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Purple soil which riches in mineral nutrients and is the main farming soil in Southwest China. Purple soil color images collected by machine vision have complex background, including crops, weeds, scattered small soil blocks and surface soil because of its stochastic field scenes. In order to avoid the interference of background on further processing and recognition of purple soil with machine vision, it is a primary task to segment the purple subsoil region from its background adaptively. Clustering algorithm has achieved good results in image segmentation and is widely applied. However, the selection of parameters of some classical clustering algorithms are sensitive, which need to be manually set and cannot satisfy to the adaptive segmentation of purple soil. Thus, aiming at the problem of adaptive segmentation, a segmentation methool of purple soil color image based on adaptive density peaks clustering was proposed in this paper. The specific segmentation algorithm was as follows: firstly, in order to calculate the density peaks conveniently and increase the separability between soil region and its background, a color to gray transformation method was carried out. The entropy-based similarity matrix was constructed, then the optimization model based on maximizing the between-class variance and minimizing the withinclass variance criterion was established with the similarity matrix. The optimization model was solved to obtain the gray matrix, which enhanced the separability of the gray value for clustering. Secondly, in the light of the shortcomings of density peaks algorithm, the density formula was improved and a measure was designed to determine the clustering centers adaptively, which realized the adaptive segmentation of purple soil region with the clustering algorithm based on the density peaks clustering framework, and improved the initial segmentation accuracy. Finally, post-processing algorithms of boundary extraction and region filling were designed to remove both the discrete small soil blocks in the background area and the internal voids in the soil area of the image obtained by initial segmentation. Therefore, the purple soil region image could be completely obtained and the segmentation accuracy of soil region was improved. From purple soil color images collected by machine vision in the field, 60 images with normal illumination, no surface soil and no shadows around the subsoil were randomly selected as normal test images and divided into 20 groups.we picked out randomly 60 images with the characteristics of normal illumination, then another 60 images were randomly selected as robustness test images, which were characterized by scattered subsoil and some shadows around the topsoil. These images were divided into 20 groups. The results of contrast test showed that the proposed method could automatically segment the purple soil color images of normal test and robustness test. For 60 normal test images, average segmentation accuracy of the proposed algorithm were 93.45%, which were 11.54, 7.96, 3.16 and 0.85 percentage points higher than that of FRFCM (fast and robust fuzzy C-Means) algorithm, H-threshold algorithm, DPC (density peaks clustering) algorithm and DFDPC (data field based density peaks clustering) algorithm, respectively. For 60 robustness test images, average segmentation accuracy of the proposed algorithm were 87.40%, which were 11.75, 5.2, 12.47 and 3.09 percentage points higher than that of FRFCM algorithm, H-threshold algorithm, DPC algorithm and DFDPC algorithm, respectively. The results proved that the proposed algorithm in this paper was superior to the other four comparison algorithms. Furthermore, boundary extraction algorithm and region filling algorithm further improved the average segmentation accuracy of soil region, in the post-processing stage. In the final exact segmentation results, average segmentation accuracy of normal test images were 96.30%, with average time-consuming of 0.36 s，and average segmentation accuracy of robustness test images was 91.63%, with average time-consuming of 0.35 s. In conclusion, the proposed algorithm was effective, and it can provide reference for the segmentation and extraction of purple soil region from the computer vision image. [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]

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]

The change process of cultivated layer quality for slope farmland at plot scale is influenced by the interactive effects between erosive rainfall and artificial farming activities at different temporal and spatial scales. For a slope surface, there exists a successive erosion process of rainfall-runoff-infiltration and the consequence is first reflected in the quality of cultivated layer. Among the factors induced the erosion process at plot scale, terrain is an important factor because it could redistribute the ratio of rainfall--infiltration, which directly cause a different erosion process for an erosive rainfall and the different degradation degree during a rainy season and a growth season. Taking purple soil slope farmland as an example, the paper firstly analyzed the varying characteristics of cultivated layer quality of slope farmland, then quantitatively evaluated the effects of four terrain factors, altitude, slope angle, effective soil thickness and slope position on cultivated layer quality and their sensitivity of impact, adopted principal component analysis and evaluation model. The results indicated: 1) Such soil properties as cultivated layer thickness, soil organic matter and soil bulk density of cultivated layer were all within the suitable scope and soil nutrient properties were generally at middle & low levels. The variation coefficients of soil bulk density and soil total porosity showed weak variability (CV<10%), presenting 7.97% and 8.36% respectively and the other soil properties showed moderate variability. 2)Minimum data set for cultivated layer quality evaluation of purple soil slope farmland consisted of eight soil parameters, bulk density, penetration resistance, soil organic matter, clay content, cultivated layer thickness, soil shear strength, saturated water conductivity and bioavailable phosphorus. Soil physical properties are more important than chemical properties except soil organic matter for erosion control and crop growth of slope farmland. Evaluation based on the MDS revealed that the cultivated layer quality varied spatially over the slope, being 0.458 in the low part of the slope, 0.443 in the middle part of the slope and 0.417 in the upper part of the slope and the quality value of the lower slope was 3.39% and 9.83% higher than that of the middle slope and upper slope positions, respectively. 3) The factors affecting cultivated layer quality divided into four types: slope-angle impacted type, slope location impacted type, effective soil layer thickness impacted type and altitude impacted type and they accounted for 38.89%, 22.22%, 14.81% and 24.08% of the total samples taken from slope farmland respectively. The slope angle was the main determinant of cultivated layer quality because it could induce directly many ecological processes at plot scale. The slope angle and effective soil layer thickness could be modified by such soil and water conservation measures as terrace, biological ridge and soil improvement methods. But the slope location and altitude could not be modified easily only by selecting suitable crop system. 4) The quality of cultivated layer had positive correlation with its thickness and location in the slope, and negative correlation with altitude and slope angle. Sensitivity analysis revealed that the determinants were ranked in the order of altitude (-0.399) > location in the slope (0.192) > slope angle (-0.112) > effective soil layer thickness (0.110) based on their impact on cultivated lay quality. These results could provide some useful evaluation parameters and its regulating direction for cultivated layer quality, which contributed to the sustainable utilization of purple soil slope farmland. Furthermore, other samples of slope farmland should be studied in order to find out the critical values of MDS according to 2 functions of cultivated layer, erosion control and soil productivity. [ABSTRACT FROM AUTHOR]

