Search

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]

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]

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]

Water resources management in irrigation districts is important to ensure food security. The current water resources management in China focuses on underground water and surface water (i.e. blue water), and precipitation (green water). However, most studies are on large scale such as global or basin scales and few are on irrigation district scale. The aim of this paper was to quantify and evaluate the consumption of different types of water resources in the irrigation district by the concept of water footprint (WF). The maize and wheat production in the Baojixia Irrigation District of Shaanxi in China from 2008 to 2017 were selected as the case study. One hydrological station and two weather stations were included in the study area. Data of runoff, precipitation irrigation and soil-related physical properties were collected. A regional distributed hydrological model (Soil and Water Assessment Tool, SWAT) based on the hydrological cycle was established. The model was constructed by coupling with the soil water balance model and considering the water delivery losses of the irrigation canals. The blue and green water resources and WFs of crop production were quantified. The variability of the annual WFs of crops during the study period was analyzed, and the WFs of crops on daily and monthly scales were also analyzed in three typical years (dry, normal, wet). The runoff data was used to validate the SWAT model, and the MOD16A2GF Version 6 Evapotranspiration product (MOD 16) at a 500 m pixel resolution was used to verify the evapotranspiration simulation results. Then, the change of WF was analyzed. The results showed that the model could simulate well the runoff with the values of R 2 of 0.74, Nash Efficiency Coefficient (NSE) of 0.69 during the calibration period. By validation, the model was still well and both the values of R 2 and NSE were 0.51. It indicates that the model established in this study could accurately simulate the hydrological process in irrigation districts. During the period from 2008 to 2017, the blue and green water resources in Baojixia Irrigation District increased on the whole. The multi-year average blue water resources in Yangling was the highest but the multi-year average green water resources in Jingyang was the lowest. The multi-year average total WF values of maize and wheat (including the blue WF of irrigation delivery losses) were 573 and 779 m3 /t, respectively, showing an overall rising trend. The fluctuations of total WFs were mostly affected by the green WF. The green WF of crop production was higher at the jointing and filling stages and lower at the maturing stage. The WFs of crop production were fluctuated the most on the daily scale and the fluctuation decreased gradually from month scale to annual scale. The fluctuations of the green and blue WFs of wheat were the largest in the dry year. Although the irrigation water in the dry year was lower than the normal and wet years, the unit maize yield and the unit wheat yield were the highest and the total WF values of maize and wheat were the lowest. This study can provide valuable information for crop production and management in irrigation districts.. [ABSTRACT FROM AUTHOR]

There are relatively few studies on the spray quality of citrus tree canopy in China. In most cases, the method is that farmers observe the spray quality of citrus tree canopy up close in the orchard, which wastes manpower and material resources. Moreover, the observation effect is not ideal and may cause harm to human safety. Domestic conditions allow some orchards to judge the spray effect by observing the water-sensitive paper. This method does save a lot of manpower, and efficiency is significantly improved compared with the previous ones. However, this method is affected by the external environment, and the naked eyes cannot correctly determine the spray quality, which will cause certain errors. Therefore, this study explored new ways to solve these problems. In recent years, thermal imaging technology had shown great research promise in some emerging research areas, especially in agricultural production. In the field of precision agriculture, for example, high-resolution thermal imaging cameras, with the aid of advanced aerial photography technology, can quickly capture thermal images of the canopy before and after spray, which provides new ideas for precision agriculture spray detection technology. This study combined thermal imaging technology and computer vision technology to identify and classify the spray conditions of the plant canopy and accurately detected the spray quality of the leaves, which avoided the waste of pesticides and reduced the manual re-examination steps. Thereby reducing agricultural production costs and improving the economic benefits of agricultural products. In this study, the canopy of a citrus tree was used as a thermal image acquisition area. Inevitably, there are problems such as high noise, low contrast, and blurred feature information in the thermal image acquisition process. In response to the above problems, this study preprocessed the acquired thermal images and eliminated unreasonable data, and set the original data set to two labels (sprayed and unsprayed), and divided them into the training set and the test set. An improved SPP-Net-Inception-v4 model based on the Inception-v4 model and the SPP-Net target detection algorithm was proposed to achieve multi-feature fusion to enhance the feature extraction effect. The model took the construction of a sparse network structure to generate dense data as the core design idea. By introducing the Inception and Reduction modules, the feature description bottleneck problem was reduced; further, SPP-Net (Spatial Pyramid Pooling Network) was innovatively connected between the convolutional layer and the fully connected layer pooling network), which aimed to extract fixed-length feature vectors through the pyramid space pooling method to achieve the fusion of multi-scale features and extraction enhancement effect. Compared with the two models of Inception-v4 and ResNet-152, the experimental results showed that the accuracy of the improved SPP-Net-Inception-v4 model test set was 95.07%, which was 1.58% higher than the accuracy of the original Inception-v4 model and 3.26% higher than that of ResNet-152. Compared with Inception-v4 and ResNet-152, the SPP-Net-Inception-v4 model reduced the model size by 13% and 24%, respectively. The SPP-Net-Inception-v4 model could be used to detect the spray quality of chemicals in citrus fruit trees quickly as well as could improve the economic benefits of agricultural production, and would provide a reference for the further improvement of pesticide detection technology in precision agriculture. [ABSTRACT FROM AUTHOR]

Agricultural machinery purchase subsidy is an important agrarian policy, its policy effect has been widely concerned by scholars. However, very few studies have discussed the spatiotemporal difference, agricultural machinery types difference and endogeneity of subsidy’s policy effect. The purpose of the present study is to make policy effect evaluation more accurately, and analyze the spatiotemporal difference and agricultural machinery types difference of policy effect. Different from existing studies, the present study uses a large sample collected from 15 089 observations in 3 287 households at 18 provinces from 2008 to 2018 by China agriculture research system (rapeseed) farmer fixed observation point and employs unbalance panel fixed effect model, panel high-dimensional fixed effects model, Box-Cox model, quantile regression model to calculate the differential policy effects between different year, topographic regions and types of agricultural machinery purchase subsidy on farmer’s agricultural machinery self-investment. In addition, instrumental variables fixed-effects panel-data models, Tobit fixed-effects panel-data models and Heckman sample selection models were used for the robust test. The result showed that 1) On the whole, agricultural machinery purchase subsidy had an obvious incentive effect, effectively promote farmer’s agricultural machinery self-investment, the marginal effect of agricultural machinery purchase subsidy on farmer’s agricultural machinery self-investment was 2.530 8. 2) The effect of subsidies varies significantly between plain and non-plain areas. Subsidy’s marginal effect in plain county was 1.408 5, subsidy’s marginal effect in hill and mountain county was 3.108 2. Subsidy policy was more effective in hill and mountain areas. 3) Generally, subsidy’s incentive effect fluctuated significantly between the years, crowding-out effect was showed in some years. The number of years in which the policy effect declined from the previous year was equal to the number of years in which it rosed from the previous year. 4) On the whole, the subsidy effect was enhanced with the increase of the value of agricultural machinery, and the policy effect was higher for large and medium-sized agricultural machinery. Accordingly, this paper suggested that: 1) In the future, agricultural machinery purchase subsidy should continue to implement. 2) Agricultural machinery purchase subsidy should tilt appropriately to non-plain areas and large and medium-sized agricultural machinery continually. Appropriate R&D subsidies can be given to agricultural machinery production enterprises to research and develop large and advanced machines and suit machines which used in hilly and mountainous areas. Encourage local governments to include large and advanced machines and machines which was suitable used in hilly and mountainous areas into the new agricultural machinery subsidy pilot catalogue timely. Accelerate the transformation and application for new machine products. 3) Adjust or improve the subsidy mode according to the implementation situation and agricultural mechanization development situation. [ABSTRACT FROM AUTHOR]

