A remote irrigation monitoring and control system (RIMCS) for continuous move systems. Part B: field testing and results

Precision irrigation systems can have inherent errors that affect the accuracy of variable water application rates controllers, as well as affect the controllers’ performance when evaluated on different continuous move irrigation systems configurations. The objective of this study was to assess the performance of a remote irrigation monitoring and control system (RIMCS) installed on two separate linear move (LM) irrigation systems. The RIMCS varies water application rates by pulsing nozzles controlled by solenoids connected via relays to a single board computer (SBC) with wireless Ethernet connection to a remote server. The system also monitors irrigation system flow, pressure, position and wireless field sensor networks. The system was installed on a LM irrigation system in Prosser, Washington, USA and on a LM in the Nesson Valley of North Dakota, USA. For the LM at Prosser, four pre-defined irrigation patterns were imposed and variable rates were applied as a percentage of the nozzle base application rate. Each nozzle was pulsed across the span length and along the LM travel direction. For the LM at the Nesson Valley, a quadratic pattern was imposed pulsing banks of nozzles along the LM travel direction. Standard catch can tests were performed and the system performance was evaluated by comparing measured catch can water depths with pre-determined target values. The RIMCS accuracy was found to be in the range of the LM uniform water depth application uniformity coefficients of 88–96%. The RIMCS was successfully transferred to another LM in North Dakota as indicated by the relatively low variable rate application errors of –8.8 ± 8.1% and −0.14 ± 6.7% for the two spans.     

基于PID算法的水稻直播机播量控制系统的设计与试验

【目的】为了解决现有的机械式水稻直播机镇压轮传动播种导致的漏播以及播量无法同步均匀调节的问题,实现水稻直播机播量自动精准调节。【方法】对现有苏南地区传统机械式水稻直播机进行自动化改造,设计了基于PID调速算法的水稻直播机播量控制系统。该系统在田间播种作业时,由设计的测速轮采集机具作业速度,结合设定的目标播种量和机具作业速度,依据播量控制策略得到排种轴理论转速;利用PID调速算法和编码器测到的排种轴反馈转速对直流电机进行闭环控制,可在线无极调节播量,从而实现精准播种。【结果】该系统排种电机空载时转速调整时间小于0.63 s,最大超调量8.21%,施加12.5 N·m负载时,排种电机最长回调时间为0.32 s。目标设计播量对应转速范围内,转速控制误差最大值小于7.21%,转速误差小于5.21%,田间播量误差小于4.92%。田间车速阶梯变化时,排种转速跟随响应及时,具有较高的排种同步性,与传统机械式水稻直播机相比播量调节性能显著提高。【结论】该系统自动化改造简便,重点改进了播量调节机构,提高了传统播种机播种性能,对传统机械直播机具有较高适配性。     

Robotic Weed Control System for Tomatoes

A real-time intelligent robotic weed control system was developed for selective herbicide application to in-row weeds using machine vision and precision chemical application. The robotic vision system took 0.34s to process one image, representing a 11.43 cm by 10.16 cm region of seedline containing 10 plant objects, allowing the prototype robotic weed control system to travel at a continuous rate of 1.20 km/h. The overall performance of the robotic system in a commercial processing tomato field and in simulated trials is discussed.     

Measurements of cadmium in soil extracts using multi-variate data analysis and electrochemical sensors

There is a growing awareness of potential health risks due to exposure to heavy metals. One source of uptake is via agriculture, when heavy metals in the soil are taken up by the crop. The metal cadmium holds a special position, since it is considered to be a health risk, even at the low concentrations observed in our food supply, furthermore, it is ranked as eight on the top 20 hazardous substances list. Two measurement systems are described based on stripping voltammetry for analysis of cadmium. One is based on a three metal direct probe system (TMDPS) with three working electrodes (platinum, gold and rhodium), combined with a polishing unit, the other is an automatic flow through system, using one working electrode of gold, also equipped with a polishing unit. A number of different soils were extracted with an ammonium-lactate solution and analyzed with the systems, and the data obtained were subjected to multi-variate data analysis (MVDA). Using modeling based on partial least square (PLS), concentrations of cadmium in the soil extracts could be predicted for the TMDPS in the concentration area 0.5–10 μg/l with a root mean square error of prediction (RMSEP) of 0.8 μg/l and a relative predicted deviation (RPV) of 2.0. One sample could be analyzed in 4 min. It was also shown that by using different PLS models, the concentration of the elements copper, aluminum, lead and iron could be predicted. The possibilities of using the technique for field use were also evaluated by studies of mixtures of different soils in 0.1 M HNO₃ solution, the time for an analysis was, however, rather large, around 20 min.     