In order to study the characteristics of microplastics and its response relationship with mulching years, irrigation methods in the farmland soil of Hetao Irrigation District, field sampling and indoor experiments were used in combination for in-depth study. This paper mainly analyzed the current situation of plastic film mulching in Hetao Irrigation District by considering the effects of mulching years (5, 10, 20 a) and irrigation methods (drip irrigation and surface irrigation under film mulching). The abundance, type, color, particle size and other distribution characteristics of microplastics in the farmland soil were analyzed and other microplastic surface features and attachments also were observed and discussed, which was supported by scanning the electric microscope and energy spectrometer. The results showed that the average abundance of microplastics in soil under the different mulching years (5, 10, 20 a) in Hetao Irrigation District was 2 526.00, 4 352.80, 6 070.00 pieces/kg. The maximum microplastic was 2133.50 pieces/kg in every layer of soil appeared at 0-10 cm soil layer by mulching 20 a, and the minimum microplastic was 678.00 pieces/kg at 20-30 cm soil layer by mulching 5 a. The average annual increasing rate of microplastics was 14.46% in the early stage (5-10 a), while the increasing rate in the later stage (10-20 a) was 3.95%. The abundance of soil microplastics was affected by different plastic-mulching years and irrigation methods. The abundance of microplastic in drip irrigation farmland was slightly larger than the surface irrigation farmland, and it decreased with the increase of soil depth. By further analysis, the major categories of microplastics were fibers (23.34%), fragments (26.31%), films (38.57%) and grains (11.78%); the colors of microplastics included black, transparent, green, red, blue, etc., with the proportions 24.56%, 23.83%, 19.34%, 16.52% and 15.75% respectively. In the 0-10 cm soil layer, the main color of microplastics was black and it accounted for 30.25% of the total microplastic; in the >10-20 and >20-30 cm soil layer, the main color of microplastics were transparent, accounted for 30.15% and 29.23% of the total microplastic. The particle size exhibited a downward trend with the increase of the mulching years, and the majority of particle size less than 1 mm. In addition, with the increase of mulching years, microplastics particle size in >0-10, >10-20, >20-30 cm soil layer was gradually decreased, and there was no significant relationship between size and irrigation method (P>0.05). The surface features of microplastic samples were rough and irregular pores existed on it, and fiber, thin film and fragments microplastics had regular micropores, while the grain microplastic surface pores were irregular and concave. The porous properties of microplastics in soil made the characteristic of greater specific surface area carried by it. This characteristic could increase the adsorption of other pollutants and microorganisms from the soil; and there were stable iron oxides and rare earth elements on the surface. The research is of great significance to clarify the distribution and harm of microplastics in the soil of the Hetao Irrigation District. [ABSTRACT FROM AUTHOR]

The investigation site is located in Jinggouxing watershed (from 26°10′31″N to 26°12′33″N and115°9′3″E to 115º11′39″E) in the north of Gan County, Jiangxi Province, China. The soil type is mainly red soil developed by granite. The collapsing gully area is 95.8 hm², which belongs to the intensity erosion area of the hills and mountains in the south of Jiangxi. Due to the sudden, violent, serious damage, and difficult to manage characteristics of collapsing gully, it has severely affected the local ecological environment and residents' lives, so it has become an important research direction for soil and water conservation. Collapsing gully is affected by hydraulic and gravity erosion. Among them, the hydraulic erosion of collapsing gully is mainly affected by surface runoff. The instability of the collapsing gully wall gradually increases through the undercutting effect of runoff, and then develops under the combined action of hydraulic and gravity erosion. Soil infiltration is the premise and basis of surface runoff. By analyzing the infiltration characteristics of collapsing gully soil, we can further understand the process of soil erosion by collapsing gully soil. In recent years, the disc infiltration meter has been widely used to determine soil hydraulic characteristics due to its fast and easy operation. In this paper, a disc infiltration instrument was carried out under four pressure heads (-9, -6, -3, and 0 cm) on the collapsing gully soil at three different developmental stages (initial stage, active stage and stable stage) and three parts (catchment, slope and channel). The basic physical and chemical properties of collapsed hills at different developmental stages were studied, and the correlation between the developmental stages and parts of collapsing gully to the basic physicochemical properties was analyzed. The variation of soil infiltration rate with different infiltration heads at different developmental stages and parts of the collapsing gully was plotted. According to the measured values of soil hydraulic conductivity and Gardner's constant α, the effects of collapsing gully at different developmental stages and their parts on the soil hydraulic conductivity and soil pore classification contribution to flow were analyzed. The results showed that soil infiltration properties were affected by soil sand content, pressure head, soil pore size distribution, soil erosion and space parts. The higher the sand content in the soil, the more severe the soil erosion would be, which would affect the soil infiltration characteristics. When the pressure head was 0, the stable infiltration rate at the collapsing gully in the developmental stable period was the highest, 1.01 and 1.40 times higher than that in the collapsing gully at the initial stage and active stage of the collapsing gully. With the decrease of the pressure head, the stable infiltration rate of the soil in the three different developmental stages gradually decreased. The soil hydraulic conductivity of different parts of the collapsing gully was basically similar under different pressure head conditions. There was no significant difference in soil hydraulic conductivity and Gardner's constant α at three different developmental stages. Except for the hydraulic conductivity at a pressure head of -9 cm, the soil hydraulic conductivity and the Gardner constant α values at different parts of the collapsing gully were significantly different. As the degree of erosion increased, the contribution rate of macropores to flow at different developmental stages increased. The parts of collapsing gully significantly affected the contribution rate of macropores, mesopores 2 and micropores to flow, it could be seen that the part of collapsing gully was an important factor which affected the hydraulic properties of soil. The results could provide some references for the soil erosion process of the collapsing gully soil at different developmental stages in the southern china [ABSTRACT FROM AUTHOR]

