to segment the 2016 optical image for an initial segmentation. Then, the second segmentation was implemented using the same approach, where the features of the SAR image were provided for the purpose of guided segmentation. As such, the regions of growth were merged from small to large, in order to eventually form a complete geographical object. A final segmentation was obtained to select the changed and unchanged samples. More importantly, an object contained both changed and unchanged pixels, particularly with a single type of pixel inside the samples. Then, the object-level multidimensional features were extracted using the samples. The initial radar parameters included the backward scattering coefficient, Pauli and Freeman-Durden polarization decomposition parameters. The segmentation was utilized to generate the geographic objects. Meanwhile, some parameters were calculated using the initial parameters, including the mean, and standard deviation, whereas, the texture feature parameters using the Gray-level co-occurrence matrix (GLCM) included the mean, standard deviation, homogeneity, contrast, entropy, and the correlation for a total of 72-dimensional features. The redundant feature dataset was filtered to select the extracted feature set. Consequently, an FSO-RF change detection framework was proposed to achieve the feature optimization and the acquisition of the final change detection. The inter-sample distance metric learning was used to optimize the separability of feature space. The optimal features were used to calculate the distance between the changed and unchanged samples in different features. Finally, the change detection task was implemented using an object-oriented random forest classifier. The existing change detection pixel-based methods were selected to verify the improved model, including the change vector analysis (CVA), principal component analysis (PCA), multivariate alteration detection (MAD), Iteration multivariate alteration detection (IR-MAD), support vector machines (SVM), and random forest (RF) change detection using radar difference image segmentation. The change detection framework showed a remarkable improvement, with an overall accuracy of 92.90% in the test area. Two representative areas were selected in the study area for sampling and validation. The experiments demonstrated that better performance was achieved than that of the traditional, although the accuracy indexes were degraded in some areas with the complex features. The overall accuracies of the two sample areas reached 95.08 % and 88.16%. The algorithm in this paper can well meet the needs of detecting changes in different feature categories such as towns and farmlands, and has certain application value in the monitoring of national land resources. [ABSTRACT FROM AUTHOR]

As long-standing goals and all-round development practices of agricultural and rural modernization of China, the rural revitalization strategy provides huge opportunities and spaces for the disciplinary innovation and development of all agricultural related disciplines. The purpose of this paper was aimed to analyze special requirements, objectives, tasks and implementation environment raised by the rural revitalization strategy, based on reviewing the references and development history of agricultural engineering, and to analyze impacts of the rural revitalization strategies on and demand for the adjustment of agricultural engineering innovation, so that to figure out the ways, means and measures for new round disciplinary adjustments and restructuring of agricultural engineering. In recent years, the disciplinary renovation and restructuring for all subjects have been encouraged and launched by the Ministry of Education, China. The new round adjustment of the discipline layout marked by the innovation and construction of new disciplines such as new engineering and new agriculture were given more attention on introducing new technological and industrial revolution achievements, and transforming and upgrading traditional engineering and agricultural science with information technology, digital technology and artificial intelligence. But it’s worth noting that insufficient attention had been paid to the expansion of agricultural and rural modernization roads and changes in development patterns caused by the rural revitalization in this important adjustment process. Agricultural engineering takes multiple and wide range responsibilities in offering scientific and technological support and talent training and cultivation, so that it plays a special and key role in the modernization of agricultural and rural areas. Information, communication, intelligent and smart technologies, and all new breaking through technologies should be introduced into agricultural engineering to equip and empower it more updated and effectively. Under such a background, more efforts should also be made in such important development consequences brought by the rural revitalization strategy. The disciplinary adjustment of agricultural engineering should be restructured and optimized according to the instructions of the national development strategies and its new application areas required by agricultural and rural modernization. The more attention should be paid to the influence of social and economic development mode and structural adjustment and upgrading on innovation and its correspondence. Great attentions should be paid to following key issues: 1) The implementation of the rural revitalization strategy has opened up some new development spaces for the disciplinary innovation of agricultural engineering and proposed new development requirements. 2) The development and extension of the agricultural engineering technology systems will extend from the agricultural production to rural multi-industrial integration, relying on all agricultural and rural resources. 3) The cultivation of agricultural engineering talents and the construction of educational scientific research systems should aim at the requirements of the whole process for all rural productions, as well for the construction of rural ecological systems. 4) The systematic construction and management of agricultural and rural industries in different regions should meet the needs of the urban-rural integration development and the modernization of new rural communities’ governance system. Currently, more reform, renovations and adjustments should be made to reshape the agricultural engineering to meet new needs of the rural revitalization, the new development fields and directions of agricultural engineering disciplinary innovation currently are more practical in rural e-commerce engineering, rural landscape construction and maintenance engineering, rural new industrial development space construction, rural ecological environment engineering, and rural social and economic management and governance system engineering. [ABSTRACT FROM AUTHOR]