Abstract:For grafting brings various advantages to plants, such as enhancing the disease resistance, speeding the growth, increasing production of per unit and reducing chemical application, it is a crucial step in large-scale vegetable production. Furthermore, automatic grafting by machine can effectively improve the survival rate of grafted seedlings and the working efficiency, which makes this kind of technology a rigid demand in vegetables’ commercial production. At present, global research within the field of automatic grafting and related robotic technologies has been carried out for years. The recent developments and the key technologies were systematically analyzed based on studying information in both academic and commercial fields. And five kinds of key technologies were brought forward, which were seeding mechanical grabbing technology, seeding romanticized delivering technology, stock/scion cutting technology, stock/scion joining technology and controlling technology for the grafting system. Moreover, the conclusion and prospection for the worldwide automatic grafting technologies were provided from three aspects: firstly, the level of the automation for grafting machines would make a further progress in the near future; secondly, the amount of the plants that a single grafting machine can process was supposed to increase; thirdly, the state of the art technologies in relationed fields, such as agronomy, ergonomie and artificial intelligence, would promote the grafting machines’ performance more in the future.

Abstract:There are many problems in the current greenhouse and plant factory. It’s an effective solution to work by robots. However, because of the limit of the intelligent algorithm at present, the robot’s works are imprecise.And they can just complete single job in once cruise which cause the inefficient using. Aiming at the problem, an algorithm which based on the motion sensing of Kinect and used in three arms robot was proposed, by using the Kinect to collect the depth image, including the operating personnel and combining the Random forests of statistical learning theory with the mean shift algorithm based on the Gauss kernel function which acquired 20 skeletal joints that can standard the human motion. On this basis, a mapping relation was put forward in innovation of three arms based on the mode switching to achieve that the two arms of the man can freely control three arms of the robot and perform several works in greenhouse. In addition, a way of gesture features segmentation was proposed which based on skeletal tracking technology in Kinect and YCbCr color space, realizing the aim that using the action of the palm to control the robot’s end effectors. Finally, a prototype of three arms robot was built to test the decision algorithm of motion sensing and its accuracy. A discrete value was taken for the angle in shoulder joint to recognize the error data in experiment, so eliminated errors in the shoulder joints. The results showed that the maximum mapping error of joint angle was 1.90° between human and robot. The maximum error of the host computer sending angle and the real angle by robot was 0.80°, which was within the margin of error. Meanwhile, the average time of completing an order of picking and spraying was 13.34s, the picking time was 6.36s and the spraying time was 6.98s. And the performance of the robot can be boosted by training the manipulator. It was indicated that this algorithm had a great practicability and can work accurately.

Abstract:Accurate and rapid disease severity quantifying is critical for scientific selection of disease control measures. Smartphone-ased systems may facilitate this procedure. Based on Android and digital image processing, a smartphone-based system for cucumber leaf disease severity quantifying was designed and implemented. Leaf images can be obtained by using the smartphone back camera in field, and also can be loaded from local storage of the smartphone. Severity quantifying was done to the image in several steps. Firstly, image pre-processing and non-interested background removal were directly done to the leaf color image. Secondly, the diseased region was discriminated from the leaf region. Finally, disease severity was calculated by the ratio of disease area to leaf area as percentage, and disease grade was also calculated from the disease severity following a national standard. Numerical severity quantifying results were displayed in the interface, and the identified diseased region of the leaf image was marked in red and displayed in the interface as a synthesis image simultaneously. Two background removal algorithm were implemented in the system. One was used for simple background removal, namely super-G, which was used for background removal when the leaf region within a simple artificial background, such as a white A4 sheet. The other one was grabcut, which was a user-interactive background removal method chosen for complex natural background removal. Where the user could roughly point out background and foreground, and then the application would do the rest. For testing performance of the system, totally 50 images of downy mildew infected cucumber leaves were used. Images were acquired from greenhouses in north of Beijing. Results showed that the system could accurately quantify the downy mildew disease severity in acceptable time. Average percentage of false quantifying was 6.56%. Average running time for disease severity quantifying was 1s for disease images with simple artificial backgrounds and 11s (user interaction time was varied with each individual, thus not included) for those with complex natural backgrounds.

Abstract:The identification of plant species is an essential part of botanical study and agricultural production. However, low dimension features cannot describe the leaf information. Thus, it cannot differentiate varieties of plants, and the accuracy is low. A method of plant species identification was proposed based on multi-feature dimension reduction. Firstly, color images of plant leaves were preprocessed by the digital image processing technology. The binary image, gray scale image and texture image without the petiole, wormhole and background were obtained after the preprocessing. Secondly, geometric characteristics and structural characteristic were extracted from the binary image. Hu moment invariants features, gray level co-occurrence matrix features, LBP features and Gabor features were extracted from the gray scale image. The fractal dimension was extracted from the texture images and 2183 features were extracted to describe leaf samples in number. Thirdly, the method of combining principal component analysis (PCA) and linear discriminant analysis (LDA) was adopted to reduce the feature dimension. Then the feature data of training samples was adopted to train the support vector machine classifier. Finally, the support vector machine classifier was used to classify the feature data of test samples. The experiments were carried out on Flavia database and ICL database. The average accuracy was 92.52% and 89.97%, respectively. The experiments showed that the average accuracy of the proposed method was better than that of the compared researches.

Abstract:Tool design and working parameters for subsoiling in wet clayey paddy soil are different from those for dry land cropping system. Investigation on the subsoiling process and the governing mechanisms requires detailed description on the underlying influential factors. Field soil parameters were used as a reference to construct a DEM model for subsoiling which was suitable for wet clayey soil analysis and performed in a EDEM software. The proposed DEM model of clayey paddy soil was then implemented to simulate a subsoiling process, in which directly measured draft and macroscopic disturbance of field soil was compared. Microscopic process and mechanisms of soil fragmentation were assessed with simulated stages. Results showed that simulation error with the proposed DEM model was less than 6.63%. Mean error of the resulted microrelief was 4.39%. Mean error of elevated ridge was 19.22%. The measured results from microscopic approach were re-evaluated and the correctness of related assumptions from microscopic approach was confirmed by DEM results, soil failure boundary evolution and soil failure with particle contacting models were depicted. A soil fragmentation index was proposed for describing soil fragmentation behavior from DEM perspectives. The error of fragmentation index with respect to measured soil fragmentation parameter was less than 3.46%, affirming that the proposed parameter was a suitable tool for microscopic description of soil failure imposed by subsoiling. This research provides a powerful technical basis for the interaction mechanism between soil and soil, and lays a theoretical foundation for the optimization design of the soil contact parts.

Abstract:When the interaction between agricultural machinery and soil is simulated, the accuracy of the chosen particle parameters will directly have an effect on the simulation results. A systematic method for calibrating the interaction parameters of sand particles was proposed based on the combination of experiment and simulation. By the repose angle test apparatus, the triaxial shearing test instrument and the particle image analysis system equipment, the repose angle of the sandy soil, the shear modulus, the particle size distributions and morphology were obtained, which provided reference for particles or factory modeling. The standard ball and non-standard ball were used to calibrate the coefficient of restitution, coefficient of static friction and coefficient of dynamic friction between particles. The effect of different qualities and different calibration methods (drawing plate method and funnel method) on the repose angle were studied. The effect of different qualities of the soil on repose angle was small, and it can be ignored. Meanwhile, there was no significant difference between the two calibration methods. When the standard ball was used for calibration, the repose angle obtained from the simulation was closest to that of the test (coefficient of restitution was 0.15. coefficient of static friction was 0.8, and coefficient of dynamic friction was 0.2). The repose angle of drawing plate method was 33.99°, and the relative error was 4.74%. The repose angle of the funnel method was 33.59°, and the relative error was 3.51%. When the non-standard ball was used for calibration, the repose angle of the drawing plate method was 32.06°, and the relative error was 1.20% (coefficient of restitution was 0.15, coefficient of static friction was 0.2, and coefficient of dynamic friction was 0.3.). It can be seen that the effect of particle appearance on the coefficient of static friction was relatively large. The result provides a new idea and method for the calibration of particle parameters.

Abstract:In order to study seed movement law of seed conveying tube of airassisted centralized metering device for rapeseed and wheat, effects of seed conveying tube’s diameter and length, ration of lateral length to longitudinal length (k), and joint’s type on seed motion characteristics and airflow field were analyzed with EDEM-CFD coupling approach. Impact of seed conveying tube’s structure on seeding performance was studied by bench experiments. The results showed that seed movement direction which was the same as airflow direction in seed conveying tube was in axis direction and seed motion source was the drag force. The seed velocity in seed conveying tube’s outlet was increased first and then decreased with the increase of ratio of lateral length to longitudinal length (k). The each row’s averaged seeding quantity and apiece row consistency variation coefficient of seeding quantity were affected significantly by seed conveying tube’s structure. When seed conveying tube’s diameter, length and k was 42mm, 1.0m and 2/3, respectively, seed velocity, relative velocity between particle and airflow and seed distribution were good with lower pressure loss and better seeding performance. Seed velocity of conveying tube with bends was larger than that of conveying tube with mansard joint. The relative velocity of conveying tube with bends was lower than that of conveying tube with mansard joint. Airflow field and seed distribution was uniform with larger seed velocity and lower pressure loss in conveying tube with bends of 100mm of radius. When rotational speed of seed feed device was within the range of 10~40r/min, apiece row consistency variation coefficient of seeding quantity of rapeseed and wheat was less than 4.0% and 5.0%, respectively. The stability of full seeding quantity and seed damage rate were no more than 1.0% and 0.1%, respectively, for both rapeseed and wheat. The results provided the basis for structure optimization of air-assisted centralized metering system and improvement of seeding performance.