In order to solve the problems of high resistance and high power consumption of rotary tillage and land preparation, the rotary blade is studied based on theoretical analysis, simulation and field experiment in this paper. First, a wedge drag reduction rotary blade is designed based on the theoretical force model of cutting tools in mechanical soil dynamics. Second , the three-dimensional model of the national rotary blade and the wedge drag reduction rotary blade is established by using the Inventor software and the simulation experiment is carried on. The cutting soil model of 2 kinds of rotary blades is established by using HyperMesh software, and the material parameters, boundary constraints and working parameters are defined. On this basis, the soil cutting process, stress and cutting resistance are analyzed. It is proved that the wedge drag reduction rotary blade design is reasonable. In order to verify whether the wedge drag reduction rotary blade meets the strength requirement, the stress of the rotary blades is analyzed, and the cutting resistance of the national rotary blade and the wedge drag reduction rotary blade are compared. Third, field comparative experiments are carried out on national rotary blade and wedge drag reducing rotating blade with the evaluation indexes of torque, power consumption and soil breakage. The results show that the cutting resistance of the wedge drag reduction rotary blade is smaller than that of the national rotary blade; the maximum stress of the national rotary blade is 35.68 MPa and the maximum stress of the wedge drag reduction rotary blade is 29.49 MPa, which is less than that of the national rotary blade and far less than the yield strength of the material 430 MPa. On the premise of ensuring the strength of the blade body, the weight of the wedge drag reduction rotary blade is reduced by about 50 g, which is about 8.3% lower than that of the national rotary blade. The maximum cutting resistance of the national rotary blade is 530 N, the average cutting resistance is 375.5 N, and the maximum cutting resistance of the wedge drag reduction rotary blade is 510 N, the average cutting resistance is 335.5 N, the average cutting resistance of the wedge drag reduction rotary blade is 10.65% lower than that of the national rotary blade, which proves the feasibility of the wedge drag reduction rotary blade designed; The average torque of the wedge drag reduction rotary blade is 11.35% lower than that of the national rotary blade. In the working process of rotary blades, the average power consumption of the national rotary blade is 74.2 kW, the average power consumption of the wedge drag reduction rotary blade is 67.3 kW, and the average power consumption of the wedge drag reduction rotary blade is 9.29% lower than that of the national rotary blade. The average breaking rate of soil of the national rotary blade is 75%, and the average breaking rate of wedge drag reduction rotary blade is 79%, which is 4% higher than that of the national rotary blade; After continuous 33 hm2 tillage, rotary blades did not break, and the average wear of the national rotary blade is 98.5 g, the average wear of the wedge shaped drag reduction rotary blade is 97.3 g, the wear difference is 1.3%, and the wear degree is the same. The wedge drag reduction rotary blade can effectively solve the problems of high resistance and high power consumption of rotary blade, which is helpful to accelerate the development of arable land machinery, improve the mechanization level of cultivated land, and reduce the production cost of crops. [ABSTRACT FROM AUTHOR]

