Soil Strength Profile Sensor Research Articles

Design and development of a front mounted on-the-go soil strength profile sensor

Soil compaction is a great problem since it affects crop growth and yield. The causes of soil compaction are the management practices in agricultural production. A common practice is to implement subsoiling at a few centimeters below the hardpan. Management practices, field traffic, and variations of the soil?s physical and chemical properties throughout the field cause variations in the soil compaction degree and depth. Subsoiling at certain depths can cause excessive energy consumption at a high cost. Therefore, agricultural tillage equipment could be improved by varying the tillage depth. Soil strength is the main indicator that depends on several soil properties such as bulk density, moisture, and organic soil texture content for determining the compaction level. The goal of this study was to develop an on-the-go sensor. It measured soil strength at multiple depths in order to determine the depth of the compacted soil layers. The mechanical frame of the sensor (body) was designed using Solidworks 3D CAD Design Software. Depth measurements were based on the Programmable Logic Controller (PLC) system. The data-gathering algorithm was developed with Phoenix Contact PC WORX software. It recorded the data flowing from the load cells, calculated the depth of the hardpan, and altered the depth of the chisel. In order to calibrate the load cell and compensate for differences among the load cells, static tests were conducted in a laboratory. The consistency of the sensing tips in terms of the input load - output load harmony was in linear format with higher R2 values ranging between 0.98 and 0.99. Consequently, the on-the-go soil sensor was developed for variable depth subsoiling. Dynamic tests revealed that the sensor was capable of monitoring the soil strength through the profile in order to determine the compaction level and hardpan depth. Moreover, the sensor was capable of adopting itself to crop varieties that have different critical compaction levels for root penetration.

Design of a Soil Cutting Resistance Sensor for Application in Site-Specific Tillage

One objective of precision agriculture is to provide accurate information about soil and crop properties to optimize the management of agricultural inputs to meet site-specific needs. This paper describes the development of a sensor equipped with RTK-GPS technology that continuously and efficiently measures soil cutting resistance at various depths while traversing the field. Laboratory and preliminary field tests verified the accuracy of this prototype soil strength sensor. The data obtained using a hand-operated soil cone penetrometer was used to evaluate this field soil compaction depth profile sensor. To date, this sensor has only been tested in one field under one gravimetric water content condition. This field test revealed that the relationships between the soil strength profile sensor (SSPS) cutting force and soil cone index values are assumed to be quadratic for the various depths considered: 0–10, 10–20 and 20–30 cm (r2 = 0.58, 0.45 and 0.54, respectively). Soil resistance contour maps illustrated its practical value. The developed sensor provides accurate, timely and affordable information on soil properties to optimize resources and improve agricultural economy.

Relating mobile sensor soil strength to penetrometer cone index

A horizontally operating on-the-go soil strength profile sensor (SSPS) was previously developed so that the within-field spatial variability in soil strength could be measured at five evenly spaced depths down to 50cm. Force divided by the base area of the sensing tip of the SSPS was defined as a prismatic soil strength index (PSSI, MPa), similar to the cone index (CI, MPa) of a vertically operating cone penetrometer. This study was conducted to establish theoretical and empirical relationships between PSSI and CI data to aid interpretation of PSSI data with respect to the many previous CI studies. Comparison of mathematical soil failure models for the SSPS and a conventional cone penetrometer, along with a sensitivity analysis of model parameters documented patterns of CI and PSSI in different soil and operating conditions. Patterns for both the soil strength indices were: (1) linear as a function of unit weight of soil, cohesion, adhesion, and operating depth, (2) exponential as a function of internal friction and soil-tool friction angles, and (3) quadratic as a function of operating speed. When a single model parameter was varied, the simulated CI and PSSI data showed highly significant linear relationships. Field data showed that, in general, both CI and PSSI were greater with higher bulk density, lower apparent soil electrical conductivity (ECa, where lower values indicate coarser texture), and lower gravimetric soil water content. Relationships between soil strength indices and the other measured soil variables were different when the data were divided into sub-groups by operating depth and ECa range. In models estimating CI, the effects of PSSI and its interaction with other variables were relatively clear at 30- and 40-cm depths. CI prediction models with the highest coefficients of determination were also found at these depths. Across entire fields, including operating depth in the regression model decreased RMSE values slightly from 0.35 to 0.32MPa and from 0.53 to 0.51MPa for the two test sites. These results would be useful to understand different approaches to soil strength measurement and to relate data obtained with the SSPS to the extensive research literature where CI has been used to quantify soil strength and manage the soil for better plant growth.