Abstract:In order to solve the problems of great impact and vibration and poor dynamic performance of incomplete non-circular gear transmission applied in the rotary transplanting mechanism for dryland and rice plug seedlings, the analytic method was used to carry out improvement design for the buffer device of incomplete non-circular gear mechanism. The kinematics and force analysis of the buffer device were completed, and an analysis and design software based on VB platform for the buffer device was developed. The structure design of the buffer device was carried out. The dynamic performance of the transplanting mechanism with the improved buffer device was studied through theoretical analysis. The dynamic test bench of the transplanting mechanism was built and the dynamic tests were conducted for the transplanting mechanism installed with buffer device before improvement and postimprovement respectively. The dynamic test results showed that the maximum amplitudes of bearing force of the transplanting mechanism in X and Y directions were reduced from 365.5N and 48.4N before improvement to 345.2N and 42.2N after improvement, which were decreased by 5.55% and 12.81%, respectively, while the variances were reduced from 4880.3 and 148.7 to 4516.1 and 126.1, which were decreased by 7.46% and 15.20%, respectively. The test results after improvement were consistent with the corresponding results of theoretical analysis. The improved design of the buffer device was correct and effective, and the dynamic performance of the transplanting mechanism was improved.

Abstract:Aiming at enhancing the mechanization level of potato cultivation, promoting the development of potato industry, and further integration agronomic requirement of seedlings emerge cultivation pattern of potato self-puncture with covering soil on the film, a combined potato planting machine was designed, which synchronously realized institutional operation, such as fertilization, seeding, ridging, film mulching and covering soil on the top of full film surface. Based on the prototype, key parts were designed and selected, and the structure and operation parameters of fertilizing system and chain-spoon potato metering device were determined. The operation process of covering soil on the top of full film surface was analyzed, and the necessary work conditions to make sure that the covering soil thickness on the top of full film surface were obtained by analysis and calculation. For the relevant work performance test of prototype, the field experimental results showed that under the condition of operation speed of 1.8~2.0km/h, the multiple index was 4.9%, the missing index was 6.6%, the qualification rate of planting depth was 95.2%, the potato distance qualified index was 90.1%, the qualification rate of covering soil on the top of full film surface was 98.8%, the variation coefficient of fertilizer consumption consistency for each row was 6.5%, and the variation coefficient of fertilizer consumption stability for the total row was 5.1%, which were up to the relevant work quality evaluation specification requirements, and also the experimental results met the design requirements of combined operation machine. The research results provided an important reference for the plastic film mulching cultivation pattern of root-tuber crop combined machine development.

Abstract:The grain bite wounds and grain bite off of corn harvester snapping means caused a serious loss. Aiming at those existed problems, a polygonal vertical-rollers snapping means with simple structure, good snapping effect and high reliability was designed. The mechanism of the vertical vibration snapping broken was studied. And then the design methods of main structural parameters for polygonal vertical-rollers snapping means were analyzed. Orthogonal design method was used for test design with influence factors of the number of edges, snapping roll speed and snapping roll diameter. By orthogonal test, it can be known that the factors affecting the quality of snapping in order of their importance were the number of edges, snapping roll speed and snapping roll diameter. By orthogonal test, it can be known that the optimum combination was snapping roll diameter of 7cm, the number of edges of 8, snapping roll speed of 950r/min. Test under optimum combinations was carried out, and it was found that the grain broken rate was 0.13%, the grain loss rate was 0.28%, and the rate of broken stem was 0.53%. The grain losses and damages were both far lower than the national standard. Under optimum conditions, validation tests were done to determine the most appropriate size of the interior angle adjustment. The test result showed that the resizing interior angle Δ was 16°, which was half of the maximum interior angle range of adjustment, and under this conditions the harvesting quality was the best.

Abstract:The D200 straw fiber extruder developed by Northeast Agricultural University is used mainly in fiber processing to get crop straw expanded by utilizing physical extrusion method, which can realize clean, efficient and high value utilization of crop straw. In order to improve the efficiency in soaking, cleaning, continuous and stable conveying of crop straw material and solve the problems of strong labor intensity when it is fed artificially and nonuniformly, the development of a matched raw material supply device is absolutely necessary. This supply device mainly consisted of soaking device, stirring device and fishing conveyor device, in which the fishing conveyor device functions as a critical component. Based on analysis of the cooperating relationship among three systems (referring to soaking, stirring and fishing systems), a fishing rake was selected as research object to establish a mathematical model of fishing amount by analyzing the kinematic process between harrow tooth and straw. Belt linear velocity, harrow tooth number and rotating speed of agitator were proved to be the effective factors affecting fishing efficiency. Critical condition that the straw was not thrown out from harrow was found through force analysis when straw was separated from the water surface. The test material was Dongnong No.425 rice straw. Experimental investigations were carried out with the method of L16 (45) orthogonal test to obtain the optimal parameter combination. Meanwhile, the belt linear velocity, harrow tooth number and rotating speed of agitator were supposed to be the main influence factors. Fish efficiency and variable coefficient of fishing efficiency were chosen as the evaluating indicator. The results showed that belt linear velocity, harrow tooth number and rotating speed of agitator had very significant effect on fishing efficiency （P<0.01);belt linear velocity had very significant effect on variation coefficient of fishing efficiency （P<0.01). Subsequently, by using fuzzy comprehensive evaluation method, the order of the comprehensive indicator combined fishing amount with variation coefficient of fishing efficiency was the belt linear velocity, the harrow tooth number and the rotation speed of agitator. The optimal combination of parameters occurred with linear velocity of conveyor line at 0.6m/s, rotation speed of stirring paddle at 40r/min, harrow tooth number of rake of 8 when fishing amount per unit time was 1111.2kg/h and variation coefficient was 0.124. This research provided a reference for the structural improvement of the supply system of raw crop straw and guidance for the optimization of the operating parameters as well.

Abstract:With the aim to analyze and verify the advantages and rationality of cocurrent special-shaped alfalfa, the preparation and storage experiments were designed and the relative theories were analyzed. Through the preparation experiment of concurrent special-shaped alfalfa, the effects of three factors, such as the height of the flight, the number of flight and the rotation speed of the drum, on the density and yield of the cocurrent specialshaped alfalfa were analyzed.Through the analysis of heat and mass transfer process of cocurrent special-shaped alfalfa storage, a heat and mass transfer model of cocurrent special-shaped alfalfa storage was established. In contrast with the heat and mass storage transfer model of grass normal storage, it can be proved that the heat and mass transfer of cocurrent special-shaped storage was faster, the cocurrent special-shaped alfalfa storage had practically and significantly improved the quality of the grass during natural ventilation. Through the storage experiment of alfalfa, the temperature changes, moisture changes and the ratio of decay were analyzed. Results showed that the alfalfa’s plant activity was improved after the cocurrent special-shaped preparation to storage. Although in the short-term, the temperature within the alfalfa heat was increased seriously.After a period of time, the temperature of cocurrent special-shaped alfalfa storage was decreased. The alfalfa decay weight of the cocurrent special-shaped storage was reduced by 23.7%~76% compared with the scattered storage.

Abstract:Cylinder rotational speed and forward speed are two main working parameters of spring-finger cylinder pickup collector. Harvesting, different ways of storage and transportation also have forage moisture content requirements. Through researching the influence law of forage moisture content and working parameters on the pickup collector collecting performance, the pickup performance index of optimal parameter combination can be got, and it can be used to guide the actual production and provide technical support and theoretical basis for pickup collector design and manufacturing. For collecting alfalfa, taking cylinder rotational speed, machine forward speed and forage moisture content as test factors, taking power consumption and leakage rate of picking up as performance index, orthogonal experiments were done on the original device of spring-finger pickup cylinder collector and the improved convex contour line device at the same time. Through the orthogonal experiment and the springfinger end of acceleration experiment, effects of the three factors on collecting performance were analyzed. Levels of orthogonal test factors were selected from single factor experiment results, namely the machine forward speed of 3.5km/h, 4.0km/h and 5.0km/h, cylinder rotational speed of 42r/min, 50r/min and 60r/min, forage moisture content of 15.1%, 17.3% and 22.3%. The test results showed that the CAM track had greater influence on collecting performance, the cylinder rotational speed and forage moisture content had extremely significant effects on working performance, the machine forward speed had influence on working performance. The affecting sequence of importance for three factors on power consumption and leakage collecting rate were cylinder rotational speed, forage moisture content and machine forward speed. When cylinder rotational speed was 42r/min, forage moisture content was 15.1%，and machine forward speed was 4.0km/h, the collecting performance of the pickup collector was the best．Through the spectrum analysis, it was concluded that the spring-finger end acceleration was increased with the increase of forage moisture content, power consumption was increased and pickup leakage rate was declined with the increase of forage moisture content. It would lay research foundation for the spring-finger pickup cylinder collector to match the optimal working parameters and structure parameters and collecting performance for the future.