As the largest distribution area of black soil in China, Heilongjiang Province is undertaking important responsibility of food safety for country. However, due to lack of protection, it has become one of those regions undergoing the most serious soil erosion and is gradually losing its basic role of important agricultural production. Soil erodibility index (K-value) is not only an important parameter for evaluating soil's sensitivity to erosion and forcasting soil erosion process but also a key foundation for monitoring and planning of soil and water conservation. In this paper, in terms of soil census data, the characteristics of K-value were analyzed by traditional statistical and geostatistical methods. Results showed that: 1) The soil texture presented significant difference among main soil types; the contents of coarse silt, fine powder and clay obeyed normal distribution, and their spatial correlations were weak. 2) The average K-value of aeolian sandy soils was the largest (0.0281), that of albic soils was the smallest(0.0234), and all K-value of main soil types had weak variability. 3)The average K-value of sandy loam was the largest (0.0281) while moderate clay had the smallest K-value(0.0201). Generally, the average K-value reduced with the increasing physical clay content as well as the decreasing physical sand content, and all soil textures had weak variability but for heavy clay having moderate variability The difference of soil texture either in same soil type or among different soil types was effected by their components content, and this difference was also reflected in K-value. 4) There was a significant linear relationship (R²=0.83) between the average K-value and soil surface thickness and furthermore, the K-value would gently descend when the thickness increased. In other words, the thinner top soil resulted from soil and water loss can cause the increasing K-value and amplify the probability of soil erosion. Thus, the top soil would become thinner and thinner and even disappear. 5) The K-value's distribution characteristics of the areas with various soil erosion types showed obvious difference, however, those regions belonging to same soil erosion type had similar distributions although they were in different soil erosion intensity levels. In water erosion region, the distribution area of different K-values showed an increasing trend in the section from 0.0220 to 0.0241, and got the largest area in the interval from 0.0241 to 0.0245 while a decreasing trend occurred in the zone from 0.0245 to 0.0276. Generally, the distribution area of K-value increased with the increasing of K-value in wind erosion region. The K-value of freezing-thawing erosion region converged in the zone from 0.0258 to 0.0268, and the K-value of engineering erosion region was centered in the zone from 0.0229 to 0.0245. 6) The K-value had a moderate spatial correlation, and showed a gentle linear downward trend from the west to the east, as a distribution of concave parabolic shape occurred in north-south direction. In addition, the maximum K-value mostly appeared in the area of aeolian sandy soil, and the two minimum K-value areas were almost related to the areas of black soils and albic soils, respectively. We also found the distribution features of K-value coincided with the soil and water conservation regionalization well. The K-value grid database produced in this paper would provide basic parameters for soil erosion monitoring and prediction, and controlling of soil and water loss, especially provide scientific basis for the protection and restoration of black soil resources, and impose a positive effect on sustainable grain production safety in the black land. It was necessary to note that the data used in this work were a little old and their soil profile samples were not collected randomly, and thus this shortage of the data may make our results less reliable. Besides, since we lacked newer data, we didn't further analyze relevant spatial and temporal dynamic changes of K-value. [ABSTRACT FROM AUTHOR]

Combined with the current research progress and shortcomings on spatial distribution characteristics and scale effects of soil properties, using a combination of variogram theory, spatial autocorrelation theory, multi-fractal theory and other methods from the aspects of the spatial variability of soil properties and the structure, the paper gradually revealed the spatial distribution characteristics of SOC (soil organic carbon) and its scale effects under 4 kinds of scales. The results showed that: Ratio of nugget to sill of SOC under 15, 25, 35 and 45 km scales were 61.78%, 42.65%, 49.98% and 39.34%, respectively, which showed a moderate spatial correlation. The spatial correlation from high to low was 45, 25, 35 and 15 km in turn. Except the 15 km scale, the spatial variability caused by random factors including representative measurement error and the micro-scale process, was less than the structure variance, namely the ratio of nugget to sill was less than 50%, the structural factors were dominant, and spatial variability from the random part showed a decreasing trend with the scale increasing. The variation function couldn't be described with discrete characteristics (i.e. spatial negative correlation), which was also impossible to make a significant test for variable range. As the separation distance increased, the Moran index decreased from full positive to negative, then the positive and negative values alternately occurred, and eventually the values turned out to be negative totally. Nearer positive correlation distance represents the spatial correlation distance, which is the first cross point of positive and negative conversion under different scales, and were 1 607, 7 520, 8 649 and 9 053 m for 15, 25, 35, and 45 km scale. With the scale increasing, the spatial correlation distance increased, and compared to the change range in the semi-variation function, it became smaller with varying degree under different scales except 15 km scale. The greater the scale, the greater the total spatial autocorrelation. The order for standardized statistic under different scales was 15 km < 45 km <35 km < 25 km, which increased firstly and then decreased with the scale. All random scale accounted for less than 5%, and on the whole each scale had good spatial structure. The multidimensional fractal parameter value under 25 km scale was the largest, indicating that the SOC content in this scale was mainly concentrated in a dense area. The magnitude of variation of Rayleigh dimension of SOC under 4 kinds of scales was consistent with that of width of multidimensional spectrum. The spatial distribution of SOC is a typical fractal dimension. Multifractal method is a tool for describing the spatial heterogeneity of SOC. It can reveal the scale variation characteristics of spatial heterogeneity of SOC. No matter what kind of scale, specific value of the measured value based on the Mkrige method agreed well with the predicted value, and the coverage ratio of specific value was above 85%. Spatial distribution characteristics of SOC were deeply revealed through combining variation function, spatial autocorrelation, multi-fractal and Mkrige method from spatial variability, spatial correlation and spatial structure in research area. The results can provide a method to the research on the spatial distribution characteristics of SOC in relatively flat agricultural region. However, due to the different combinations of artificial and natural factors, the spatial variability, correlation and structure will vary with scale change. [ABSTRACT FROM AUTHOR]