In the feed industry, through crushing, mixing and conditioning, feedstuffs are pelleted by mechanical equipment to obtain pellet products. In this compression process, the feed material particles are overlapped and staggered with each other, and the granular system is changed from the loose state into the curing bond with squeeze flow and the gap flow occurs synchronously. The mechanism for the pelleting process appears to be a regular relationship of stress and strain and other mechanical properties. Therefore, it is necessary to learn the stress-strain relationship and rheology properties of the feedstuffs during the compression process, and it is of theoretical significance to analyze the forming rules of granules and optimize the pelleting process and equipment. In this paper, based on characteristics and nonlinear properties of wheat as a feedstuff, a nonlinear visco-elasto-plastic constitutive model for characterization of rheological properties was constructed. Based on the experiment, and establishment and verification of the numerical model, the rheological properties such as viscoelasticity and plasticity of the feedstuff were analyzed by the model coefficients, and the influence of material properties and processing parameters on the rheological properties is studied. Also, the relationship between the rheological coefficients of the materials and the quality of the pellet is learned, which provides a new methodology for the study on the compression process of pellet feed. According to the process of pelleting, the factors in compression trials were selected including moisture, particle size (i.e., mesh size) and forming temperature, compression load. During the initial stage of the compression process, air between the particles was extruded by pressure and relative positions of particles are rearranged under the action of the inertial force. With the process progressing, the gap gradually decreases to infinitely small and the relative positions of the particles cease to change significantly, after which the deformation of the material can be considered as caused by its own viscoelastic properties, and therefore the compression process is divided into inertial deformation stage and visco-elasto-plastic compression stage for better description. According to the theory of rheology, the feedstuffs properties exhibited during the compression process are summarized as elastic-plastic, viscous and particle-wall friction, and represented by the strain hardening spring element, Newton viscous dashpot element, and Coulomb friction element, respectively. The elastic modulus shows the flexibility of the elastic element or the difficulty of compression. It turns out that the larger the coefficient, the more difficult the deformation and the stronger the stiffness of the material, which can stand for the strength and deformation properties. The improvement of the plastic strain showed by combined plastic exponent, which is coupled by plastic modulus and strain hardening exponent, indicates that the deformation can be maintained after the removal of the compressive stress, which has a special meaning on the quality control of the pellet feed. The viscous coefficient is mainly characterized by the ability of the particles to be bonded in the process of pelleting, thus reflecting the capacity of the formed pellet to stay stable under external force without significant damage in the current state. Meantime, the frictional loss factor can reflect the characteristics of energy dissipation, which mainly includes the friction and adhesion between the particles or the particles and the die wall. The compression stage was divided into 5 even ranges in order to study the various material properties along with the process. The numerical results of the constitutive model of wheat were obtained under 15% material moisture content, 2. 0 mm mesh size, 80 °C forming temperature and 3 kN compression load, which showed that the determination coefficients (R2) in all stress ranges were beyond 0.99 and the mean relative error values were 3.883%, 1.798%, 2.992%, 1.496%, and 6.721% in the ranges of 1-5, respectively. The comparative curve showed a good fit between the actual test value and model value; besides, the χ2 examination showed that the χ2 values of the data in each range were much smaller than the standard values in the degree of freedom of 130 and the significance of 0.001. Based on the above criteria, this constitutive model possesses a good performance that can be used to characterize the rheological properties of wheat. The constitutive model coefficients and the rheological properties of the feedstuff were characterized by regular changes, which showed obvious stress function: The elastic modulus increased with the increase of stress, indicating the deformation performance of the material was gradually weakened and the overall compressibility of the material decreased step by step to reach the end of forming, and the stiffness increased significantly. The increases of combined plastic exponent showed that the plastic deformation of the material increased gradually with a sudden downside in the last range. The absolute value of the viscosity coefficient increased gradually, which means that the bonding force among the material particles is enhanced with the progress of the forming, and the connection between the particles is strengthened therewith. For the influence of various forming factors, results were showed as follows: The increase in forming temperature can improve the elastic modulus, which means a better compression deformation capacity; with preferable softening, and bonding effect on the compressibility, higher moisture content can improve the combined plastic exponent and viscosity coefficient at the same time; the decrease of the particle size increases the absolute value of the viscosity coefficient, indicating its significant positive effect on the particle bonding force. The correlation relations between the pellet quality index and the constitutive model coefficients show that the pellet density, the pellet forming ratio and the pellet hardness were correlated with the viscous coefficient, plastic modulus, and elastic modulus respectively (P<0.001), which owned the highest correlation coefficients that were all above 0.80, illustrating the close relationship between pellet product quality and feedstuff rheological properties. The nonlinear visco-elasto-plastic constitutive model constructed in this paper can provide a new methodology and perspective for the research of the process of feed pelleting, and provide theoretical basis for analyzing the particle forming characteristics, and product quality from the view of material rheology, which give contribution to the efficient and low-cost pellet production and the improvement of product quality. [ABSTRACT FROM AUTHOR]