Abstract:When wind speed, soil particle size distribution, collection time and inlet collection efficiency etc. are certain, separation efficiency of sand sampler is the main factor affecting collection efficiency, which is often affected by wind-sand separation rules. In order to reveal wind-sand separation rules in the sand sampler, a sand separator in the shunt-hedging and multi-stage expansion combined sand sampler was took as a study model, a analysis of single-phase flow field and gas-solid two-phase flow field in the sand separator was made through Fluent numerical simulation and micro wind-tunnel test. On the base of explaining reducing velocity mechanism of airflow, a further analysis of airflow reducing velocity and sand volume fraction effect on wind-sand separation was done, and the influencing situation of different particle size of sand was expounded. The results showed that reducing velocity substantially was the most effective method that achieving wind-sand separation, the main reason caused by substantial airflow speed reduction was the formation of a large value of turbulent kinetic energy field;for wind-sand flow, when the sand content was high, the wind-sand separation effect was going to be good with good velocity reducing effect, when sand was affected by strong winds, sand with particle size less than 0.03241mm was easily induced by flow field, less affected by the motion of inertial, the possibility excreted from the exhaust port was large, which was the main part that affected sand separation efficiency and sand collection efficiency. The study provided a theoretical reference for the design of sand sampler, which had a good collection performance, and it further improved the theoretical system of sand sampler technology.

Abstract:Pressure oscillations in the axial flow pump impeller are associated with operational stability of the pump unit and fatigue failure of the blade. In order to obtain the characteristics and sources of the pressure oscillations and investigate the effects of adjustable guide vanes (AGV) on pressure oscillations, the CFD method based on the RANS equations and SST k-ω turbulence model was applied to simulate the unsteady flow inside the axial flow pump. The monitor points were located on the impeller blade and the guide vane. The static pressure of each survey point was recorded for 14 rotation periods. The calculated head was performed and supported by experimental data with the maximum relative error less than 4%. It indicates that the geometric model, numerical method, and simulation scheme are reasonable and reliable. Fast Fourier transformation method was used in the pressure signal processing. The main frequency of the pressure oscillations on the impeller blade is the guide vane passing frequency and the main frequency on the guide vane is the blade passing frequency, which indicates that the rotor-stator interaction between the impeller and the guide vanes is the source of the pressure oscillation in studied operating points. After adjustment of the guide vanes, the amplitudes of the pressure oscillations on both the impeller blade and the guide vane are reduced. The flow pattern with different guide vane angle was shown by the streamline, and the vortex flow was partly suppressed. It indicates that the rotor-tator interaction is improved in such operating conditions. The adjustable guide vane provides a valid solution to protect the impeller from potential fatigue failure.

Abstract:The computational accuracy for sediment erosion numerical simulation of double suction centrifugal pump is influenced by solid-liquid two phase flow algorithm. The modified Eulerian algorithm for solid-liquid two-phase flow was adopted, both characteristics of inter-phase drag force and sediment diffusion coefficient were considered in the modified algorithm. Then the flow field of double suction centrifugal pump was simulated for typical suspended load sediment particle diameters. The results showed that the turbulence intensity on the front and back of blade were greater, which were 6%~10%. The particle dynamic scales were greater on the front and back of blade rather than on the middle of the blade in consideration of the location. The turbulence scale effect was composed of the turbulence intensity and the particle dynamic scale. The turbulence scale effect gave more obvious influence on the front and back of blade rather than on the middle of the blade. The particles were easier to diffuse because of the increasing inter-phase drag force led by the turbulence scale effect, the particles gathering phenomenon was then avoided. The turbulence scale effect gave more obvious influence on large particles rather than on small particles in consideration of the particles scale. So interval range between maximum value and minimum value of the calculated solid concentration distributions on blade pressure surface was decreased. The calculated solid volume fraction had larger variation for the large particles than the small particles, and larger variation on the front and back of blade than the middle of blade, because turbulence scale effect was considered. The block erosion area located in blade pressure surface trailing edge was severe erosion area, the result calculated by the modified algorithm was agreed well with the actual erosion conditions of centrifugal pump rather than the results of the zonary erosion area and partial erosion area calculated by traditional algorithm. There was an increase in the erosion ratio with the turbulence scale effect considered. Then on this basis, the principles of the blade hydraulic design and the blade surface spraying protection for double suction centrifugal pump were proposed. The principles laid the foundation for improving abrasion resistance of double suction centrifugal pump.

Abstract:As the basic carrier of long-distance inter-basin water conveyance project of pressure piping, pressure piping is an important part of agricultural engineering and water conservancy projects, which plays an important role in solving the uneven spacetime distribution of water resources. The vibration during the operation is the critical problem in the design and safety evaluation of water pipeline. In order to solve the problem of how to improve the precision of the FSI (fluid-solid interaction) model in the natural vibration characteristics analysis of the piping, two different FSI models of a piping in cascade pumping station of Jingdian Project were built, by using the additional mass method and direct coupling method respectively. Then the modal characteristics of two FSI models which were obtained in the natural vibration characteristics analysis were compared with the modal characteristics of the prototype piping identified by stochastic subspace identification (SSI) method. The comparison results show that the simulation results of the model by using direct coupling method were in good agreement with the results identified by SSI method, and the maximum error was 3.62%. In the comparison of calculation accuracy of the same order, the model by using direct coupling method outperforms the model by using additional mass method, making up for the lack of the modes that the additional mass model can not work out. The results show that FSI affects the piping system modal frequency seriously and the model by using direct coupling method is superior to the additional mass model in terms of the order number and precision of the simulation, reflecting the real natural vibration characteristics of liquid conveying piping. This method can be used in the analysis of the dynamic characteristics of complicated pipe systems.

Abstract:The high-speed photography system was built to investigate the self-priming process of external mixing self-priming pump to analyze the influence of gap between impeller and tongue on self-priming performance of pumps, and then further grasp the self-priming mechanism. The digital images processing technique based on Matlab was applied to compute the number, average diameter and motions of bubbles in the area of diffuser. The tongue gap was resized and the self-priming time was measured to research the internal relations between the bubbles characteristics and self-priming mechanism. The results show that self-priming process is a complicated unsteady gas-liquid two phase flow and always accompanied by generation, collapse, gathering and splitting of bubbles. During the self-priming process, bubbles in the left area of diffuser are smaller and denser, which are easier to be discharged out of the pump. On the contrary, bubbles in the right area vibrate and rotate, which goes against self-priming and wastes energy. When the gap is increased from 1.0mm to 2.5mm, the average diameter of bubbles in the diffuser is increased from 1.2mm to 1.9mm and the self-priming time is increased from 28s to 113s. It means that the bigger the gap is, the bigger diameter of bubbles from tongue to diffuser will be and the longer the self-priming time will be.

Abstract:The heavy metals pollution in cultivated soils of main grain producing areas has become a prominent problem affecting the safety of food and living environment. The hyperspectral remote sensing technology as the frontier technology in the field of remote sensing technology, provides a new approach to access to soil heavy metal data quickly and accurately, and also provides the technical support for monitoring and predicting. Taking Xinzheng City of main grain producing areas in Henan Province as the research object, the 191 cultivated soil samples collected were divided into 144 calibration set and 47 validation set by Rank-KS method. The hyperspectral reflectance of soil samples was measured by using ASD FieldSpec 3 spectrometer in laboratory experiments. The correlation analyses between row spectral reflectance in 400~2400nm and the content of heavy metals Cr, Cd, Zn, Cu, Pb were done, and the correlation coefficient by F significance test (P=0.01) was selected which could be used to extract sensitive hyperspectral feature wavebands reflectance common to the above heavy metals as the independent variables of model. The hyperspectral inversion model was built by panel data model of fixed effect variable coefficient based on the ordinary least squares estimation method (OLS), which was about the panel data of heavy metals Cr, Cd, Zn, Cu, Pb of 144 samples in Xinzheng. The results show that the panel data model is overall significant, with high goodness of fit (R2=0.9937， F=1365.94). The result of precision test indicated that models for Cu and Pb performed well in modeling and predicting with a good ability of quantificational prediction, with relative percent deviation (RPD) values of 2.046 and 3.432 separately;Cr,Cd,Zn could perform generally in modeling and predicting with a good ability of quantificational prediction, with RPD values range of 1.4~1.8. The panel data model can be used to calculate various heavy metals at the same time and rapidly monitor soil heavy metals with hyperspectral reflectance in Xinzheng, with simple and fast calculation.

Abstract:A scientific and reasonable protection zoning scheme of cultivated land was given by using the spatial autocorrelation analysis method, which combined the natural condition, utilize situation and economic level with the spatial characteristics of cultivated land. Firstly, the global autocorrelation was used to explore the global distribution of cultivated land quality in Gaoping City for further analysis. Then the local autocorrelation was used to study the local distribution of cultivated land quality in Gaoping City, regarding the cultivated land quality index as vitiate. Finally, a protection scheme was formulated based on the analysis results of the comprehensive quality. The main results were as follows: firstly, the cultivated land quality which included the natural condition, utilize situation and economic level exhibited significant aggregation of global spatial distribution in Gaoping City. Besides, the local distribution of cultivated land quality showed a regular pattern, which contained the HH type (high-high) and LL type (low-low) emerged as the shape of cluster, while the HL type (high-low) and LH type (low-high) were barely sporadic distributed in Gaoping City. At last, kinds of protection zoning were put forward according to the combination of comprehensive cultivated land quality index based on local spatial autocorrelation and actual situation, which would provide a reference for cultivated land protection in Gaoping City.