In this paper, the experiment area is dry and prone to soil erosion, in order to stop slope runoff and promote rapid vegetation restoration, a restoration program was implemented. So it is significant for grassland ecological construction to study on the effects of ecological restoration measures on soil properties and soil quality. A study had been done to investigate the different of 0-40 cm soil depth of soil properties and assessment of soil quality under different restoration measures in typical steppe grassland in Ningxia. We selected the sites that has been subject to enclosure(FY), contour trench(SP), fish-scale pits(YL), which were implement in 2001 and grazed(FM) (as a reference, traditional grazing with some supplement) grassland. The results showed that: 1) Soil bulk density of grazing grassland was the highest (P <0.05) whereas the soil clay content, field water holding capacity and total porosity were the lowest (P<0.05), and there was no significant difference (P > 0.05) in soil physical properties between enclosure, contour trench, and fish-scale pits grassland. 2) Soil organic matter and total nitrogen were the highest (P < 0.05) in enclosure grassland, followed by grazed grassland, and the lowest in contour trench. The content of total phosphorus was higher (P = 0.05) in grazed and enclosure grassland, but was the lowest (P < 0.05) in contour trench grassland. The available K content was the highest in grazed grassland the lowest in fish-scale pits grassland (P<0.05). The content of available N was highest in enclosure grassland but lowest in contour trench grassland which were 161.75 mg/kg and 77.17 mg/kg respectively (P<0.05). 3) Soil sucrase and urease activity showed FY>SP>YL>FM; protease and phosphatase activity both showed the highest (P <0.05) in enclosure grassland and the lowest (P <0.05) in the fish-scale pits grassland; the bacteria, actinomycetes and fungi were varied in each treatment; the amount of microorganisms showed FY>FM≈SP>YL whereas microbial biomass carbon and nitrogen showed FY>YL≈SP>FM (P<0.05). 4). As a whole, soil bulk density was negatively correlated with other indexes, and negatively correlated with clay content, field water holding capacity, total porosity, sucrase activity, urease activity, microbial biomass carbon and microbial biomass nitrogen (P<0.01). There was a significant positive correlation between soil organic matter, total nitrogen and available nitrogen (P<0.01) and the correlation between soil enzyme activity and soil microbial population (P<0.05). Soil capillary porosity (except soil microbial biomass nitrogen) and available potassium were not correlated with other indexes (P>0.05). 5) The comprehensive score of soil quality evaluated by the membership function factor analysis method was: enclosure> grazed> contour trench>fish-scale pits grassland. In summary, the enclosure grassland was more conducive to the restoration of typical grassland. Based on the study of the effects of enclosure, contour trench and fish-scale pits on the soil physical and chemical properties and biological traits, the membership quality of soil under different restoration measures was evaluated by membership function and factor analysis and can provide the basis for the ecological construction of typical grassland in Ningxia. The results showed that the enclosure was the most beneficial to the restoration of soil quality in degraded grassland in the study area. [ABSTRACT FROM AUTHOR]

In the last several decades, the problem of food shortage has been one of the main challenges in the world. It is necessary to enhance the use of protected agriculture in order to promote better microclimate conditions allowing high productivity, stable quality, earliest harvest dates and thus better economic output and good environment quality and food security. However, there are pests and pathogenic bacteria in the soil of agriculture production systems due to an ideal temperature, no wind and high humidity conditions in soil. Then soil disinfection treatments are used in agriculture before planting high-value cash crops, to reduce soil-borne crops pests including bacterial, fungal and nematode pathogens, weeds and insects. Methyl bromide fumigation is the widely used as a disinfection method due to its low cost and high effectiveness. But gaseous methyl bromide may destroy stratospheric ozone. Hence, forthcoming agro-ecological techniques should both reduce pollution hazards and be compatible with sustainable development guidelines. Many other chemical fumigants have become strongly restricted and more ecological treatments are now been sought. Alternative sustainable techniques such as soil electrical disinfection, steam soil disinfection and flame soil disinfection are utilized. However, many of these methods have the major drawbacks of their effect strongly depends on fossil energy. Moreover, the employment on a large scale of these methods could lead to a strong increase in environmental pollution. For this reason, in this paper, we presented a novel concentrating regeneration type solar soil extermination and sterilization device, which used high temperature air to kill soil-borne crop pests, reducing the employment of chemical fumigants and improving the quality of agriculture products. The device consisted of trough compound parabolic concentrating system, soil feed system, soil and air regeneration system and forced draft system, et al. The operational principle of concentrating light and regeneration type solar soil extermination and sterilization device was introduced. A 3D model of the concentrator supported with optical analysis software was used to analyze the tracking accuracy. The distribution of the concentrated light of the absorber could be visualized. Based on the simulation results, an experimental set-up, which can be used to verify the heat collection efficiency and the heating temperature, was designed and constructed. The results indicated that the overall ray's receiving rate of the trough compound parabolic concentrating collector of 99.66%-62.20% were obtained with radial incidence angles of 0°-7°. The outlet air temperature of the device increased with the decreasing the air flow rate. The maximum outlet air temperature of the device at the air flow rate of 1.075m/s was higher than that of the device at the air flow rate of 4.076 m/s by 70 ℃. Under good sunshine in winter, the outlet air maximum temperature of the device with the tracking accuracy of 5°and the concentrating rate of 3.6 can reach to 88 ℃, and the heat efficiency can reach about 65%, thus, it is able to provide enough heat to soil disinfection in the protected agriculture, which is an idea solar soil extermination and sterilization method for protected agriculture. [ABSTRACT FROM AUTHOR]