The simulation of land use change in mountainous urban fringes is always a difficult problem. Existing methods, based on the traditional cellular automata (CA)-Markov coupling model, to capture and simulate such changes in this special areas suffer from notable deficiencies. In this paper, we explore, based on a case study of a mountainous urban fringe in Southwestern China, the performance of an improved method that combines the traditional CA-Markov model with multi-criteria evaluation (MCE). We develop an MCE based AHP model fitted by constraining conditions and factors in the study area. The MCE output is then used as the input of the CA-Markov model to simulate land use changes in the study area based on three periods (2006, 2011, and 2016). Meanwhile, the simulated results by the traditional CA-Markov model are also obtained. Both land use simulation results (the simulation images) are then compared against the observed land use in 2016 (the existing image in 2016) to examine the performance of the improved CA-Markov method. The results show that: 1) Establishing the missing link between the MCE process and the conventional CA-Markov model using land use suitability maps can significantly improve the performance of conventional CA-Markov model in mountainous urban fringes. The results from the case study show that the overall 93.15% simulation accuracy is much higher than that of the average 80% accuracy from most traditional CA-Markov models used in other similar areas. 2) The case study further indicates that from 2006 to 2016, the areas of cultivated land, garden, woodland, grassland, water body, and unused land in study area are decreasing annually. By contrast, the areas of urban land and rural settlement are increasing. The types with the most changes are cultivated land and urban land. This situation indicates that the rapid urbanization in mountainous urban fringe is still a mode of denotation expansion, in which a large amount of agricultural land, especially cultivated land, is occupied by urban construction. 3) The simulation shows that if the current rapid urbanization rate is maintained, then by 2030, the areas of cultivated land, garden, woodland, water body, unused land and rural settlement will be decreased by 6442.46, 923.53, 3239.17, 72.55, 41.26, 352.07 hm2, respectively. The increased land types mainly include urban land and grassland. We also argue the implications of the findings and suggest areas of further work. [ABSTRACT FROM AUTHOR]

Evolution of cultivated land needs to be clarified in the driving mechanism for the sustainable land use in China. Most studies generally focused on the relationship between the evolutionary data and the driving mechanism in the evolution of cultivated land use. However, research on the drivers of marginal impact is rare, such as the spatial factor density that represented by the POI points. There can be a tipping point of marginal impact, when the quantity reaches a specific region, in the distance to the main road represented by the human factors. In this paper, the marginal effect analysis was used to make a preliminary evaluation, taking Southern Hubei as an example. Landsat remote sensing images were selected for the interpretation data of three periods from the year of 2000-2005, 2005-2010 and 2010-2015, including 15 types of POI spatial data. Firstly, the evaluation system of spatial factors was constructed from three aspects, including Euclidean distance indices, POI kernel density indices and locational indices. The Spatio-temporal evolution of cultivated land was systematically analyzed, together with dynamic change in the area from 2000 to 2015. Secondly, the principal component analysis was used to integrate the driving factors for the change of cultivated land. The extracted principal components were selected to construct the multiple Logistic regression models, including interaction terms. Lastly, an emphasis was put on the bidirectional marginal effect of spatial elements in the driving mechanism, and the change rule that illustrated by the graph of marginal effect. The results indicated that: (1) The evolution types of cultivated land showed the agglomeration of the same type, while the specific conversion type strongly depended on the spillover effect of neighboring land use. There was obvious evolution trend from cultivated land to construction, but others were not, possibly due to the influence from the macro-control policy of land use. From 2000 to 2015, the proportion of cultivated land converted to construction land increased from 28% to 44%, and then jumped to 96%, mainly concentrated in areas around towns and along major roads. (2) Marginal effects of spatial factors depend on types of cultivated land and periods. From 2000 to 2015, there was a gradual decrease in the variation range of marginal effect for different conversion types of cultivated land, while the homogeneous intersection point moved in the same direction for marginal effect curves of different transformation types. The dominated marginal effect of natural location factors was on the conversion of cultivated land to construction land, and cultivated land to water area, when the spatial elements of POI were different values. (3) The curve of spatial factors implied that there was a critical value of marginal effect. In the range of critical values, marginal effect changed significantly with the spatial factors, but outside the range, marginal effect tended to be stable. The qualitative and quantitative analysis on the marginal effect of spatial factors can offer a theoretical reference for the optimization of cultivated land layout, and the formulation of regional coordinated development strategy. [ABSTRACT FROM AUTHOR]

Differential pressure tank is a widely used fertilization device in the application of fertilization in China and many other countries. However, the fertilizer concentration in the tank continuously decays with the inflow of water. The decay feature of fertilizer concentration can easily lead to excessive fertilization at the head and insufficient fertilization at the end of the irrigation system. An analytical solution was proposed in this paper to achieve uniform fertilization based on differential pressure tank with constant fertilizer concentration and flux. The relationship between the uniform fertilization analytical solution and the fertilizer continuity equation was obtained based on differential pressure tank. The analytical solution was expected to control the flux flowing into the differential pressure tank and the flux directly flowing into the irrigation system through the main pipe according to 4 parameters: Uniform fertilizer concentration, initial fertilizer concentration, the volume of differential pressure tank and the total fertilization flux of the main pipe. Based on the analytical solution, the fertilizer continuity equation and the incompressible continuity and momentum equations of water were used for describing the movement of mixture in the differential pressure tank. The numerical model for mixed water and fertilizer flow in the differential pressure tank was determined by experimental data. The fertilizer concentration simulated by numerical model was nearly uniform in the tank and the fertilizer concentration at tank outlet obtained by numerical model decayed with a negative exponential pattern as described by Feng’s theory. The numerical simulation results directly verified the accuracy of the basis of Feng’s theory. The differential equation was also the basis of the uniform fertilization. The mean absolute error between the differential equation and the experimental data was less than 0.041 when the boundary condition of traditional fertilization method was substituted into the differential equation, which indirectly proved the rationality of uniform fertilization method satisfying the boundary conditions of constant fertilizer concentration and flux. The analytical solution’s feasibility in the uniform fertilization process based on differential pressure tank was simulated by the numerical model of fertilizer solution in determining the uniform fertilizer concentration and the fertilization time. The fertilizer concentration at tank outlet simulated by the numerical model decayed almost linearly and agreed with the uniform fertilization analytical solution. The fertilizer concentration simulated by the numerical model at drip irrigation system inlet was almost uniform and in agreement with the analytical solution of uniform fertilization. The relative bias of fertilizer concentration between the analytical solution and computation calculated by the numerical model was less than 15%, which verified the feasibility of uniform fertilization method based on differential pressure tank. The results showed that the application of uniform fertilization method and the uniform fertilization method could basically achieve constant fertilizer concentration and flux based on differential pressure tank. According to the actual product, the relationship between valve opening and time could be obtained in order to realize the control of valve opening process by computer. Approximately 70% to 80% of fertilizer in the normal operation was within range of the excessive or insufficient amount, whereas the uniform fertilization method could effectively avoid the waste of excessive fertilization and the lack of insufficient fertilization. [ABSTRACT FROM AUTHOR]