Abstract:Hengshan county of Shaanxi was taken as research area, three kinds of soil organic matter content inversion model based on hyperspectral data were compared. The soil samples were collected in the field. The ASD Field Spec FR was used to measure the soil samples’ spectrum. The content of soil organic matter was measured via potassium dichromate oxidation volumetric method in laboratory. Then the first derivative of spectral data was obtained by applying the reciprocal difference to original spectral reflectance, and the multiple linear stepwise regression (MLSR) analysis model of the first derivative of spectral data was constructed. The correlations between the original spectral reflectance, the first derivative of spectrum and soil organic matter content were analyzed. The first derivative spectra of the characteristic bands which had high correlation coefficient with soil organic matter content were obtained. Based on the first derivative spectra, the MLSR model was established. Meanwhile, the principal component analysis (PCA) was performed for the first derivative spectra of the characteristic bands with high correlation coefficient. The PCA-BP model and PCA-MLSR model were established by the results of PCA. The soil organic matter content was inversed by three methods, and the inversion accuracy was validated and compared with each other. The results showed that the coefficient of determination (R2) and root mean square error (RMSE) between the measured value and inversion value were 0.8930 and 0.1185% with PCA-BP model, respectively, and the R2 and RMSE between the measured value and inversion value were 0.7407 and 0.1613% with PCA-MLSR model, respectively. However, in these MLSR models which based on the first derivative spectra, R2 and RMSE between the measured value and inversion value were 0.6899 and 0.1710% with the optimal inversion model, respectively. Based on the results, the inversion accuracy of soil organic matter content in PCA-BP model was higher than that of MLSR model. In MLSR model, the inversion accuracy of soil organic matter content by using all principal component was better than that only using the partial principal component, of which the cumulative variance contribution was greater than 90%. The content of soil organic matter can be well inversed.

Abstract:Actual livestock and poultry breeding capacity was calculated by using area under crops and amount of breeding livestock based on GIS technology and modulation, the changes and spatio-temporal coupling relationship of the livestock and poultry breeding capacity and its volume in Hebei Province in 1994, 2003 and 2013 were analyzed by using crops planting area to calculate the capacity and using polluting coefficient to calculate the volume. The research result revealed that the acreage of crops was increased to 83663hm2, and the areas were mainly concentrated in Chengde and south central plain. The livestock and poultry breeding capacity was increased to 1.087 million in counting of pigs, and the areas were mainly concentrated in Shijiazhuang, Tangshan, Zhangjiakou and other urban areas. The livestock and poultry breeding volume showed a trend of firstly increase and then decrease, which was increased by 11.02 million in counting of pigs. Considering the crops planting area as the only factor absorbing feces, following results could be deduced: there were 69 counties which were overloaded in Hebei Province between 1994 and 2003;94.24% of the counties in Hebei Province were under ecological sustainable redline;overloaded situation was improved between 2003 and 2013, total number of overloaded counties was decreased to 26, which accounted about 18.7% of all counties in Hebei Province, except for Chengde and Tangshan, other areas of livestock and poultry over loaded counties were significantly reduced. Using Ward cluster analysis, coupling features were classified into nine regional types by its volume and changes of crops planting area in Hebei Province from 1994 to 2013. The research results provided decision support for development of livestock and poultry breeding industry and improvement on Beijing-Tianjin-Hebei eco-environment.

Abstract:In order to measure the soil moisture in real time, quickly and accurately by using time domain measurement technique, a low cost soil moisture measuring meter was designed based on time domain transmission (TDT) principle. The probe of TDT meter adopted structure of closed loop, so that the signal was transmitted on the probe in one way. The permittivity of soil was measured by measuring the transmission time of electromagnetic wave in soil medium, and the soil moisture was obtained through soil calibration equation. TDT meter was composed of a high frequency pulse signal source, a coaxial transmission line, a probe in U-shaped loop structure, a transmission time measuring circuit using TDC-GP2 time interval measurement chip as the key component and a control circuit using LPC2132 ARM micro controller unit as key component. Through the standard solution test and soil test, it was proved that the measurement results of TDT meter with double U-shaped probe were better than those of single U-shaped probe. The root mean square error (RMSE) of transmission time measurements by using TDT meter with double U-shaped probe was 43.9ps, and the RMSE of dielectric constant measurements was 0.791. Using TOPP equation, the RMSE of soil moisture measurements in sand soil determined by TDT meter was 0.029cm3/cm3, and the RMSE of soil moisture measurements in loam soil determined by TDT meter was 0.039cm3/cm3. The results showed that the soil permittivity and soil moisture could be measured accurately by using TDT soil moisture measuring meter.

Abstract:In order to improve the accuracy of apple orchard extracting in very high spatial resolution (VHSR) remote sensing image, an automated apple orchard extracting method based on texture features together with spectral values and support vector machine (SVM) was studied. This method firstly obtained the optimum combination of multi-spectral bands by using the optimum index factor (OIF);then three kinds of texture features, namely gray level co-occurrence matrix (GLCM), fractal and spatial autocorrelation texture with six different window sizes (from 3 pixels×3 pixels to 13 pixels×13 pixels) were extracted from the panchromatic image for comparison, and further merged with spectral values respectively;finally the above features were used to identify apple orchard by using SVM. Experiments using QuickBird data showed that spectral features combined with texture features could achieve higher apple orchard extraction accuracy (Fa) and overall accuracy (OA) than using spectral features or textures features alone. Among the different features used, the spectral+GLCM features (with 9 pixels×9 pixels) achieved the highest accuracy (Fa and OA were 96.99% and 96.16%, respectively), which were slightly higher (0.63 and 1.56 percentages, respectively) than those of spectral+fractal features and significantly higher (11.92 and 9.20 percentages, respectively) than those of spectral+spatial autocorrelation features. Among the different classification methods, three classification techniques (SVM, maximum likelihood and neural networks) were compared for accuracy in apple orchard detection, and results suggested that SVM had the highest accuracy in identifying apple orchard. McNemar test was also computed for statistic significance among spectral+GLCM and other features and also among the three classifiers, and the confidence levels were all less than 5%. Consistency of the extracted apple orchard area and the visual interpretation results according to filed investigation and Google Earth VHSR concurrent image were able to achieve 98% in test regions.

Abstract:Canopy gaps are small-scale openings in forest canopies which offer suitable micro-climatic conditions for tree regeneration. The subtropical secondary forest in Hunan Province was focused, and multi-temporal light detection and ranging (LiDAR) and survey data were adopted to analyze effects of different canopy gaps on sapling density and height growth. The results showed that both size of gap and position within gap significantly affected sapling density distribution. Shade intolerant sapling was mainly distributed in central zones of small-sized gap and transition zones of large-sized gap, in which the density got the maximum (647 trees/hm2). Shade tolerant sapling was usually appeared in edge zones of gaps, and the maximum density (941 trees/hm2) was occurred in medium-sized gap. The size of gap significantly affected sapling height growth, shade intolerant and shade tolerant sapling had the greatest growth rate of 69.3cm/a and 57.7cm/a in large-sized and medium-sized gaps, respectively. Height growth of shade intolerant sapling in central zones was significantly higher than those in other zones, while shade tolerant sapling height growth was irrespective of their position within the gap. Results of mixed linear model suggested that size of gap had the main effect on sapling height growth, which exhibited aggregation among different levels of gaps. The higher density and more rapid height growth rate were got in the gap with size of 50~150m2, which could be the optimal gap size for facilitating community succession of subtropical secondary forest.

Abstract:In order to solve the problem that difficult to extract distribution information of sublateral canal without water or with less water caused by low resolution of remote sensing image, a hierarchical classification method of feature combination was proposed, which was based on object-oriented classification method. Bangleng village in Hetao Irrigation District was chosen as the study region, and multi-spectral images were obtained by using fixed-wing unmanned aerial vehicle (UAV) which carried multi-spectrum camera (520~920nm). After a lot of experiments, finally, the segmentation threshold value of 65 and the combined threshold value of 90 were chosen as the best remote sensing image segmentation parameters, then can interpret the obtained high resolution multi-spectral image data. By comparing the spectrum, geometry, spatial relationships between sublateral canal and the other surface features, different levels of classification rules were established to extract sublateral canal distribution information. And 14 sublateral canals in the study region were extracted. The results showed that due to the strong absorption in near infrared spectrum of water, the extraction accuracy of sublateral canal with water was 97.8%;the extraction accuracy of sublateral canal with less water or no water was 75.7%. Using UAV remote sensing techniques and combination of features object-riented hierarchical classification method provided a new way to identify sublateral canal in irrigation area. And future research should focus on eliminating the effect of trees, weeds and gate, as well as extracting canal which in both sides had surface features with close spectrum.