Rice is cultivated in large area in Heilongjiang Province. The area of rice cultivation in Heilongjiang is about 100 thousand hectares. For a long time, rotary or shallow ploughing is the main tillage mode of paddy soil. Rotary tillage depth is usually 8-10 cm, and shallow ploughing is 12-13 cm. Long term shallow ploughing has the following problems. First, it makes plough pan layer move upward, which leads to the shallower tillage layer and the rise of the plow bottom. With the reduction of effective space for roots growth, roots cannot absorb nutrients from deep soil and the soil nutrient supply per unit area will decrease. Second, it easily leads to rice lodging in late growth stage due to the shallow rooting zone. When the roots are hindered by the plough pan layer, they cannot grow vertically and only extend horizontally, which results in a decrease in the ability to support stems. The more roots in the deep soil, the stronger the ability of roots to fix the soil, and the stronger lodging resistance. Shallow ploughing leads to a decrease in the soil nutrient supply per unit area. In order to meet the growth of crops, a large amount of fertilizers have to be applied, especially nitrogen, which can cause late maturing rice, lodging and losses in yield. Third, soil aeration and water permeability are impeded by the plow bottom, the air in the upper and lower soil layers is not in circulation. As long as the soil is in the reduction state, it is easy to form reduced iron, manganese as well as reduced gases such as H2S, which results in rice roots poisoning and a reduction of yield. The results of the survey for rice cultivation in Heilongjiang area showed that the topsoil thickness of high-yield cropland soil is generally 15-17 cm, and the plough layer thickness is 7-8 cm. the medium-yield cropland soil is generally 12-15 cm and 8-10 cm, and low-yield is 8-10 cm and greater than 8-10 cm, respectively. In Honghe farm, long term production practice concluded that the yield of 20 cm deep ploughing was 10% higher than that of 8-10 cm. In order to clarify the effects of deep ploughing on soil physical and chemical properties and rice yield, in this paper, we carried out the research of large area contrast of deep tillage, shallow tillage and rotary tillage by use of the independent developed deep plough of paddy field. The results showed that shallow and deep ploughing can reduce soil solid ratio and bulk density. The soil solid phase ratio was 0.74%-4.80% and 1.86%-3.90% lower than rotary tillage respectively. The soil bulk density respectively decreased by 0.09 g/cm3 and 0.08 g/cm3 in the 10-20 cm soil layer. The soil bulk density of deep ploughing was decreased by 0.03 g/cm3 than that of rotary tillage in the 20-30 cm soil layer. Compared with rotary tillage, the soil permeability coefficient and saturated permeability coefficient of shallow ploughing were increased by 4.04 and 2.71 times in the 10-20 cm soil layer, respectively, those of deep ploughing were 4.42 and 2.14 times, and those of deep ploughing were 1.86 and 2.87 times in the 20-30 cm soil layer. In two years, the change trend of soil aeration coefficient and saturated permeability coefficient was consistent. Deep ploughing can promote the growth of rice roots. The increase of root growth amount and length was 6.53-16.33% and 10.81-21.62%, respectively, and deep ploughing is better than shallow. Deep ploughing increases the yield of rice. In 2015, shallow and deep ploughing in rice yield increased by 6.91% and 9.81%, respectively compared with rotary tillage, and by 6.59% and 7.84% in 2016. The trend of increasing yield was consistent in two years. [ABSTRACT FROM AUTHOR]

Rapid lower-cost detection methods for soil macronutrient, including soil samping, sample pretreatment and nutrient determination, are urgently needed. In this paper, a prototype soil rapid pretreatment device was introduced for the ion-selective electrode (ISE) based in-situ soil nitrate-nitrogen detection. Necessary pretreatment steps of soil weighting, extracting and filtration were achieved in the integrated device. The mechanical structure of the device was composed of 4 major components, including a two-dimensional work bench, a high-speed centrifuge, a liquid pump and a self-designed electric control unit. The two-dimensional work bench was built with a vertical sliding table and a rotary table. On the purpose of eliminating the “suspension disturbance” of ISE, the centrifuge was used to obtain the clear soil extract solution. The peristaltic liquid pump, which conducted the quantitative injection of the soil extractant solution into centrifugal tube, was involved for the soil extractant injection and stirring. The electric control unit consisted of a microprocessor of STM32F103 and its interface circuit, which was used for the precise control of the two-dimensional work bench. The soil moisture sensor was applied to reduce the interference of soil water content. Net weight of the testing sample could be calculated. According to the testing results, the displacement accuracy of the vertical sliding table was less than 0.1 cm, while the root mean square error (RMSE) and mean relative error (MRE) were less than 0.04 cm and 0.4% respectively. The one-way displacement of 10 cm consumed less than 5 s. The accuracy of the angular movement for the rotary table was 1°. The rotating speed was calculated through the ratio between rotation angle and time, which could reach 10°/s. The two-dimensional work bench possessed good repeatability with the coefficient of variation (CV) of less than 0.40%. The accuracy of the liquid pump was also evaluated. Two injection volumes of 12.5 and 25 mL were selected. A volume accuracy of 0.2 mL was obtained. The RMSE, the MRE and the injection time were examined to be 0.07 mL, 0.24% and 13 s, respectively. The continuous injection operation possessed a high repeatability with the CV of less than 0.1%. Therefore, the extractant injection performance was verified to be reliable and accurate. The performance of the self-designed device was estimated in the nitrate-nitrogen detection of wet soil. Comparisons were conducted among 3 groups of ISE-based detections and the standard spectrometric detection. The 3 groups of ISE-based detections included the fast pretreatment group, the soil suspension group and the conventional pretreatment group. The fast pretreatment group was processed by the self-developed pretreatment device discussed above. Samples of the soil suspension group were prepared without filtration operation. The conventional pretreatment group was conducted under the national site-specific soil testing recommendation. Compared with the standard spectrometric detection, the poor detection accuracy with the biggest absolute error (AE) of 76.86 mg/kg was determined in the soil suspension group. The slope of regression equation was 2.27, which indicated a non-negligible deviation from the real condition. As expected, the ISE detection, conducted by the self-designed device, was much closer to the standard spectrometric. The adjusted determination coefficient (R2) of the regression equation was 0.87 and the equation slope was 1.31, which was less than 2.27 obviously. The average AE was decreased to be 20.97 mg/kg. The RMSE of 22.34 mg/kg was found. Meanwhile, the labor intensity was greatly reduced. However, the fast pretreatment group still exhibited the obvious difference with the conventional pretreatment group. In all, the device discussed in this study demonstrates a promising result, which might provide references for the ISE applications of in-situ soil macronutrient rapid detections. Further modification on the mechanical structure for extracting is required to enhance its performance. [ABSTRACT FROM AUTHOR]