With rapid development in economy in China the demand for tourism has been changed exerting pressure on tourism resorts to transform and upgrade. As tourism area bears the responsibility of sustaining social and economic development, its land use has to be diversified, leading to a potential land use conflicts. However, there is a paucity of study on that and we attempt to address this knowledge gap. Assuming that a tourism resort should at least have ecological function, productivity and suitability for living (ecological-production-living suitability), we proposed an empirical model to identify and diagnose potential land use conflicts in tourism resorts by taking Wuyishan National Tourism Resort as an example. The potential land use conflict in resort was divided into five zones with different conflicting levels: zone without conflict, zone with mild conflict zone, zone with moderate conflict, zone with intense conflict, and zone with severe conflict. The conflict was divided into four levels: stable and controllable, quite controllable, slightly out of control, uncontrollable. Preliminary studies showed that there were significant differences in ecological-production-living suitability of the land use in this region, revealing existence of competitions and conflicts in land use. The results showed that the areas with land use conflict ranging from controllable to uncontrollable accounted for 17.76%, 35.59%, 22.37%, 23.74% and 0.55% of the whole area. The stable and controllable zone was mainly in the western, southeastern and central regions, and areas in the high-end health resort area, pastoral health resort area and eco-recreational area. The quite controllable zone was mainly in the transition zone from human production areas to the life and ecological protection area, including the waterfront recreation area and eco-recreational areas. The basic out-of-control conflicts were mainly distributed in the intensive activities of human production and life, which had both constructive and destructive conflicts. The serious out-of-control conflicts were smaller in area but deeper in degree. The spatial distribution, expression and conflict degree of potential land use conflict areas determined the conflict governance strategies should also be different. For example, strategies such as spatial control, quality improvement, and functional manifestation could be adopted according to local conditions. The framework of identification and governance of potential land use conflicts in tourist resorts proposed in this paper can accurately reflect the actual pattern of land use conflicts and can provide reference for the land use planning and management in tourist resorts. [ABSTRACT FROM AUTHOR]

Crop yield monitoring and forecast has great impact on food security, ecological environment, and farmers’ incomes. Crop growth and yield monitoring and forecast by using crop growth model has the advantages of clear mechanism, high precision, and high monitoring frequency, but its monitoring scale is usually limited to land block level. Along with the fast development of remote sensing satellite technology, using remote sensing data combined with crop growth model to accurately monitor regional crop growth and yield in a large regional scale has gradually become an important means of regional level and even national level crop growth monitoring. However, due to differences in crop types, climatic conditions, soil conditions and monitoring areas, the regionalization and localization of crop growth model is the major bottleneck of crop growth monitoring by using crop growth model combined with remote sensing data, and it is urgent to conduct targeted studies on the identification of assimilation parameters of crop growth model, pre-processing of meteorological data, and the setting of crop parameters. Based on soil-water-atmosphere-plant model (SWAP), and by taking the major commodity grain production base of China, Northeast China Region as a study region, in this the paper, we conducted a study by taking the major crop of spring maize of the region as its target crop. Firstly, we used Landsat to obtain maize (Zea mays) planting area in the study area, and used it as the basic data for estimating the total maize yield in the study area. The overall accuracy of maize area classification was 93.2%, with R² of 0.951 2. By considering the influence of latitude and altitude on temperature, in the study, we used the coKriging method in crop growth model meteorological data interpolation acquisition, so as to improve the precision of input parameters of the model. The result showed that the average standard error of minimum temperature of coKriging method was 0.31 ℃, while that of the Kriging method was 1.51 ℃. The average standard error of maximum temperature of coKriging method was 0.30 ℃, while that of the Kriging method was 1.14 ℃. In the study, leaf area index (LAI) and evapotranspiration (ET) were used as assimilative remote sensing data sources, and we proposed a novel method to adjust the LAI product of MODIS to make it closer to actual value. By optimizing maize irrigation and crop emergence date, we obtained spatial distribution result of maize yield of the study area of 2013. The monitoring result was compared with the statistical data. The R² reached 0.939 4, with RMSE of 148 065 t, and MAE of 114 335 t. Moreover, the correlation coefficient of predicted yield and statistical yield reached 0.724 5, with RMSE of 598.5 kg/hm², and MAE of 531.5 kg/ hm²。The study result showed that, using SWAP model, taking meteorological data spatial interpolation results obtained by using coKriging method as input data and assimilation of LAI and ET remote sensing, can effectively conduct corn yield remote sensing monitoring of the study region, which provided reference for the remote sensing monitoring and forecast of crop growth and productivity of the region. [ABSTRACT FROM AUTHOR]

Ample sunshine, together with scarce rainfall and large variation in diurnal temperature, makes Xinjiang a unique place for producing tasty red jujube in China. Grading is an important parameter for storing and processing the jujube to maximize its market value, and needs to measure its volume and surface area. Traditional methods for measuring fruit volume are spheroid-like to measure the volume of water the fruit displaces when being immersed into water, with the surface area measured by peeling or slicing. These methods are inefficient and cannot be used for real-time measurement. The aim of this paper is to present a real-time multi-contour model to estimate the volume and surface area of the red jujube. We assessed the effect of contour angles, projection heights and diameters on the ultimate results. In the proposed method, 2D images of the targeted jujube were captured on a rotating circular table using a camera, and the contour of the images was then extracted using image processing. A 3D multi-contour model was developed based on the extracted 2D contour, and it was then used to estimate the volume and surface area of the targeted jujube. The result showed that the diameter of the target estimated by the multi-contour sphere model did not change, and that with an increase in the relative errors between the contours angle and the projection height, the volume estimated by the model increased (with the minimum relative error being 6.0%) while the error of the estimated surface area decreased (with the minimum being 1.0%). The angle between the contour and the projection height in the multi-contour sphere model had a prescribed value, and the relative error of the volume and surface area estimated by the model varied with the diameter in that the smaller the diameter was, the bigger the errors were. The average mean square error and the average relative error of the volume and surface area estimated by the model were 2.45 cm³ and 10.2%, and 3.65 cm² and 7.09%, respectively. An increase in grading appeared to increase the average relative errors of the estimated volume but had no noticeable impact on other factors. In summary, the multi-contour model for real-time measuring the volume and surface area of the red jujube offers an alternative to grading the jujube although further improvement is needed to reduce the errors. [ABSTRACT FROM AUTHOR]