Small-radius turning performance of an articulated vehicle by direct yaw moment control

This paper reports the turning performance of an articulated vehicle in which applying direct yaw-moment control is applied to reduce the turning radius. In the proposed method, a braking force is applied to the inner tires when the articulation angle reaches its maximum in turning, which generates a yaw-moment around the vehicle's centre of gravity. The yaw-moment allows the vehicle to turn in a small radius. To evaluate the performance in tight turns, experiments were conducted using a wheel loader on paved ground. The vehicle's turning radius, yaw rate and side-slip angle were determined from the data measured using two global positioning systems and a fibre-optic gyro sensor. In addition, results of a simulation were compared with experimental results from a test vehicle. The turning radius at a braking pressure of 4 MPa was at least 0.41 m smaller than that of 0 MPa. Experimental and simulated results proved that generating a yaw-moment by applying one-sided braking forces during turning decreases the turning radius.     

Automatic wheel slip control system in field operations for 2WD tractors

A microcontroller based automatic wheel slip control system was designed and developed for 2WD tractors. The system continuously measures wheel slip under field conditions and generates commands for depth adjustment if the wheel slip falls outside the desired range. Wheel slip was calculated using the actual and theoretical speeds of the tractor obtained by measuring the rotational speed (rpm) of front and rear wheels, respectively. The developed system was installed on a test tractor and the performance was evaluated with different implements under varying field conditions. The performance data indicated a significant reduction in fuel consumption per hectare (20–30%), increase in field capacity (7–38%), and gain in tractive efficiency (4–10%) with slip control system versus the existing draft control system. The slip control system is also expected to reduce the operator’s effort as it adjusts the depth control lever automatically in response to variation in the soil conditions within the field.     

Evaluation of an on-the-go technology for soil pH mapping

Since conventional sampling and laboratory soil analysis do not provide a cost effective capability for obtaining geo-referenced measurements with adequate frequency, different on-the-go sensing techniques have been attempted. One such recently commercialized sensing system combines mapping of soil electrical conductivity and pH. The concept of direct measurement of soil pH has allowed for a substantial increase in measurement density. In this publication, soil pH maps, developed using on-the-go technology and obtained for eight production fields in six US states, were compared with corresponding maps derived from grid sampling. It was shown that with certain field conditions, on-the-go mapping can significantly increase the accuracy of soil pH maps and therefore increase the potential profitability of variable rate liming. However, in many instances, these on-the-go measurements need to be calibrated to account for a field-specific bias. After calibration, the overall error estimate for soil pH maps produced using on-the-go measurements was less than 0.3 pH, while non-calibrated on-the-go and conventional field average and grid-sampling maps produced errors greater than 0.4 pH.     

The impact of various sprinkler irrigation patterns on spatial soil moisture variation in Vertisols

The objective of this research was to assess the effect of soil cracks on soil moisture distribution under various sprinkler irrigation applications and to identify the optimal irrigation strategy that enhances soil moisture distribution and reduces water drainage for the upper soil layer 0–250 mm. The assessment was made for six irrigation events: the first two were for 10 and 46 mm water applications using a hand shift-set sprinkler system. The second set was for 43 and 19 mm water applications using the lateral move system with fixed sprayer heads and the third pair of events were for 43 and 32 mm water applications using the lateral move system with rotating sprinklers. The experiments were conducted on two adjacent fields at the University of Queensland, Gatton, Australia. Each field was divided into 2 m × 2 m grids that covered 62 sampling locations. For each event, the initial soil moisture content (SMC) was measured at each sampling location before irrigation. After irrigation, catch can readings were recorded for each sampling location. After 12 h overnight, the second set of soil moisture measurements was taken at each location. The area1 distribution of SMC for the studied applications was quantified. An attempt was made to identify the relationship between the applied water uniformity using catch cans and the soil moisture uniformity using gravimetric water content measurements. The study also took into consideration variables that could affect the soil physical and hydrological properties including the field slope, the soil texture, the infiltration rate, the salt content and the soil organic matter content of the two fields. Since the soils were cracking clay Vertisols, further analyses were conducted on the crack dynamics, size and distribution using image analysis techniques. The research findings demonstrated that the cracks were the main contributors to water drainage below 250 mm soil depth due to the micro-run off from the crust surface to the cracks. The cracks ranged from a few millimeters to more than 40 mm in width. It was observed that the cracks which were wider than 15 mm remained open after irrigation for the specified application rates. Improving the irrigation system application uniformity did not always result in higher uniformity of the surface SMC (0–250 mm). The event that best enhanced soil moisture distribution and thus improved soil moisture recharging was observed after the sixth irrigation event when the field received 32 mm water application. The soil was at a relatively high initial SMC of 25%, (which represented 43.3% of the plant available water range) and the sprinkler water uniformity was rather high above 87% Christiansen coefficient of uniformity (CUc). At this SMC, the extent of soil cracking is limited.     