Soil surface roughness is one of the important indices commonly used to describe soil hydrological characteristics and Lambert characteristic. In microwave quantitative remote sensing application, it affects the microwave scattering values and therefore impacts the accuracy of soil moisture retrieved using microwave sensing data. Therefore, measuring soil surface roughness has become one of the research hotspots in the field of microwave remote sensing. Two kinds of techniques are used to calculate soil surface roughness, including contact method, such as the pin meter and profile meter, and non-contact method, such as ultrasonic measurement, laser scanning, three-dimensional photography, infrared measurement and radar measurement method. All these methods need some special device. The development of image processing technology and the popularization of digital camera provide a simple measuring method which only needs a reference whiteboard and a camera. However, the detailed scale information commonly used on the reference whiteboard increases the requirements for data acquisition and data processing. The purpose of this study is to provide a method to obtain the soil surface image with a simplified reference whiteboard and then to measure soil surface roughness in the presence of field environmental noise. Therefore, a simple image acquisition method is introduced and then an image processing method combining the neural network and the decision tree is proposed. The neural network is built to detect image edge points. To reduce the environmental noise effect, the input characteristic parameters of the neural network are selected carefully, which include not only gradient information, but also image direction and neighborhood consistency information. The cutting of the background section on the original image based on image edge detection result improves the computing speed effectively. A decision tree model is introduced to divide image segments into 4 classes including soil, whiteboard, reference square and vegetation, which are not easy to classify correctly using other classification methods. Considering the effects of weeds and light which are inevitable in field environment, the decision criteria of decision tree integrate the texture and color information. The texture information used is the entropy, the correlation and the first-order invariant central moment, while the color information includes gray value and a component value in Lab color space. To assess the effect of the proposed method under the conditions of different illumination and with different line widths of reference square (1 and 2 mm), 6 photos taken at 11:00, 15:00 and 18:00 on September 14, 2014 are used to measure soil surface roughness. Experiments show that the proposed measuring method combining the neural network and the decision tree can calculate soil roughness from the complex field photos efficiently. The error of root mean square height error can be controlled under 5%, and the calculation error of correlation length less than 1%. Considering the photo-taken distance and the illumination condition, the width of 2 mm for reference square on the whiteboard will be more suitable for high-precision soil roughness measuring. The method proposed in this paper is easy to understand and easy to implement. Its accuracy which can meet the requirement of soil surface roughness measuring makes it widely applicable. The suggestion based on experimental results will further improve the measuring accuracy for soil surface roughness. [ABSTRACT FROM AUTHOR]

The cluster-cluster aggregation (CCA) model bridges the study of colloid aggregation by computer simulation and laboratory experiment. Two distinct and limiting regimes of irreversible colloid aggregation have been identified by computer simulation with the CCA model. One regime is diffusion-limited cluster aggregation (DLCA) corresponding to the rapid colloid aggregation. The other is reaction-limited cluster aggregation (RLCA) corresponding to the slow colloid aggregation. The simulations of the two regimes are both start with N non-overlapping identical particles distributed randomly in a cubic box with side-lengths of L. A three dimensional array, hypothetically named Cube[L][L][L], was usually used to represent the cubic box. Each particle in the cubic box occupies an element of the three dimensional array and are labeled with a different integer. When particles and/or clusters collide and aggregate, all particles in the resulting cluster are modified with the same label (one of them). The progression of Brownian movement and aggregation are realized by updating the labels of the corresponding array elements. However, a critical issue in this kind of simulation is how to efficiently distinguish all of the particles in any selected cluster only based on the three dimensional array Cube[L][L][L] when the cluster is to be moved. Similarly, there are difficulties in the process of collision detection to locate all neighboring positions of the cluster. The traditional method must perform exhaustive search in the whole system, what's more, this kind of exhaustive search will repeated over and over again in the simulation progression. In this paper, the traditional on-lattice CCA algorithm is optimized by improving the storage structure to reduce the time complexity, in which the simulation system is represented by a three dimensional array, while the clusters in the system are simultaneously stored by the linked lists respectively in programming. Another one dimensional array Cluster[N] is used to organize the linked lists and store the basic attributes of the clusters in the system. Initially, N linked lists, each only has one node, are created for the N randomly placed particles. After a cluster is moved, its particles is examined to determine whether any other clusters have been contacted via nearest neighbor occupancy. If aggregation does occur after the collision detection, the simple operation is to link the corresponding clusters. After an aggregation, the array Cluster should be indexed simultaneously because there may be some vacant linked lists. In the later random selection for the potential movement, these vacant linked lists should not be in the candidate lists. For the indexing, a one dimensional array Index[N] is used to store the non-vacant linked list subscripts of the array Cluster[N]. The current length of the Index is the number of the remaining clusters in the system. For example, if the new generated random number for the random selection is k, the label of the next moving cluster should be Index [k], and the linked list of this cluster is exactly linked by Cluster [Index[k]]. From this entry, all the particles in the cluster can be easily accessed. And then, the positions of the six neighboring boxes of each particle in the cluster can also be accessed by the element subscripts of the array Cube, which is needed for the collision detection. Brownian motion, collision detection and aggregation as the basic operations in the CCA simulation are all improved based on the compounded data structure. The results show that the new algorithm achieves linear time complexity from three cubed time complexity. This is a great contribution for researchers in large scale simulation of fractal aggregation. [ABSTRACT FROM AUTHOR]