China has the third largest coal reserves and the first coal consumption in the world. China's coal resource areas are highly coincident with major grain producing areas or ecologically fragile areas. Under high-intensity mining, overburden strata move violently and surface damage is serious. The large-scale exploitation of underground coal resources will inevitably cause the destruction of surface attachments such as cultivated land, and disturbance of ecological environment in mining area, which will seriously affect the sustainable development of mining area. The surface damage induced by high-intensity mining includes static damage and dynamic damage, but the dynamic damage is more serious. Surface subsidence velocity can reflect the severity of surface movement and deformation. So, in this paper, we chose subsidence velocity as the dynamic deformation index to reveal the dynamic development law of surface damage induced by high-intensity mining in mining area. First, we took the field observed data of ground movement observation station set on the side of terminal line of 2407 working area as an example, and selected several periods of data in the full mining stage as samples. Through the analysis of mathematical statistics, we concluded that the subsidence velocity curve has the distribution characteristics of right skewness. Second, we established a physical similarity model test according to the mining and geological conditions of 2407 working area. Combined with this experiment, we found that the average of bedrock break angle was 56°, which revealed the formation mechanism of stepped crack. Under high-intensity mining, the bedrock was full-thickness fractured along the break angle of bedrock, the main failure type of loose layer was shear failure and the direction of failure was upward in the vertical direction. When the failure reached the surface, the stepped crack appeared on the ground surface. According to the analysis of the measured data of 2407 working area, it was found that overlying strata and surface had the periodic failure characteristics along the advancing direction of working area under high-intensity mining, the period of roof caving was the same as that of stepped crack, and the maximum subsidence velocity was located at stepped crack. The position of maximum subsidence velocity can be determined by the break angle of bedrock in real time. Then, we selected the lognormal density function with right skewness and normality, and combined with the real-time location distribution characteristics of maximum surface subsidence velocity to construct the dynamic prediction model of subsidence velocity. The reliability of the dynamic prediction model was analyzed by selecting the field measured data of subsidence velocity from adjacent high-intensity mining working face of Bulian Tower coal mine. The results showed that the correlation coefficient between predicted data and measured data was over 0.9, and the ratio of standard deviation to measured maximum subsidence velocity was less than7.0%. It showed the high reliability of the model. This research can provide guidance for dynamic prediction of mining subsidence in similar mining conditions. [ABSTRACT FROM AUTHOR]

As the basic means of agricultural production, cultivated land plays an irreplaceable role in ensuring food security and promoting social and economic development. With the enhancement of urban interactions in space, the land use conflicts between urban development and agricultural protection have been intensified due to the diversified land demands caused by population agglomeration, industrial restructuring and infrastructure construction. Exploring the impacts of urbanization on cultivated land change has become a hot issue in China at present. Most of current studies have paid increasing attentions to the relationship between the growth of individual cities and cultivated land occupation, and few of them attempted to reveal the driving factors of cultivated land change from the perspective of spatial interaction of cities. Urban agglomeration is the main form of new urbanization in China. It is crucial to identify the distribution of cultivated land change and its driving factors from the perspective of urban agglomeration. In this paper, we measured the spatial connection of urban agglomerations based on the gravity equation and the urban flow intensity model, and then explored influencing factors of cultivated land conversion at the scales of individual cities and urban agglomerations during the period of 2005-2015 using a multilevel linear regression model. The research results show that the area of cultivated land in the major urban agglomerations has dropped sharply by 17 572.8 square kilometers in the decade from 2005 to 2015. The situation of cultivated land protection is grim. Then it shows significant scale effects and regional heterogeneity of cultivated land change in urban agglomerations. At the urban scale, the change of cultivated land is positively correlated with agricultural population, industrial economy and agricultural science & technology development, whereas negatively correlated with the growth of foreign investment and the expansion of construction land. At the scale of urban agglomeration, both indicators of spatial connection have a negative correlation with cultivated land change. Moreover, remarkable regional differences of influencing factors of cultivated land change exist between coastal and inland China. Comparing the regional differentiation of the degree of influence of outward functional forces, it can be found that the spatial interaction of coastal urban agglomerations has a more positive effect on the protection of cultivated land than the inland urban agglomerations with relatively backward development, and the negative impact is also smaller than that of inland urban agglomerations. The comparison with other models verified the effectiveness of the multilevel linear regression approach to reveal the influencing mechanism of cultivated land change on different scales. And the result of null model has proved the necessity and rationality in the research perspective of spatial interactions between cities. As a word, the strengthening of spatial interaction in urban agglomerations under rough development will obstruct the protection of cultivated land. In this case, controlling industrialization and urbanization reasonably, concerning the scale effects and regional heterogeneity, improving laws and regulations, correcting the rough development path, and improving land use efficiency might be the critical roads to relieve conflicts between development of urban agglomerations and protection of cultivated land. [ABSTRACT FROM AUTHOR]

Tomato has become the most cultivated and consumed vegetable crop in the world, and China has become one of the largest producers and consumers of tomatoes in the world. The pectin content in cell wall of tomato during ripening is closely related to fruit hardness, which is one of the important indicators to determine the maturity and reflect the quality of tomato. The requirement of tomato maturity classification and evaluation promotes the development of non-destructive, fast and accurate detection methods of tomato hardness.Hyperspectral imaging integrates spectroscopy and imaging technology in an analysis system, which transfers tomato maturity assessment from subjective, manual classification and measurement methods. Hyperspectral imaging has been widely used in the rapid acquisition of information to classify, detect or identify the quality of various fruits. A novel method for tomato hardness detection based on hyperspectral imaging and modified interval Random Frog was proposed in this paper. Firstly, hyperspectral images of 120 tomato samples in different mature periods were captured by hyperspectral imaging system covering near-infrared region (865.11nm-1 711.71nm). And the hardness data of tomato was obtained by texture analyzer. Secondly, the spectral data were pretreated by multiplicative scatter correction (MSC) and normalized preprocessing to eliminate noise and improve signal-to-noise ratio. The validity of the characteristic wavelength plays a crucial role in the prediction performance of the model. Therefore, we need an effective method to extract the effective wavelength to improve the accuracy of the model. Interval random frog (iRF) algorithm considers all possible spectral wavelengths and ranks all the wavelengths based on selected probability. But one of the disadvantages of this method is large number of iterations and slow convergence. In view of above disadvantages, the traditional iRF algorithm was optimized in terms of constructing initial variable subset method. A modified interval Random Frog (miRF)was proposed to extract the characteristic wavelength effectively. Finally, a prediction model was developed based on partial least squares regression (PLSR) method to detect tomato hardness. The results indicated that the convergence efficiency and accuracy of miRF has a significantly improvement compared with the iRF method. The iRF has selected 100 feature bands, accounting for 40.65% of the full band, and its runtime was 32.1min. miRF has selected 47 feature bands, accounting for 19.1% of the full band, and its runtime was 1.6 min. It can be seen that miRF greatly reduces the running time of the algorithm. The characteristic wavelengths selected by iRF and miRF methods were mainly distributed in 1 582 nm-1 655 nm, followed by 1 160 nm-1 190 nm and 1 353 nm-1 383 nm, indicating that above regions were sensitive bands to tomato hardness. In order to prove the effectiveness of the proposed algorithm, the results of miRF-PLSR were compared with those of iRF-PLSR and SPA-PLSR. The prediction set correlation coefficients (RP) of the SPA-PLSR model and the iRF-PLSR model were 0.803 9 and 0.936 6 respectively. And the RP of miRF-PLSR model was 0.968 5. The root mean square error (RMSEP) of the SPA-PLSR model and the iRF-PLSR model were 0.007 7 kg/mm2 and 0.004 4 kg/mm2respectively. And the RMSEP of miRF-PLSR model was 0.004 0 kg/mm2. The experiments results show that the miRF-PLSR model has the best prediction results in all models. [ABSTRACT FROM AUTHOR]