使用网络遥控渔船机械手的系统研究

渔业船舶上的机械手臂可以帮助人们在恶劣环境中实现很多操作作业,为了充分发挥渔船机械手的自主性以及他所具备的主观能动性,实现了一种在非结构环境下使用网络进行遥控渔船机械手。阐述了一种使用Agent的网络遥控渔船机械手的控制系统结构,对系统中主要部分的功能进行了分析,并对各Agent的实现方法进行了一定的阐述。     

Real-time controlled direct injection system for precision farming

Real-time controlled pesticide application requires a fast reacting system, enabling continuous variation of pesticide type and concentration based on a control signal. Direct injection systems meet the requirements for such application; however there are significant differences in the response time and quality of single system designs. This article discusses the complex of problems in direct injection systems in connexion with real-time control and proposes optimisations of system parts in order to reduce the response time and improve the quality of the process. The system response time was reduced to 160 ms for 1% output concentration by optimization of the control process, injection assembly and mixing chamber design.     

基于UWB定位的农业机械辅助导航系统设计与试验

【目的】低成本实现南方中小型田块中农业机械田间精确定位,降低农机操作人员劳动强度、提高农机作业效率。【方法】采用超宽带(Ultra wide band,UWB)技术对作业机械进行实时定位,通过位置解算算法,得到定位标签的三维精确位置坐标;利用位置校正算法,修正作业机械车身倾斜引起的田间定位误差;设计基于AB线的路径规划算法,实时规划作业路径并计算作业偏差;通过可视化人机交互界面为农机操作人员提供实时辅助驾驶信息。【结果】水田环境中,分别以0.5、1.0和1.5 m/s的速度沿规划路径行驶时,系统平均横向定位偏差均小于7 cm;当行驶速度大于1.0 m/s时,利用位置校正算法平均横向定位偏差降低了52.79%,标准差降低了49.82%,最大横向定位偏差降低了50.04%。搭载辅助导航系统进行田间插秧试验,各行作业轨迹与自身行拟合直线的平均横向偏差为5.90 cm,标准差为3.64 cm;各行作业轨迹与其规划直线路径的平均横向偏差为6.98 cm,标准差为4.95 cm。【结论】辅助导航系统具有较高的定位精度和良好的稳定性,成本低且通用性强,能够满足南方中小型田块中农业机械田间作业要求。研...     

Uniformity testing of variable-rate center pivot irrigation control systems

As water supplies become limited, agricultural water use needs to become more efficient to maintain current productivity levels. The efficiency of center pivot and linear move irrigation systems can be increased by matching the amount and rate of water application to specific soil conditions that vary in the field. Such site-specific application can be achieved by variable-rate control systems. Although such systems are being developed, their effects on center pivot and linear move uniformity have not been documented. The uniformity along the length of a center pivot and a linear move irrigation system was measured at two system movement speeds and three variable-rate settings. One variable-rate system is commercially available using pneumatically actuated solenoid valves to turn groups of sprinklers ON and OFF at fractions of a minute corresponding to the cycle rate, for example a 50% cycle rate is 30 s ON and 30 s OFF. The other variable-rate system used commonly available electric solenoid valves to accomplish the same task. Overall, the coefficient of uniformity and low quarter distribution uniformity averaged 93% and 0.90, respectively for the center pivot irrigation system; 84% and 0.74 for the linear move system. The results were not significantly (P > 0.05) affected by wind speed, cycling rate, or system movement speed. The type of nozzle did influence the uniformity because of the distinctly different application characteristics of rotator, fixed plate, and wobbling low pressure sprinklers. Thus, the variable-rate technologies tested under the conditions presented in this paper had at least as good uniformity as the center pivot and linear move systems when functioning in non-variable-rate mode.Mention of a trade name, proprietary product, or specific equipment does not constitute a guarantee or warranty by the University of Florida or the University of Georgia and does not imply approval of a product or exclusion of others that may be suitable.     