Numerous evidences show that alternate partial root-zone irrigation (APRI) could save large amounts of irrigation water without significant yield reduction. In addition, intensive studies indicated that APRI could reduce nitrate leaching and increase the chance of nitrogen being absorbed by plant. However, all these studies could not discriminate the fate of nitrate in different soil layers under APRI. The fate of residual nitrate in specific soil layers and its regulation by different forms of nitrogen fertilizers (nitrate- or ammonium-nitrogen fertilizer) under APRI were studied in this paper by means of soil column experiment with labeled nitrate-N (K15NO3) applied to 10-20 cm or 40-50 cm layers. The results showed that compared with conventional irrigation, APRI saved 34.31 percent of irrigation water without significant yield reduction. Nitrate-nitrogen fertilizer improved nitrogen absorption by tomato plants to an extent of 27.0 percent, thus increasing plant growth and tomato yield. The rate of 15N absorbed by plant decreased significantly as 15N was labeled to deeper soil layer. The absorption of 15N by plant decreased 33.1 percentage for conventional irrigation and 23.0 percentage for APRI when the 15N-labeled layer decreased from 10-20 cm to 40-50 cm. Nitrate nitrogen supply promoted absorption of residual nitrate in soil profile to an extent of 53.9 percent compared with ammonium nitrogen supply by promoting tomato root growth and biomass accumulation. The leaching of soil residual nitrate from 10-20cm layer was more intensive than from 40-50 cm layer during tomato growth. For the soil columns with 15N labeled to the 10-20cm layer, the remaining rate of 15N in the 10-20cm layer was 2.7 and 23.1 percentage, the 15N accumulation peak moved downward 30cm and 10cm, and 15N accumulated in the 0-100cm soil layer took account of 60.9 and 75.2 percent of total 15N amount introduced by K15NO3, with loss rate 17.0 and 5.17 percentage, respectively, for conventional irrigation and APRI. However, for the soil columns with 15N labeled to the 40-50cm layer, the remaining rate of 15N in the original labeled layer was 38.1 percentage, whereas under APRI, 15N accumulation peak moved upward 10cm with 61.3 percent of 15N moved to 0-40cm layer, leading to 15N accumulation in 0-100cm soil 24.2 percent more than the conventional irrigation and a large extent of reduction of 15N loss. Compared with ammonium nitrogen supply, nitrate fertilizer promoted plant growth and thus 15N uptake, leading to a lower 15N accumulation after plant harvest in the top 100cm soil. However, there was no significant difference in 15N loss between soil columns fertilized with ammonium nitrogen or nitrate nitrogen. These results suggested that APRI could reduce soil residual nitrate leaching, and promote residual nitrate in deeper soil move upward, thus increasing the chance of being utilized by plant. Different forms of nitrogen fertilizer affect the fate of residual nitrate in soil profile through affecting plant growth. [ABSTRACT FROM AUTHOR]

In the arid area after long-term drip irrigation, the accumulation of soil salinity in the crop root zone and its farming availability have attracted a lot of attentions and concerns from researchers, which was also an important factor to limit the agricultural production and affect the oasis ecological stability and the sustainable application of drip irrigation. In this paper, we try to reveal the trend of soil salinity evolution in the root zone with the long-term drip irrigation based on a four-year (2009-2012) sentinel surveillance in five typical farmlands of Xinjiang drip irrigation district (Paotai County, Shihezi City, Xinjiang) where the drip irrigation under mulch was applied. The drip irrigation under plastic film in these five cotton fields has been respectively started from 2008, 2006, 2004, 2002, and 1998. And the conditions of these five cotton fields including the soil texture, structure, irrigation and fertilizer regime, cotton variety and planting pattern were basically the same, except their drip irrigation history (2-5, 4-7, 6-9, 8-11 and 12-15 years). Since 2009, the drip irrigation has been carried out and continually run until 2012. Na+, Ca2+, K+, SO42-, Cl-, HCO3- and Mg2+ were the major ions in these fields, and changes of their contents in the root zone inside the film with years of drip irrigation were analyzed. The results indicated that the salt content of the root zone soil (0-60 cm) under the plastic film in the drip irrigation cotton fields decreased along with the increasing year of drip irrigation in Xinjiang arid oasis region under the current irrigation regime. The decrease of total salt content was notable for the 1st-4th years irrigation, while it became slowly during the 5th-7th years with an average salt content less than 5 g/kg in the root zone. The salt content became stable during the 8th-15th years of irrigation and the average salt and Cl- content were respectively less than 3 g/kg and 0.12 g/kg in the root zone. Relative to the uncultivated lands, the desalinization rate of total salts was more than 94%, and Na+ and Cl- contents in the root zone significantly decreased after many years of irrigation. Similar to the total salt content, the Cl- content tended to decrease exponentially as a whole. Na+ and Clwere the major decreasing ions after long-term drip irrigation as well as Ca2+, SO42- and Mg2+, while other ions (e.g. HCO3-) showed no obvious change with different irrigation histories. The duration of drip irrigation under plastic film had a significant effect on the survival rate and yield of cotton in arid regions, which were 7.1% and 1 279.2 kg/hm2 for 2-years drip irrigation, 60% and 5 250 kg/hm2 for 5-years irrigation, and >90% and 6 500 kg/hm2 for > -years irrigation, respectively. The survival rate could reach more than 80% after 6-years irrigation. Finally, it is found the local irrigation regime is the main reason inducing the decrease of salt content in the root zone, so it is favorable to maintain the existing irrigation regime for the long-term sustainable application of drip irrigation under plastic film. However, the irrigation should be properly reduced to save water during the late flowering, boll setting and boll opening stages. [ABSTRACT FROM AUTHOR]