Alfalfa plays an important role in dairy farms for economic and ecological reasons in northwest China. In order to manage the complex relations between alfalfa growth and environmental issues accurately and timely, the alfalfa simulation model has been widely studied. An alfalfa growth simulation model based on water and nitrogen factors (ALFSIM-WN) was proposed. The model was divided into 3 sub-models, including crop dynamic sub-model, water balance sub-model and nitrogen balance sub-model using modular design method. It took alfalfa in Ningxia irrigation area of Yellow River as research object and could simulate the growth dynamics of alfalfa under different water supply and variable fertilization. It also could estimate the yield of alfalfa. In order to verify the accuracy and applicability of ALFSIM-WN, experiments were carried out at grassland experiment area of Maosheng Grass Limited Company in Yinchuan (northwest China, 3855N, 10606 E). The experimental alfalfa was Medicago sativa No.7. The irrigation methods included surface irrigation and subsurface drip irrigation. A split plot was designed as 2 experimental treatments. The 1st treatment was the irrigation amount which was divided into 5 irrigation levels including the surface irrigation (1 199 mm) and the subsurface drip irrigation (525, 600, 675, 750 mm). The 2nd treatment was nitrogen application rate which included 4 nitrogen application levels (0, 60, 120, 180 kg/hm2). A total of 17 treatments were designed in experiment. Different irrigation levels were carried out in batches according to different cuts and different growth period of alfalfa. Different nitrogen application levels were carried out in different cuts. Through 2 years experiments (2016-2017), model parameters had been determined using data from 2016, and growth parameters of alfalfa (such as growth period, leaf area index, soil moisture dynamics and yield) had been predicted based on gathering meteorological date, soil data and field management data of 2017. The comparison between simulated and observed was taken in this paper. The results showed that the simulated values by the model was in agreement with the trend of the observed values under different irrigation and nitrogen treatments, such as growth period, leaf area index, soil water content and yield of the alfalfa. Alfalfa in Ningxia irrigation area of Yellow River could harvest 3 to 4 times per year, the mean relative error of the growth period of alfalfa in 4 cuts simulated by the model was between 1.9% and 5.7%, which was consistent with the local growth period for forage. In addition, through analyzing the 4 cuts data in 2017, the mean relative error of leaf area index simulated by the model was between 2.3% and 17.6%, the mean relative error of soil water content simulated by the model was between 2.3% and 17.6%, and the mean relative error of yield simulated by the model was between 1.7% and 16.2%. The root mean square error of the leaf area index was between 0.09 and 0.44, the root mean square error of soil water content is between 0.009 and 0.039 cm3/cm3, and the root mean square error of yield was between 0.3 and 2.3 t/hm2. Therefore, the ALFSIM-WN had higher simulation accuracy in simulated growth period, leaf area index, soil water content and yield, indicating that the model has good application in Ningxia irrigation area of Yellow River and can be used as an effective simulation tool for alfalfa growth in forage planting. [ABSTRACT FROM AUTHOR]

In order to study the coupling relationship between rural population and rural residential land area change and promote the economization and intensification level of rural residential land, in this paper the Tapio decoupling model was introduced to reveal the decoupling degree of rural population-land change. From the perspective of urban and rural demographic shift, the factors decomposition model for rural residential land expansion was established. The logarithmic mean Divisia index (LMDI) was adopted to quantitatively analyze the influencing factors accounting for the changes in rural residential land area. The change of rural residential land area was decomposed into 4 main driving effects including rural residential land intensive use effect, urban-rural population structure effect, urbanization effect and total population effect. The addition decomposition method was used to measure the magnitude of 4 driving effects. The rural residential land area of China (1996-2016) and 31 provinces or municipalities (2000-2016) were taken as example. The results show that China has experienced rapid urban-rural transformation in the past few years. Rural population continues to decrease, presenting a 30.7 percent decline. But in the meantime, the total area of rural residential land increases continuously. The changes in rural residential land area among different provinces (municipalities) varied obviously, and overall the eastern and western regions indicated a greater growth. The relationship between rural population and rural residential land change is uncoordinated, and rural residential land tends to be more extensively utilized. From the decoupling index of China and 31 provinces or municipalities, the decoupling relationship between rural population and residential land area change were mainly characterized by strong negative decoupling. The degree of negative decoupling in the eastern and western regions was more serious than that in the central areas. What's more, the degree of negative decoupling is generally deteriorating. The values of 4 driving effects were measured from 1996-2016. The results indicated that the scale of rural residential land in China increased by 2.020×105 hm2 from 1996 to 2008 including a decrease of 116.833×105 hm2 caused by urban-rural population structure effect, and the increase of 33.497×105, 71.813×105, 13.544×105 hm2 for rural residential land intensive use effect, urbanization effect and total population effect, respectively. Additionally, during 2009-2016, the scale of rural residential land in China increased by 7.275×105 hm2. The rural residential land intensive use effect, urbanization effect and total population effect caused the increase of 36.689×105, -68.271×105, 32.164×105, 6.692×105 hm2, respectively. Among 4 driving effects, the urban-rural population structure effect was stronger than the others. The contribution of 4 driving effects to the change in rural residential land area in different periods performed differently. The value of urbanization effect was greater than that of rural residential land intensive use effect during 1996-2008, but after 2009, the rural residential land intensive use effect gradually exceeded the urbanization effect, and become the dominant factor caused the increase of rural residential land. Therefore, strengthening the planning and management of rural residential land, gradually promoting rural residential land consolidation, and actively exploring the exit mechanism of rural residential land may be effective measures for improving the intensification level of rural land use. [ABSTRACT FROM AUTHOR]