Verification of color vegetation indices for automated crop imaging applications

An accurate vegetation index is required to identify plant biomass versus soil and residue backgrounds for automated remote sensing and machine vision applications, plant ecological assessments, precision crop management, and weed control. An improved vegetation index, Excess Green minus Excess Red (ExG − ExR) was compared to the commonly used Excess Green (ExG), and the normalized difference (NDI) indices. The latter two indices used an Otsu threshold value to convert the index near-binary to a full-binary image. The indices were tested with digital color image sets of single plants grown and taken in a greenhouse and field images of young soybean plants. Vegetative index accuracies using a separation quality factor algorithm were compared to hand-extracted plant regions of interest. A quality factor of one represented a near perfect binary match of the computer extracted plant target compared to the hand-extracted plant region. The ExG − ExR index had the highest quality factor of 0.88 ± 0.12 for all three weeks and soil-residue backgrounds for the greenhouse set. The ExG + Otsu and NDI − Otsu indices had similar but lower quality factors of 0.53 ± 0.39 and 0.54 ± 0.33 for the same sets, respectively. Field images of young soybeans against bare soil gave quality factors for both ExG − ExR and ExG + Otsu around 0.88 ± 0.07. The quality factor of NDI + Otsu using the same field images was 0.25 ± 0.08. The ExG − ExR index has a fixed, built-in zero threshold, so it does not need Otsu or any user selected threshold value. The ExG − ExR index worked especially well for fresh wheat straw backgrounds, where it was generally 55% more accurate than the ExG + Otsu and NDI + Otsu indices. Once a binary plant region of interest is identified with a vegetation index, other advanced image processing operations may be applied, such as identification of plant species for strategic weed control.     

Use of real-time extend GNSS for planting and inverting peanuts

Among the main techniques employed in precision agriculture, yield mapping and automatic guidance of agricultural machines are the best-known to farmers. The objective of this study was to evaluate, using statistical process control tools, the quality of automatic guidance using satellite signals, to reduce positioning errors and losses in peanut digging. The treatments consisted of the use of manual (operator guidance) and automatic (autopilot) guidance with RTX satellite signals in sowing and digging operations. The quality of the operation was evaluated after collection of 30 points spaced at 100 m for each quality indicator, which are the losses and the errors of alignment of the mechanised sets in sowing and digging operations. From the perspective of statistical control, manual guidance was shown to be compromised for the quality indicators of digging losses. Despite the instability in the sowing and digging operations, the use of automatic guidance proved to be accurate. The use of automatic guidance increases the precision and reduces overlaps (<?38 mm, as stipulated by the supplier) for sowing and digging. The manual sowing mean error between overlaps was stable; however, it did not remain constant over time.

     

Potential of a terrestrial LiDAR-based system to characterise weed vegetation in maize crops

LiDAR (Light Detection And Ranging) is a remote-sensing technique for the measurement of the distance between the sensor and a target. A LiDAR-based detection procedure was tested for characterisation of the weed vegetation present in the inter-row area of a maize field. This procedure was based on the hypothesis that weed species with different heights can be precisely detected and discriminated using non-contact ranging sensors such as LiDAR. The sensor was placed in the front of an all-terrain vehicle, scanning downwards in a vertical plane, perpendicular to the ground, in order to detect the profile of the vegetation (crop and weeds) above the ground. Measurements were taken on a maize field on 3 m wide (0.45 m²) plots at the time of post-emergence herbicide treatments. Four replications were assessed for each of the four major weed species: Sorghum halepense, Cyperus rotundus, Datura ferox and Xanthium strumarium. The sensor readings were correlated with actual, manually determined, height values (r² = 0.88). With canonical discriminant analysis the high capabilities of the system to discriminate tall weeds (S. halepense) from shorter ones were quantified. The classification table showed 77.7% of the original grouped cases (i.e., 4800 sampling units) correctly classified for S. halepense. These results indicate that LiDAR sensors are a promising tool for weed detection and discrimination, presenting significant advantages over other types of non-contact ranging sensors such as a higher sampling resolution and its ability to scan at high sampling rates.     

Development of a yield monitoring system for citrus mechanical harvesting machines

A load cell based yield monitoring system was developed for the Oxbo citrus mechanical harvesting machines. The yield monitoring system consisted of a GPS receiver, a mass flow sensor and data processing and storage units. The mass flow sensor consisted of four load cells attached to a carbon-fiber plate which sensed the impact force created by the oranges hitting the plate. A mathematical model was developed to relate the impact force to fruit mass. Laboratory tests were conducted on a test rig that replicated the flow of oranges to measure the accuracy of the system under a controlled environment. The system performed very well under laboratory conditions (R ² = 0.99 and an average error of 3.3%). In addition, a field test was conducted in a citrus orchard in Florida to evaluate the performance of the system under field conditions. Of the 72 rows used in the field test, the first 10 rows were used to calibrate the computed weight. A correlation of R ² = 0.97 between the actual weight and the computed weight was found from the field data with an average error of 7.81%.     