Abstract:Crop growth information is closely related to crop yield prediction and food security. Accurately investigating and monitoring crop growth information provides invaluable information for agricultural management, planning and decisionmaking, and further ensures sustainable development of agriculture. Guanzhong area is a main food production region of Northwest China, however, the varied topography, including loess hilly-gully region, Weihe plain and Qinling mountain, makes crop information extraction challenged and complicated. In order to obtain winter wheat planting information of Guanzhong area in 2014, thirty phases of MODIS NDVI image from September 2013 to December 2014 were used, the images were reconstructed by iterativeing Savitzky-Golay filter in time sequence, and the characteristics of NDVI profiles of the typical objects selected from filtered images were analyzed. And then the noncropland was masked based on the characteristics analyzed above. On account of the special NDVI profile of winter wheat, the twi-difference algorithm was applied to the selection of 17 phases’ image during period of November 2013 and July 2014, and the NDVI peaks were identified. From the local crop calendar and the characteristics of typical NDVI profiles, it was found that except winter wheat and rapeseeds, the rest of the crops did not show NDVI peaks during the selected period. Interestingly, winter wheat had two peaks in its growing season. The first one was appeared before the coming winter because of the snow or frost, and the second one was the normal growing peak. Rapeseeds had a single peak which was lower than that of winter wheat. Thus, the winter wheat of Guanzhong area was identified at the pixel level by combining the pixels which had double peaks and single peak with NDVI value under 0.65. For verifying the accuracy of extraction, the winter wheat growth area was measured at four typical plots of 1km×1km, which were used to compare with the remote sensing results. Besides, totally 100 winter wheat NDVI profiles were sampled to compare with the artificial interpretation at the pixel level. The results showed that the winter wheat was mainly distributed at two regions in Guanzhong area. One was located in the river valley of middle reaches of Weihe river, and the other one was located in the wide Weibei plain of the east side of Jinghe river. Meanwhile, the winter wheat presented a scattered pattern at the loess hilly-gully area in the north, and did not appear at the mountainous area in the south. The total area of winter wheat in Guanzhong area in 2014 was 8.882 × 105hm2, and its areas in Xi’an, Tongchuan, Xianyang, Baoji and Weinan were 1.958×105hm2, 2.296×105hm2, 1.704×105hm2, 2.222×105hm2 and 2.769×105hm2, respectively. Compared with the statistics of government, the total relative error of Guanzhong area was 3.70%, with variation of 1.08%~9.02% at the city level. The maximum relative error was 9.02% which was occurred at Baoji. The accuracies of four plots of Changwu, Yintai, Fufeng and Yangling were 17.3%, 15.1%, 5.6% and 7.7%, respectively. Besides, the accuracy of sampled 100 NDVI profiles at the pixel level reached 90.28%. The results indicated that exacting the crop information using NDVI time-series at a topography complicated region was feasible and it can be applied to the other regions of Northwest China for making plan of crop planting, agricultural resource allocation and monitoring crop growing.

Abstract:Hyperspectral remote sensing can provide a non-destructive and effective approach for assessing the yield and yield components of oilseed rape timely. A quantitative technique was developed to estimate oilseed rape yield accurately depending on ground-based canopy reflectance spectra. Field experiments were conducted over three growing seasons at different sites (Wuxue and Shayang) in Hubei Province, China. The key parameters, including canopy hyperspectral reflectance during pod-filling period, seed yield and yield components (pod numbers per plant, seed numbers per pod and 1000 seed weight) were monitored. A partial least square (PLS) regression analysis was employed to perform the relationship between raw spectral reflectance (RSR), the first derivative reflectance (FDR) and seed yield and yield components. According to the calibration dataset, the best results were obtained with the FDR-PLS model for the prediction of yield and pod number, which yielded the highest coefficient of determination (R2cal) of 0.96 and 0.98, and the lowest root mean square error (RMSEcal) of 158kg/hm2 and 17 pods/plant, respectively. The tests using the independent validation dataset also showed that the FDR-PLS model could well forecast yield and pod number of winter oilseed rape, with values of R2val of 0.90 and 0.91, RMSEval of 379kg/hm2 and 66 pods/plant, and RPD of 3.11 and 3.12, respectively. The variable importance in projection (VIP) scores resulted from the PLS regression analysis were used to determine the effective wavelengths and reduce the dimensionality of the spectral reflectance data. The newly-developed FDR-PLS model using the effective wavelengths (628nm, 753nm, 882nm, 935nm, 1061nm and 1224nm) performed well in yield prediction with R2val of 0.91, RMSE val of 504kg/hm2 and RPDval of 2.34;Similar results were also obtained for pod number prediction with R2val of 0.87, RMSEval of 82 pods/plant and RPDval of 2.52 using the effective wavelengths (628nm, 758nm, 935nm, 1063nm, 1457nm and 1600nm). Consequently, the yield of winter oilseed rape could be reliably estimated with the in situ developed FDR-PLS method.

Abstract:In the process of automatic targeted spray in forest region at present, the accuracy and efficiency of point cloud data are all low when the tree trunks grow intensively, aimed at which the optimized K-means clustering algorithm was put forward, and data acquisition method was based on 2D laser detection. In view of the relevant data needed to be filtered before clustering analysis for trunk scanning spots, application of window filtering algorithm was put forward. The edge of trunk which generated mixed pixels was selected, and then the mixed pixels deriving from three adjacent scans and the scanning spots deriving from two scanning angles near the mixed pixel were extracted, finally, the maximum threshold filtering processing for the neighbor spots was done. Through 50 times of extractions and analyses of test data, only two mixed pixels were not filtered, which indicated that the filtering rate of mixed noises was high. Aimed at the defects of cluster number and initial cluster centers for Kmeans algorithm needed to be predetermined, the method of slope variation used to determine the clustering number was firstly proposed. Five groups of trunks were respectively measured for 100 times at five different distances in the test, and results showed that the number of error measurements was only three times, which could be removed by artificial way at the early stage of the test, and it indicated that the slope variation algorithm was reasonable and effective. The performance of Huffman tree method, which was used to determine the clustering centers for the trunk scanning spots, was analyzed in another test, and K-means clustering was carried out by using random sampling method and Huffman tree method under three trunk distribution types. The average correct rate of former was only 76.4%, while that of the latter was 95.5%. Meanwhile, iterations and time-consuming using the two above-mentioned algorithms at type I distribution were analyzed, and the average number of iterations of random sampling method was obviously higher than that of Huffman tree method at five different distances, but the average time-consuming of Huffman tree method was higher than that of random sampling method. The variation range of former was 120~220ms and it was 50~85ms for the latter, which were all in acceptable ranges on forest surveying and mapping. Experiments proved that the determining methods for clustering number based on the slope variation algorithm and clustering centers based on Huffman tree method were effective algorithms for the clustering of trunk scanning spots in forest region during using K-means algorithm, which could be applied to tree trunk detection for actual forest region.

Abstract:In order to promote the trading and accelerate the transformation of agricultural scientific and technological achievements (ASTA), a WebGIS-based system for evaluating the value of ASTA was designed and developed. Object-oriented JAVA language was adopted to realize various functions of the system. The functions included the storage and management of spatial and temporal data, value evaluation of ASTA, spatial and temporal characteristics analysis of value evaluation results and visualization of the results. As an integrative tool for managing data and analyzing spatial and temporal characteristics, the system provided service for agricultural scientific and technological achievements management department. Comprehensive fuzzy method was adopted to evaluate the value of ASTA. In order to ensure the accuracy of evaluation results, the indexes were extracted from many influence factors and then the evaluation index system was constructed. The index system took into account all the influence of technology, market and benefit. So far, totally 265 ASTA were evaluated in the system, which were produced in 2010—2015. To validate the correctness of the system, an experiment was carried out, and results showed that the accuracy of the system was good. The application of the system showed that it provided an efficient-fast third-party assessment tool for ASTA holders, and it also supplied an intelligent management tool for ASTA management department. Furthermore, evaluation results of the system can provide reference for ASTA trading.

Abstract:In forest surveys, volume tables are usually used for standing wood volume estimation. From the national to the provincial scales and even forest farm all have their own single and binary tree volume tables which have characteristics of a large number of samples and high accuracy. However, due to the great number of models that the form is not unified, it is difficult to identify the large species and other reasons, resulting in poor efficiency in table look-up. It is inconvenient to estimate standing wood volume by using volume tables for some applications with no high precision requirement, such as estimation of wood value by lumberman, growing stock estimation by UAV and remote sensing retrieval of standing parameters in wide area. Therefore, a simple and quick standing tree volume estimation model is required. Based on standard volume model of national major tree species and single entry volume table of all provinces and municipalities, the regression model was made by SPSS to process all the data of 2082 groups of diameter at breast height (D), height of tree (H) and volume (V) generated by 1cm sampling diameter class, and then the generic standard volume models and derived form factor (f) models were built. Among them, generic standard volume models included a nationwide standard volume model, two nationwide needle-leaved and broad-leaved standard volume models and six standard volume models that made by using SPSS software with form of Yamamoto type. The result of model fitting showed that the fitting determination coefficients (R2) were all above 0.984 and the effects of model fitting were good. Evaluation indicators of six regression models were selected to conduct model verification, and the verification results showed that the indicators of total relative error (TRE) and average system error (MSE) of all models were almost within the range of ±3%. Using basic data to derive the value of f to get 16 overall, needle-leaved and broad-leaved derived form factor models. The validation result of generic standard volume models and derived form factor models showed that in specific situation, it can replace existing regional tree species’ single entry and standard tree volume model to estimate volume, which avoided the process of in-place wood recognition and table look-up, and it is of practical significance to guarantee precision and simplify evaluation process of standing tree volume.