In order to obtain the precise physical parameters of the discrete element simulation model of typical cultivated soil clay loam in southern China, this paper constructed a soil discrete element simulation model. Based on a soil accumulation test, this study proposed a method for combining the significance analysis and response surface method, which calibrated and optimized the simulation parameters of clay loam in southern China. Combining the results of actual test and GEMM database parameters recommended by constructing the DEM model of the soil, repose angle of soil was taken as response value, using the Design Expert software through the Plackett-Burman test, the steepest climbing test and Box-Behnken test, simulation physical parameters were calibrated and optimized. The simulation model of discrete element in clay loam was verified to be accurate by analyzing the simulation and soil bin testing of hole forming device. The DEM model of soil was established on the basis of the parameters determined by the basic test. The 8 initial physical parameters were screened for significance using the Plackett-Burman test. The results show that: the surface energy of soil for JKR model, soil-soil restitution coefficient, and the soil-soil static friction coefficient have significant effects on the response value and repose angle. Based on the optimal interval value of the significant parameters are determined by the steepest ascent test and the Box-Behnken test result, the quadratic regression model of significance parameters and repose angle is established and optimized to obtain the optimal combination of the significance parameters: The surface energy of soil for JKR model is 12.73 J/m2. The soil-soil restitution coefficient is 0.55. The soil-soil static friction coefficient is 0.84. Other insignificance parameters are as recommended by the GEMM database (Poisson's ratio of soil is 0.38. Soil-soil rolling friction coefficient is 0.1. Soil-steel restitution coefficient is 0.3. Soil-steel static friction coefficient is 0.6. Soil-steel rolling friction coefficient is 0.1). By the analog simulation of optimal parameter combination, it can be obtained that the simulated repose angle is 42.9° and the measured repose angle is 42.4°, therefore, the relative error is only 1.2%. There is no significant difference in shape and relevant value between the soil in simulation and the soil in experiment (P>0.05). The optimized parameters can be used for further DEM analog simulation between the clay loam and the soil-contacting components and revealing the law of motion of clay loam under the action of soil-contacting components. The results of the simulation and soil bin testing of hole forming device show that, motion law of the soil-engaging component in the simulated soil model is slightly different from that in the soil groove test, with the numerical difference within 3.98%, which proves that the soil simulation model after parameter calibration and optimization can accurately replace the real soil for simulation. The research can provide theoretical basis and technical support for the dynamic study of the interaction between this type of soil and the contact soil components. [ABSTRACT FROM AUTHOR]

As a large agricultural country, China has abundant straw resources, and the annual output of corn stalks is 3 billion tons. Corn straw could be used as silage after mechanized processing, it could effectively alleviate the current shortage problem of animal feed. At present, the research on kneading and crushing of corn straw mainly focused on physical experiment, but less on numerical simulation. Therefore, the lack of effective numerical simulation method in the crushing process of corn straw and the improvement efficiency for the structure of processing equipment is reduced to some extent. Based on the above background, in this paper, a discrete element model for bimodal distribution of corn straw was established based on discrete element method, which was originally applied to the field of geotechnical mechanics. This process included setting particle size, filling geometric model, obtaining particle group coordinate information and so on. All of the numerical simulations were carried out in EDEM 2018 version, and users were allowed to customize the settings. Then the parameters calibration for the bonded particle contact model of corn straw was carried out that combined with physical experiment and virtual experiment. The mechanical parameters were obtained through compressing and shearing experiments of corn stalk samples. This parameter could provide basis for theoretical calculation of bonded particle model parameters of corn stalks. The mechanical properties of bonded particle model were determined by 5 parameters: normal stiffness coefficient, tangential stiffness coefficient, normal critical stress, shear critical stress and bonded radius which could be obtained through theoretical formula calculation. In the virtual experiment, the corn stalk model was subjected to axial compression experiment and radial shear experiment, respectively. The final BPM (bonded particle model) parameters were determined by the phenomenological simulation method which was compared physical experiment and virtual experiment. Finally, the discrete element model of corn straw was simulated and verified by physical experiment. This process involved the kneading and crushing simulation of corn straw model, classifying the types of materials and weighing the mass of materials, and using API plug-in to realize particle replacement and adding bonded particle model in the simulation process. After the simulation was completed, the change of bonded number and the shape classification of broken materials were analyzed. The whole research results showed that the maximum critical loads were 2,260 N and 110 N, respectively when the straw was compressed and sheared at a loading rate of 5 mm/min; After calibrating the parameters of bonded particle model, it was found that the normal stiffness coefficient, tangential stiffness coefficient, critical normal stress, critical tangential stress and bonded radius were 9.60×106 N/m, 6.80×106 N/m, 8.72 MPa, 7.5 MPa and 2 mm, respectively. At this time, the mechanical properties of the discrete element model were close to the harvested corn straw that had a moisture content of 87.8%. After the simulation, material could be divided into four types: short type, standard type, long type and incomplete crushing type. At the same time, the simulation mass of 4 materials were 5.2, 5.8, 8.2 and 8 g, respectively. After the physical experiment, the mass of different types of materials were respectively 4.8, 5.3, 7.6 and 9.1 g. The deviation of the mass for different materials were 8.3%, 9.4%, 7.8% and 7.7%, respectively. The mass deviation for different types of materials between the physical experiment and virtual experiment was kept within 10%. This research could not only prove that it was feasible to establish corn straw model by discrete element method and simulate the kneading and crushing process, but also provide guidance for kneading other straws. [ABSTRACT FROM AUTHOR]

Conservation tillage is an important measure to promote the sustainable agriculture. No-tillage sowing in straw-covered fields is an advanced farming technology of conservation tillage system, which has been widely used in northeast China because of its many advantages, such as saving production cost, protecting soil and ecological environment. However, due to the long growth cycle of corn, the straw is stronger and harder to rot. During the harvest operation in autumn, corn stalks are usually crushed by combine harvesters and scattered on the ground, but the length of the stalks crushed is inconsistent and the distribution is uneven on the ground. During the sowing operations in spring, the crushed straws are not rotten in the field, the surface flatness is relatively poor, and the sowing operating environment is worse. No-tillage finger-type precision planter is widely used in straw mulching for seeding, the above problems results in the random vibration excitation of the no-tillage planter during the operation is significantly enhanced, which seriously affect its performance, such as affecting the working quality of planters, reducing the seeding yield and uniform plant distribution, and ultimately reduces crop yields. In this paper, in order to study the vibration characteristics of 2BMZ-2 corn no-tillage finger-type precision planter and the influence of vibration on the seeding performance of corn finger-type precision seed metering device, the vibration characteristics model of the planter was established and the steady-state vibration response was solved. The vibration characteristics of the planter worked in straw mulching were measured and analyzed by field test. Based on the above theoretical analysis and field test results, a test bench for vibration seeding was built, which was used to simulate the vibration environment of the field operation and to test the influence of mechanical vibration on the performance of the seed metering device. The three-dimensional space trajectory of the falling seed was measured and analyzed by the high-speed photography and target tracking technology. The results showed that the vibration characteristics of the planter were mainly determined by the working speed, the surface of field, the soil conditions and the structural characteristics of the seed metering device. The field experimental results showed that when the working speed was in the range of 5 to 9 km/h, the vibration frequency distribution of the seed metering device vibration energy was mainly concentrated in the low frequency range of 3 to 11 Hz; the greater the working speed was, the larger the vibration acceleration was, but the vibration frequency distribution of vibration energy was not affected. The bench comparative test results showed that the mechanical vibration had no significant effect on seed filling performance of the seed metering device, but had significant effect on seeding qualified rate, coefficient of variation of spacing in longitudinal direction and coefficient of variation of spacing in transverse direction. The multi-factor quadratic general rotation combined test results showed that rotational speed, vibration acceleration and vibration frequency were the main and secondary factors influencing the uniform stability of seed arrangement, reducing the vibration acceleration can improve working quality of the seed metering device more than reducing the vibration frequency. The single factor experiment showed that, in the range of vibration frequency of 3 to 11 Hz, vibration acceleration of 0.3g to 1.5g and rotational speed of 31.5 to 57 r /min, the increase of each test factor made the seed falling trajectory and the seed falling points more discrete, and increased the range of seeding. In addition, increase the rotational speed made the position of seed falling point gradually away from the initial position of seed. The results can provide guidance for the design of the vibration-damping system of the corn finger-type precision seed metering device and corn no-tillage finger-type precision planter. [ABSTRACT FROM AUTHOR]