Soil water status mapping and two variable-rate irrigation scenarios

Irrigation is the major user of allocated global freshwaters, and scarcity of freshwater threatens to limit global food supply and ecosystem function—hence the need for decision tools to optimize use of irrigation water. This research shows that variable alluvial soil ideally requires variable placement of water to make the best use of irrigation water during crop growth. Further savings can be made by withholding irrigation during certain growth stages. The spatial variation of soil water supplied to (1) pasture and (2) a maize crop was modelled and mapped by relating high resolution apparent electrical conductivity maps to soil available water holding capacity (AWC) at two contrasting field sites. One field site, a 156-ha pastoral farm, has soil with wide ranging AWCs (116–230 mm m⁻¹); the second field site, a 53-ha maize field, has soil with similar AWCs (161–164 mm m⁻¹). The derived AWC maps were adjusted on a daily basis using a soil water balance prediction model. In addition, real-time hourly logging of soil moisture in the maize field showed a zone where poorly drained soil remained wetter than predicted. Variable-rate irrigation (VRI) scenarios are presented and compared with uniform-rate irrigation scenarios for 3 years of climate data at these two sites. The results show that implementation of VRI would enable significant potential mean annual water saving (21.8% at Site 1; 26.3% at Site 2). Daily soil water status mapping could be used to control a variable rate irrigator.     

Comparison of Different Sampling Scales to Estimate Weed Populations in three Soybean Fields

A study was conducted to evaluate the accuracy of different weed sampling scales to accurately describe populations in soybean. Three soybean fields were sampled at 8 and 6 weeks after planting in 1998 and 1999, respectively. All weed species were counted on a 10 m grid, using a 0.58-m² quadrat. Data were eliminated from the original 10 m grid sample of weeds for each field to develop 40 m, 60 m, and 80 m independent data sets. Distribution and population maps were interpolated using an inverse distance weighted method. Data were extracted from the interpolated maps at known coordinates so that the observed population and the predicted population could be compared. The 10 m grid served as a standard to which all others were compared. No differences in population accuracies between each scale were detected when results were compared on a per weed basis, except when weed populations were very high, generally exceeding 400 plants ha^–1. When the weed density was not at an extreme, the results from these data indicate the ability to describe or account for the weed population fairly accurately, when using coarser grid sizes. These results also suggest that when using a regular grid coordinate system as the sampling structure, an increase from a 10 m scale to an 80 m scale will not cause a significant loss of information when weed populations were not extreme and will provide the necessary information for making suitable weed treatment decisions. However, some small weed patches were not detected with the coarser sampling scales, and the larger sampling scales would not meet their needs if the producers objective is complete control of a species.     

Using a vision sensor system for performance testing of satellite-based tractor auto-guidance

A vision sensing system for the measurement of auto-guidance pass-to-pass and long-term errors was implemented to test the steering performance of tractors equipped with auto-guidance systems. The developed test system consisted of an optical machine vision sensor rigidly mounted on the rear of the tested tractor. The center of the drawbar hitch pin point was used as the reference from which to measure the deviation of the tractor's actual travel path from its desired path. The system was built and calibrated to a measurement accuracy of better than 2 mm. To evaluate the sensor, two auto-guidance systems equipped with RTK-level GNSS receivers were tested and the results for different travel speeds compared. Pass-to-pass and long-term errors were calculated using the relative positions of a reference at a collocated point when the tractor was operated in opposite directions within 15 min and more than 1 h apart, respectively. In addition to variations in speed, two different auto-guidance steering stabilization distances allowed for comparison of two different definitions of steady-state operation of the system. For the analysis, non-parametric cumulative distributions were generated to determine error values that corresponded to 95% of the cumulative distribution. Both auto-guidance systems provided 95% cumulative error estimates comparable to 51 mm (2 in.) claims and even smaller during Test A. Higher travel speeds (especially 5.0 m/s) significantly increased measured auto-guidance error, but no significant difference was observed between pass-to-pass and long-term error estimates. The vision sensor testing system could be used as a means to implement the auto-guidance test standard under development by the International Standard Organization (ISO). Third-party evaluation of auto-guidance performance will increase consumer awareness of the potential performance of products provided by a variety of vendors.