Abstract:The fractional vegetation cover (fv) is one of the important indicators to reflect the health of grassland ecosystem. However, fv is influenced by both natural factors such as temperature and precipitation, and human activities such as grazing. The fv estimated by MODIS surface reflectance product (MOD09) was used to analyze the grassland variation in Xilingol steppe. There are four different types grassland in Xilingol steppe, which are temperate meadow, typical steppe, sand steppe and desert steppe. The temporal and spatial variations of those four different types grassland were analyzed in growth seasons (April to October) from 2001 to 2013 by fv. The coefficient of variation (Cv) was used to indicate the changing degree offv during the study period. Moreover, the climate and livestock data were combined to analyze the effects of climate change and human activities on grassland variations. The results indicated that the spatial distributions offv in different years were similar, which were decreased from east to west. However, the interannual variations of the same type of grassland had no significant fluctuations. The yearly Cv variations indicated that 78.66% of the study area was in fragile and very fragile level. The typical steppe and sand steppe were in fragile level, and the desert steppe was in very fragile level, but the temperate meadow was in stabile level. The effect of precipitation onfv was positive and in very significant level. On the contrary, the influence of temperature on fv was negative and not significant. The livestock number had significant effect onfv, and the suitable livestock number should be 39 standard sheeps/km2 in Xilingol steppe.

Abstract:In order to study the influence of potential evapotranspiration on daily flow simulation results for hydrological models in the northeast alpine region, the widely applied SWAT model was chosen as an example, through comparative study on Ougen River Basin, using Penman-Monteith model, Priestley-Taylor model, Hargreaves model, Shuttleworth-Wallace model and modified 20cm evaporating dish observed data to compute the potential evapotranspiration (PET), then the influence of SWAT models on the simulation results was studied by different PET drivers. Research results showed that adopting subbasin scale for SWAT model to PET interpolation was quiet rough, and the calculated results cannot reflect the spatial distribution of PET specifically, the average temperature of alpine forest areas was less than 17.8℃ from January to February and also in December every year, including March sometimes. In different subbasins covered by large forest, the change of monthly average PET was little with the variation of forest species types and distribution areas, although differences of terrain on SWAT model were considered, it didnot show a high daily flow precision. Penman-Monteith model without consideration of terrain pattern, and Hargreaves model and Shuttleworth-Wallace model considered terrain pattern had good simulation results, while Penman-Monteith model fitted the best with Ens values of 0.651 and 0.686 in calibration and validation periods, respectively, which showed that the Penman-Monteith model suited better in alpine forest areas to calculate the potential evapotranspiration.

Abstract:Considering the low water and fertilizer use efficiencies with flood irrigation in sandy soil of Yulin, Northern Shaanxi, the effects of different water and fertilizer supplies on potato growth, yield and water and fertilizer use efficiencies were investigated through the field drip fertigation experiments. There were three water levels: W1(60%ETc), W2(80%ETc) and W3(100%ETc), and three fertilizer levels: F1(100-40-150kg/hm2), F2(175-60-225kg/hm2) and F3(250-80-300kg/hm2), resulting in a total of nine treatments. Based on those, key indicators (e.g., growth and yield) of potato in response to different irrigation water and N, P and K amounts were further analyzed. Results showed that different water and fertilizer amounts significantly influenced the plant height, leaf area index, dry weight, yield, water use efficiency (WUE), partial factor productivity of fertilizer (PFP), different tuber quality, yield related relations and economic benefits. The growth, yield and PFP were increased with the increase of irrigation amount, and W3 was more beneficial to growth of potato. However, the water use efficiency of W3 was significantly lower than those of W1 and W2. The average water use efficiency of W1 was 5.83% and 13.05% higher than those of W2 and W3. The impact of fertilizer on growth and yield showed an increasing and then decreasing trend, and yield reached the maximum of 59394.98kg/hm2 at W3F2 level. The water use efficiency of F2 was significantly greater than those of F1 and F3. Linear fitting revealed a positive relationship between plant height, leaf area index, dry weight and yield of potato within a certain range. Comprehensive analysis indicated that the appropriate irrigation and N, P and K amounts can not only maintain the good growth of potato, but also can obtain great yield and economic benefits. From the point of view of obtaining high yield and saving water and fertilizer, W3F2 (100%ETc, 175-60-225kg/hm2) can be used as an appropriate combination under the present experimental conditions.

Abstract:In order to explore the effective way to improve the water use efficiency of tomato in the sunlight greenhouse, the effects of lateral depths on growth, fruit shape and quality of tomato under different water deficit were studied through drip irrigation experiment in 2014 and 2015. Results showed that lateral depth had a significant influence on yield, irrigation amount (p＜0.05), and had no significant impact on irrigation water use efficiency and quality (p＞0.05). The growth rate of tomato was faster and fruit diameter was bigger when lateral was buried at 20cm depth. Under moderate and moderate-mild water deficit, lateral buried at 20cm depth could significantly decrease the fruit ratio of C grade (fruit diameter D＜6.5cm) by 29.2%, and increase the fruit ratio of A grade (D≥7.5cm) and B grade (6.5cm≤D＜7.5cm) by 16.6% and 2.0%, respectively. The changing trend of yield and irrigation amount of tomato showed a first increase and then decrease trend with the increase of lateral depth, the value of yield for lateral depth buried at 20cm was the highest (66.44t/hm2). Yield and irrigation water use efficiency of tomato were decreased significantly with the increase of irrigation threshold (p＜0.01), so irrigation amount can be reduced while the yield and water use efficiency of tomato can be increased by adopting different combinations of lateral depth and irrigation threshold. Therefore, lateral depth of 20cm and irrigation threshold of 60% of field capacity would be the most appropriate treatment combination for tomato cultivation in the sunlight greenhouse in Guanzhong region of Shaanxi Province. For the observed responses, the information on how the tomato adapted to different lateral depths under water deficit condition would provide guidance for field production practices as well as indications of possible mechanisms.

Abstract:A model system was proposed based on the advanced experience at home and abroad, which was applied to agricultural water-saving zoning. The reality of agricultural water saving, water resources distribution, natural conditions, agricultural water management, project management level and pecuniary condition in Beijing were also included in this model system. The model system included several indices and each index was defined based on index categorization. These indices were also used to present the aridity soil type and ground water index distribution in the corresponding zoning. Meanwhile, ArcGIS was also combined based on the function of superposition analysis and analytic hierarchy process (AHP). The ArcGIS analysis function in each lay was defined and the weight function on each function was also defined. Through the definition, the index value on each lay and each function can be obtained. After that, the index value can be scored and classified and also multiplied with each index weight. The multiplied values were the final value result and treated as overall value which was treated as the guided line for Beijing agriculture water-saving zoning classification. Through the model system classification results, Beijing was divided into agricultural water conservation priority development area, agricultural water saving suitable development area and agricultural water saving encouraging development area. According to the model system results, the corresponding engineering measures and agronomic measures were also recommended in water-saving and can partly help the decision-maker in Beijing to optimize the agricultural water saving.

Abstract:The movements of tracer particles in a labyrinth channel were observed by using the PIV technique. The pressure was in dynamic modes with trigonometric function, triangular, step and rectangular waveforms. The trajectories, velocity of single particle as well as the overall flow field in the channel were analyzed to reveal the anti-clogging mechanism of dynamic water pressure. The results showed that when compared with constant water pressure, flow rates in the channel under trigonometric function, triangular, step and rectangular waveforms dynamic pressure modes were not decreased significantly. Therefore, effect of dynamic water pressure on water delivery capacity of drip irrigation system was not obvious. Among the different dynamic water pressure modes mentioned above, the trigonometric function type demonstrated the shortest particles residence time in the flow stagnation region. The deposition probability of particles was the lowest under this mode, indicating a better particles transport capacity in the channel. Fluctuation effect generated by the water under pressure of trigonometric function form produced effect on the lowspeed swirl in the stagnation region, and aggravated the turbulence of flow in this region. The turbulent flow was enhanced and the ability to carry the particles retained or even deposited in the stagnation zone was improved. As a result, the particles were suspended from the bottom and returned back to the main flow path. The transport capacity of the flow got strengthened, and the anticlogging performance of the channel was improved.Therefore, the trigonometric function waveform dynamic water pressure model can most effectively improve the anticlogging performance in the labyrinth channel.

Abstract:Accurate estimation of reference evapotranspiration (ET0) is very important in hydrological cycle research, and it is also essential in agricultural water management and allocation. Using less meteorological parameters to estimate ET0 is necessary in areas with limited data. The ability of random forest (RF) and gene expression programming (GEP) algorithm in modeling ET0 was investigated and compared by using fewer meteorological parameters collected from four weather stations of Duan, Hechi, Baise and Rong’an, in karst region of southwest China, over a fiveyear period (2008—2012). Daily climatic data of the four stations, including maximum temperature (Tmax), minimum temperature (Tmin)，sunshine duration (n), relative humidity (RH) and wind speed (u2) were employed to model ET0 by using FAO 56 Penman-Monteith equation as the reference, and their performances were evaluated using determination coefficient (R2) and root mean square error (RMSE). From the statistical results, the derived RF-based (R2 was ranged from 0.809 to 0.991, and RMSE was ranged from 0.158mm/d to 0.678mm/d) and GEP-based (R2 was in range of 0.830~0.977, and RMSE was in range of 0.225~0.645mm/d) ET0 models were successfully applied to model ET0 with different input combinations. When only the temperature data can be used, the RF models produced satisfactory results (R2=0.875，RMSE=0.546mm/d), which can be used as an alternative to the conventional Hargreaves model. The relative importance of meteorological variables for ET0 can be assessed by RF method, the order of the relative importance of meteorological variables was: Tmax, n, Tmin, Ra, RH and u2. In most cases, the RF models were found to perform better than the GEP models. The results were expected to be useful to guide rehabilitation strategies and agricultural water management in karst region of Southwest China.