With the continuous development of the economy and society, the problem of air pollution in China is becoming more and more serious especially in Hebei Province. Currently, Hebei Province has been one of the most serious areas of air pollution in China. The wind-blown dust, emitted from the earth’s surface to the atmosphere, has become one of the main components of air pollutants. The wind-blown dust has significant impacts on atmospheric phenomena and consequently on air quality. The wind-blown dust not only causes atmospheric pollution, but also changes the radiation balance of the ground and the acidity or alkalinity of the aerosol. It not only affects human health but also causes changes in the global climate system and ecosystem. In order to evaluate the PM10 of atmospheric pollutants in Hebei Province caused by wind-blown dust, the article set up parameters system of wind-blown dust production by Community Land Model 4.5 (CLM4.5) using remote sensing data, the ground meteorological data, the Land Data Assimilation System data and the land surface characteristic parameters production data with 1 km spatial resolution. The factors affecting the wind-blown dust include soil texture, wind speed, soil moisture, surface roughness, and the proportion of bare soil determined by vegetation coverage, surface freezing ratio, snow cover ratio, lakes and wetland ratio. Wind speed, soil moisture, vegetation coverage, snow cover area and freezing ratio change greatly with the seasons, so they are the sensitive factors of the wind-blown dust. This study provides the first estimates of the fine-scale spatial and temporal distribution of dust emissions from Hebei Province. The result shows that: The wind-blown dust annual emission flux of PM10 is 1.02 t/hm2 in 2013. The highest monthly emission flux is 0.28 t/hm2 in March, accounting for 27.6% of the whole year, and the lowest is July, accounting for only 0.2%. The dust emission flux of spring is 0.55 t/hm2, the summer is 0.015 t/hm2, the autumn is 0.18 t/hm2, and the winter is 0.28 t/hm2. That shows spring is the highest season and summer is the lowest season for wind-blown dust emission flux. There are obvious regional differences about wind-blown dust emissions in Hebei Province, the coastal plain of Cangzhou and Bashang plateau are the highest areas for dust emission flux, annual emission flux of which is 5.365 and 3.542 t/hm2 respectively, and Taihang Mountain piedmont plain is the lowest area, annual emission flux of which is 0.20 t/hm2. The result above shows CLM4.5 wind-blown dust model can well simulate the characteristics of spatial and temporal change in Hebei Province. Comparing the initial data of CLM4.5 with our study data, it presents the spatial resolution of initial data is very low, and not suitable for the simulation of the small area, in contrast, the local parameters we used including vegetation coverage, wind speed, soil moisture, the proportion of bare soil, lakes and wetland ratio data with high spatial resolution (1 km) have improved the accuracy of the simulation result. This paper is not only meaningful for evaluating the PM10 from wind-blown dust in Hebei Province, but also the first application to estimate wind-blown dust in the fine scale by CLM4.5 model. [ABSTRACT FROM AUTHOR]

The Yellow River Delta Nature Reserve (YRDNR) is a national nature reserve designed to protect the newly built wetland ecosystem and the rare and endangered birds. It is one of the fastest growing coastal wetland ecosystems around the world and an important site for red-crowned cranes during migration and wintering periods. It is an urgent task to effectively manage and control resource utilization activities and protect the wetland habitat of red-crowned cranes in the YRDNR. Spatial optimization model can be applied to a variety of spatial planning problems to identify trade-offs between conflicting objectives and solve the optimum allocation problem (such as allocation of reserve sites or management actions). In this paper, we firstly had a secondary development with C++ language to construct a land use pattern spatial optimization model based on LUPO (land use pattern optimization) model developed by Annelie Holzkamper et al. The LUPO model can be applied to identify trade-offs between habitat conservation of red-crowned cranes and sustainable development of community economy in the nature reserve, and to optimize allocation of land use in YRDNR. Secondly, we designed 3 target-driven scenarios according to management requirement in YRDNR to balance ecological protection and economic development. Finally, we simulated the spatial optimization of land use pattern in YNRDR under the 3 scenarios by integrating the scenarios into the LUPO model. The results showed as follows: 1) Under Scenario A, it obviously achieved the ecological conservation target with a 30% increase of suitable habitat area of red-crowned crane by converting the areas of reed ponds and mudflats to seepweed tidal flats and Chinese tamarisk-seepweed tidal flats, which are the birds preferred habitats. However, the regional economic benefit had a small increase of only 11%; 2) Under Scenario B, it achieved 54% regional economic growth by converting the area of farmlands, reed ponds and mudflats to shrimp ponds, which owned a highly economic value. In the meanwhile, the habitat area change of red-crowned crane was not obvious, and became more fragmented in Scenario B; 3) Under Scenario C, it achieved the target of 24% suitable habitat area expansion of red-crowned crane along with 41.3% regional economic growth. It may mainly respectively result from significant expansion of seepweed tidal flats and shrimp ponds converted from mudflats and farmlands. In conclusion, it is more reasonable and practical under Scenario C than Scenarios A and B in YNRDR due to the fact the trade-off between wetland habitat conservation and sustainable development is comprehensively considered. We consider that our LUPO model can offer a good technique support for habitat protection of red-crowned crane and wetland landscape management in YRDNR. However, we also recommend a further secondary development of LUPO model to improve the accuracy, feasibility and operability of the model in the future. [ABSTRACT FROM AUTHOR]