Abstract:With the increasing scale and intensive production of the livestock and poultry breeding industry, more and more attention has been paid to ammonia emission reduction from the animal farm. Ammonia discharged directly into the atmosphere would combine with SO2 or NOx to form secondary particles which can reduce atmospheric visibility. Moreover, the NH3 emission is related to the risk of environmental problems such as soil acidification and water eutrophication. Ammonia is the stench gas emission in farms as one of the major pollutants in farms. Emission control of farm ammonia is an important part of air pollution control. There is a big gap in the research and application of environmental protection unit and automatic control system between our country and abroad. Biomass removal technology has attracted more and more attention due to its advantages of high efficiency, no secondary pollution, good safety, simple equipment construction, easy operation and maintenance, and low cost. A pilot ammonia bio-oxidation device based on the biological principle and PLC control was set up in a pig farm in Beijing. It realized the automatic storage and adjustment of pH value, the ventilation control, the real-time measurement and curve display of environment parameters in the bioreactor. After the system in pig farm was running stable, longterm test and continuous test were adopted to detect the treatment effect of ammonia oxidation device. After two-month operation, the ammonia removal efficiency could reach up to 90%. The device has the advantages of stable and reliable operation, together with low operation cost.

Abstract:The system for collecting plant micro-environment and physiological parameters was featured with large amount of data, storage and transmission difficulties, which restricted the long-term monitoring of ecological information. A new method for collecting plant micro-environment and physiological parameters based on compressive sensing was proposed. The bases of discrete Fourier transformation (DFT) and discrete cosine transformation (DCT) were selected as sparse bases under which the working performance of system was tested. Through the experimental analysis, DCT had smaller sparse error and DFT had better denoising effect, lower observed dimension, higher compression ratio under condition of the same sparsity. With the increase of sparsity, both sparse error and compression ratio were decreased. In the meantime, both observed dimensions were increased. In addition, data compression ratio and power consumption of the DFT compressive sensing system were tested based on ARM. The conclusion was that the data compression ratio was 4.24, and 13.62% power consumption was saved compared with traditional collecting system for plant micro-environment and physiological parameters. In conclusion, the method proposed had advantage of compressing data, saving storage, decreasing data transmission, which can extend working hours of the system by decreasing power consumption and make an important effect on the development of internet of things in agriculture and forestry.

Abstract:Carbon dioxide is the necessary material for plant photosynthesis, and building favorable carbon dioxide environment in facilities is essential for crop growth. The design of an environment carbon dioxide precision control system based on wireless sensor network (WSN) was introduced, which was composed of master node, monitoring node and fertilizing node. Information interaction among nodes were achieved with ZigBee protocol, which was a general protocol for wireless sensor network. Monitoring node was used to monitor real-time carbon dioxide concentration, temperature and light intensity in facilities environment. With a feedback control, master nodes achieved dynamic adjustment of carbon dioxide based on different growing seasons for various plants in facilities and combining optimum thresholds of temperature and lights. To improve the disadvantage of uneven carbon dioxide implementation, double M type conductive pipe was deployed in facilities. Meanwhile, different hole sizes on the pipe were designed for acquiring the same instantaneous flow. In collaboration with convection device, fertilizing node controlled the carbon dioxide emissions through gas tank passing and breaking, and guaranteed the uniformity of carbon dioxide implementation. The results show that the relative error between the target and the real-time value is less than 3.5% in solar greenhouse with area of 36.66m2. The designed experiment result shows that the variation coefficient of carbon dioxide concentration among monitoring nodes is less than 2.93% in glasshouse with area of 27.74m2, which proves that the system can realize precise and uniform fertilizing of carbon dioxide.

Abstract:The sodium salts in black liquor exists in two main forms: as phenolic sodium (—CONa) and carboxylate sodium (—COONa) groups (PCSG) forming a part of alkali lignin or as dissolved salt (NaOH and Na2CO3). The purpose of this study is to investigate the effect of inorganic and organic bound sodium on the char characteristics of alkali lignin, char samples were prepared by a hightemperature furnace as pyrolysis temperature at 400℃, 600℃ and 800℃, respectively. The char morphology, elemental distribution, gasification reactivity and catalytic mechanism were studied by scanning electron microscopy/energy spectrum analyzer (SEM/EDS), thermal gravimetric analysis (TG) and thermogravimetric analyzer coupled with Fourier transform infrared spectrometry (TGA-FTIR). The results suggested that for organic bound sodium lignin, a large number of bubbling occurred at the char surface and the sodium content of char surface was increased from 5.36% to 15.72% as the pyrolysis temperature was increased from 400℃ to 800℃. Meanwhile, the carbon conversions of CO2 and steam gasification were increased by 30% and 20%, respectively. The effect of organic bound sodium on the reaction characteristic was varied with temperature. When the reaction temperature was lower than 600℃, the reaction mainly occurred between —CO2Na and char. As the temperature was in the range of 600~800℃, both —CO2Na and —CONa can react with char. As the temperature was higher than 800℃, the reaction mainly occurred between —CONa and char.

Abstract:Due to the operation of cutting, fresh-cut fruits and vegetables are susceptible to microbial infection. In order to extend the shelf life of fresh-cut fruits and vegetables, the effects of the concentration and amount of available chlorine of slightly acidic electrolyzed water (SAEW) and the pressure level and holding time of high pressure (HP) on sterilization of fresh-cut carrots were studied through single factor experiment. Consequently, the combination treatment conditions were as follows: the concentration of available chlorine of slightly acidic electrolyzed water was 30mg/L and the amount of available chlorine of slightly acidic electrolyzed water was 200mL;the pressure level ranged from 100MPa to 400MPa, holding time was 5min and the total processing time was 15min. Fresh-cut carrots and apples were treated by the different combined treatments, and both brain heart infusion agar (BHIA) and vilolet red bile agar (VRBA) were used for the detection of E. coli. With the aim to explore the inactivation effects of combination treatment, during the detection, the slightly acidic electrolyzed water was chosen instead of HP sterilized water to do further test. The result shows that combined treatment can improve the efficiency of inactivation, but the enhancement was not significant at lower pressure. At 400MPa, HP treatment combined with SAEW displayed the most significant enhancement of inactivation efficiency, where E. coli could not be detected on fresh-cut carrot, but some E. coli was still detected on the fresh-cut apples in BHIA. When comparing the results in BHIA and VRBA, it can be seen that the SAEW showed significant lethal effect on E. coli, while HP showed both lethal and sublethal effect on E. coli.

Abstract:Moisture adsorption of brown rice is the fundamental reason for kernel cracking, which restricts the quality and texture of germinated brown rice. Moisture adding technique needs to be further optimized to reduce cracked kernel percentage of brown rice before germination. The whole moisture adding interval was divided into 12 intervals of 13.0%~14.4%,14.4%~15.5%,15.5%~16.5%,16.5%~17.8%,17.8%~19.2%,19.2%~20.9%,20.9%~22.2%,22.2%~23.2%,23.2%~24.3%,24.3%~25.6%,25.6%~27.3% and 27.3%~29.0%, and moisture adding procedure was finished within 1.0min,1.5min,2.0min,2.5min,3.0min,3.5min,4.0min,4.5min,5.0min and 5.5min respectively. In each interval, cracked kernel additional percentage was found to first decrease and then increase in range of moisture adding percentage. Mathematical models to describe variation in cracked kernel additional percentage were established, and derivation to models was applied to determine the optimal moisture adding rate. Optimal moisture adding rates for brown rice with moisture of 13.0%,14.4%,15.5%,16.5%,17.8%,19.2%,20.9%,22.2%,23.2%,24.3%,25.6% and 27.3% were 0.3212%/min,0.2851%/min,0.4338%/min,0.3299%/min,0.3485%/min,0.4382%/min,0.4993%/min,0.5494%/min,0.6396%/min,0.7352%/min,0.8735%/min and 0.8436%/min, which varied first slowly, then rapidly and finally slowly within the whole moisture adding interval. Based on above values, the mathematical model to describe moisture adding rate within the whole moisture adding interval was obtained. Compared with traditional segmented moisture adding technique, optimized moisture adding technique resulted in decreases of (41.48±0.15)% and (43.67±0.26)% in the cracked kernel additional percentage of non-germinated and germinated brown rice, respectively, while the germination rate and γ-aminobutyric acid content of germinated brown rice had increases of (6.92±0.25)% and (25.03±0.18)%. The optimized technique featured by continuous varied adding rate provides a reference method for high quality production of germinated brown rice.

Abstract:The drying mechanism of combined side-heat infrared radiation and convection (IRC) grain dryer is more complicated compared with that of the traditional convection drying. In order to explore the model of uncertain system like the grain drying and application of BP artificial neural network method, a new intelligent prediction model for the combined side-heated IRC dryer used to predict the outlet core moisture content ratio and drying rate is developed based on BP neural network algorithm. The model which has three layer neural network structures (8-10-1) is trained and tested based on the train data set and test data set by programming the model in Matlab. The model inputs are the eight influence variables of grain dryer, and the model output is the outlet grain moisture ratio of the dryer or the drying rate. The corresponding mathematical expressions of moisture ratio and drying rate model are also given, and the determination coefficients (R2) of model prediction are 0.9989 and 0.9980, and the root mean square errors (RMSE) are 0.009 and 0.0041, respectively. The predicted results are fitted well with the measured data, and the prediction accuracy is high. In addition, combined with the experimental drying conditions, the prediction results of the model are analyzed and summarized. According to the same method, the prediction model of outlet moisture ratio for the counter-current grain drying is also successfully established. By the comparison of predicted performance curves for two types of drying process, it is proved that the combined side-heat IRC drying has faster drying rate and less time to dry to the target moisture value than those of the conventional hot air convection drying. It can be used to predict the drying performance of different drying processes and to realize the comparison of different drying processes. In addition, compared with other grain drying mathematical models, various influence factors of grain drying can be comprehensively considered, which can provide a new modeling method for the complex system like the drying of combined side-heat IRC.

Abstract:In order to meet the requirements for human machine optimization design, the dynamic test system was designed based on the chassis dynamometer, which was used to evaluate the parking brake performance of passenger vehicle. Firstly, the feasibility analysis was conducted for the test scheme, and the test model for the equivalent angle of parking slope was put forward. Then, the test system was designed, in which the CompactRIO (cRIO) controller and the related C modules made by National Instrument Company of America were selected as the core components. Under the consideration of the general installing requirements, both the handle force sensor and the angle sensor were selected, and their related mounting brackets were designed. Besides, the LabVIEW was employed to program the code for the controller and the host computer, in which the functions, such as data collection, data processing, communication and GUI, were conducted reliably in real time. Thirdly, the test method was explored, in which these influence factors were taken into consideration, such as elastic elements rebound, surface state of brake drum or disk, processing technology. In particular, the method of probability and statistics were introduced to evaluate the parking brake performance. Finally, the test system was used to conduct several tests and it worked reliably, and it met the design requirements. The result showed that it was effective and plausible for the dynamometer based test system and the evaluation method proposed for the parking brake performance of passenger vehicle.

Abstract:Magneto-rheological (MR) damper is one kind of dampers using magnetorheological fluid as the working medium. The design and fabrication of a novel MR damper with parallel double coil are presented. Usually, MR damper with double or multi coil in serial is designed to obtain large damping force. This will lead to increase of MR damper length, and is not fit to limited installation space of length. The structural design of MR damper is focused to obtain required damping performance under limited dimension (especially the length). The technical originality is to propose a new MR damper configuration with the additional radial gap by double coil in parallel. The proposed MR damper is featured by the additional radial gap due to double coil in parallel. The conventional MR damper with serial double coil inevitably has two nonactive parts due to its structural features, while the proposed MR damper with parallel double coil has only one non-active part. In addition, the conventional MR damper with serial double coil has four magnetic poles, while the proposed MR damper with parallel double coil has two radial poles in addition to the four magnetic poles. A mathematical model for the proposed MR damper is developed. The conventional MR damper with serial double coil is also considered to compare damping performance with that of the proposed MR damper. The electromagnetic analysis for proposed and conventional MR damper is conducted to validate the principle of the proposed MR damper and obtain the magnetic properties of its magnetic circuit. After numerical comparison of the damping performances for the two MR damper designs, the MR damper with parallel double coil is chosen because of its better performance. The proposed MR damper is fabricated and investigated by means of experiment. According to the measured data, the proposed MR damper can provide much larger controllable damping force and almost twice the equivalent damping of the conventional MR damper.

Abstract:With the industry 4.0 embraced a number of contemporary automation, data exchange and manufacturing technologies, the autonomous driving system is widespread. In order to enable the autonomous driving, path following strategies are essential to maintain the normal work of the vehicles. The articulated frame steering vehicles (ASV) are flexible, efficient and widely implemented in agriculture, mining, construction and forestry sectors due to their high maneuverability. The articulated vehicle usually composes of two units, a tractor and a trailer, which are connected by an articulation joint. However, as the ASV dynamics are significantly different from the conventional vehicles with front wheel steering, the path following controller derived for conventional vehicles is considered not to be applicable for the ASVs. Thus the path following control is challenging the robustness. A path following strategy is proposed for the ASVs on the basis of reinforcement learning adaptive PID algorithm. The kinematic model of the ASV is derived by neglecting the vehicle dynamics. Three measurable errors are defined to indicate the deviation of real path from reference path, i.e., lateral displacement error, orientation error and curvature error. These errors are served as the inputs in order to synthesize the path following controller and the desired steering angle is served as the output of path following controller. Based on the PID algorithm, the reinforcement learning method is selected for optimizing the parameters of PID online to reduce the overshoot and chattering. Furthermore, the prototype test is conducted to evaluate the performance of the proposed control law. The result shows that compared with the traditional PID, reinforcement learning adaptive PID controller can restrain the overshoot and chattering efficiently and follow the reference path accurately.

Abstract:As a new smart material, dielectric electroactive polymers (DEAP) have shown great promise in the fields of sensing and actuation owning to their excellent overall performance, including large deformation, high efficiency and energy density. Based on the capacitance change principle of the polymer when deformed, a sensing cell composed of an outer frame, an inner frame and a sheet of DEAP film that was divided into four partitions coated with flexible electrode was designed and implemented. When the DEAP film was stretched or shrunk by the mobile inner frame, the flexible electrodes on both sides of the film come closer together or away each other, respectively, leading to changes in capacitance. A geometrical model of the proposed sensing cell was developed and the relationship between the capacitance of the sensing cell and the displacement of the inner frame was deduced. A differential approach was used to measure the variation of the capacitance of the parts face to face, and the capacitance difference of two opposite parts in function of the inner frame inplane displacement was developed. Moreover, 2-DOF angular sensor by the sensing cell was designed and applied to angle measurement, and similarly, a differential approach was used to obtain the curve of the capacitance difference with the joint’s rotational angle. The experimental sensitivities of X-translation, Y-translation, X-rotation and Y-rotation were respectively -57.2pF/mm, -58.0pF/mm, -139.4pF/(°) and 141.6pF/(°), which were agreed well with the theoretical results. The research result verifies the feasibility of the application of DEAP in displacement sensor and angle sensor.

Abstract:In order to solve the problem that information could be easily lost in the phase space constructed by the unit precision time series with finite length or containing noises, the method of predicting numerical control machine’s motion precision was put forward based on multivariate chaotic time series. Firstly, multiple characteristic quantity of motion precision were extracted from CNC machine tool. Delay time and embedding dimension of the multiple motion precision time series were worked out by the C-C algorithm. The low-dimensional sequences were mapped to high-dimensional space to establish a multi-precision state space by phase reconstruction of multivariate time series. The phase space established was the same topological isomorphism with the original system. The state space points’ track was described motion precision’s evolution in multivariate phase space. Then the principal component analysis was used to reduce dimensions of high dimensional phase space and remove redundant information. Finally, the state vector of the phase space was taken as a multi-dimensional input. The predicting model of wavelet neural network could be trained by the information constructed to achieve the motion precision prediction. The experiments results showed that the proposed method could well analyze the changing regulation of NC machine tools motion precision and the mean square error of prediction model was 0.0095. Compared with the way of prediction by the unit chaotic time series, it had better predictive effects, and its adaptability and practicality were stronger.

Abstract:Considering the intelligent development trend of manufacturing industry in current and the key role of CNC machine tool in modern manufacturing engineering, a multi-objective optimum seeking method of CNC machine tool is proposed, which combines the advantages of quality function deployment (QFD), fuzzy linear regression, and zero-one goal programming (ZOGP). On the basis of studying intelligent manufacturing’s specific requirements, QFD is utilized for examining the causal relationships between intelligent manufacturing’s requirements and CNC machine tool’s performances. The intelligent manufacturing’s requirements are incorporated into machine tool selection by house of quality (HOQ). Fuzzy linear regression is used to determine the extent of functional relationships between intelligent manufacturing’s requirements and machine tool’s performances in the HOQ. The weight coefficients of CNC intelligent manufacturing’s requirements indexes are calculated by analytic hierarchy process (AHP). Zero-one goal programming is used to select the optimal CNC machine tool. Taking the CNC machine tool’s multi-objective decision problem in constructing an intelligent manufacturing platform as application case, and the optimal one with high comprehensive performance is selected from five alternative CNC machine tools. The study result shows that the proposed multi-objective optimum seeking method of intelligent manufacturing oriented CNC machine tool has high practicability.

Abstract:A novel algorithm based on nonsubsampled Shearlet transform (NSST), Gaussian multi-scale space and anisotropic diffusion was proposed for detecting crack defects with uneven background, low contrast, noise corruption and textured interference in magnetic tile surface images. Firstly, NSST was employed to decompose the source magnetic tile image into one low-pass subband and a series of high-pass subbands. Then the anisotropic diffusion and the modified γ enhancement method were applied to remove the noise and enhance the weak object information in the high-pass subbands, respectively. Meanwhile, the background was estimated in the Gaussian multi-scale space constructed by convolving the low-pass subband with a varied two-dimensional Gaussian functions, and the even low-pass object could be obtained by using background subtraction. Finally, inverse NSST was utilized to reconstruct the enhanced object image which was free from noise and grinding texture interference, and crack defects could be segmented from the reconstructed image by applying the adaptive threshold method and regional connectivity function. Experimental results demonstrate that compared with four existing methods (OTSU method, method based on the adaptive morphological filtering, method based on Curvelet transform and texture feature measurement and method based on Shearlet transform), the proposed method achieves better performance in terms of defect detection accuracy.