이동식 토양 강도 센서 데이터 주파수 분석

As agricultural machinery has become larger and tillage practices have changed in recent decades, compaction as a result of wheel traffic and tillage has caused increasing concern. If strategies to manage compaction, such as deep tillage, could be applied only where needed, economic and environmental benefits would result. For such site-specific compaction management to occur, compacted areas within fields must be efficiently sensed and mapped. We previously developed an on-the-go soil strength profile sensor (SSPS) for this purpose. The SSPS measures within-field variability in soil strength at five soil depths up to 50 cm. Determining the variability structure of SSPS data is needed for site-specific field management since the variability structure determines the required intensity of data collection and is related to the delineation of compaction management zones. In this paper, soil bin data were analyzed by a spectral analysis technique to determine the variability structure of the SSPS data, and to investigate causes and implications of this variability. In the soil bin, we observed a repeating pattern due to soil fracture with an approximate 12- to 19-cm period, especially at the 10-cm depth, possibly due to cyclic development of soil fracture on this interval. These findings will facilitate interpretation of soil strength data and enhance application of the SSPS.

Soil Bin and Field Tests of an On-The-Go Soil Strength Profile Sensor

An on-the-go soil strength profile sensor (SSPS) was previously developed to measure the within-field spatial variability in soil strength at five evenly spaced depths up to 50 cm. In this article, performance of the SSPS was evaluated using soil bin and field data. First, the SSPS was tested in a soil bin at different depths (10, 20, and 30 cm), forward speeds (from 0.5 to 3.0 m s-1), and compaction levels (high and low). Second, data were collected in two fields having variable soil texture, bulk density, and water content. Prismatic soil strength index (PSSI, defined as force divided by the base area of the horizontally operating prismatic tip) and penetrometer cone index were measured at five depths (10, 20, 30, 40, and 50 cm) across entire fields and also more intensively in four 10 10 m areas selected for soil texture differences. Auxiliary data collected were soil bulk density, soil water content, and apparent soil electrical conductivity (ECa). When the SSPS was tested in the soil bin, increases in PSSI with speed were less than 15% from 0.5 to 3.0 m s-1 operating speed. Based on soil bin results, we selected 1.5 m s-1 as a maximum field data collection speed, below which speed effects on PSSI were deemed negligible. Mean PSSI values collected in adjacent, parallel transects were not statistically different, confirming the repeatability and stability of soil strength sensing with the SSPS. Field data showed that, in general, PSSI was higher at locations with lower ECa, lower water content, and greater bulk density. Results of stepwise multiple linear regression showed that variability in PSSI was better explained when interactions among the soil variables were included as independent variables and when data were grouped into subsets by depth and/or ECa level. Over entire fields, R2 values for estimating PSSI were 0.66 and 0.61 for a claypan soil field and a flood plain field, respectively. These results will be useful for interpreting PSSI and for future applications of the SSPS in crop management, e.g., delineation of highly compacted within-field areas and control of variable tillage operations.

On-the-Go Mapping of Soil Mechanical Resistance Using a Linear Depth Effect Model

An instrumented blade sensor was developed to map soil mechanical resistance as well as its change with depth. The sensor has become a part of the Integrated Soil Physical Properties Mapping System (ISPPMS), which also includes an optical reflectance and a capacitor-based sensor implemented to determine spatial variability in soil organic mater and water content, respectively. The instrumented blade of the ISPPMS was validated in laboratory conditions by applying known loads. It was also tested in the field by comparing sensor-based estimates with measurements produced using a standard vertical cone penetrometer and another on-the-go sensor, the Soil Strength Profile Sensor (SSPS), consisting of five prismatic-tip horizontal penetrometers located at fixed depths. The comparison resulted in reasonable linear relationships between corresponding parameters determined using the three different methods. The coefficient of determination (r2) for average soil mechanical resistance was 0.32 and 0.57 when ISPPMS-based estimates were compared with the standard cone penetrometer and the alternative on-the-go sensor (SSPS), respectively. Depth gradients of soil mechanical resistance obtained using cone penetrometer and ISPPMS methods were correlated with r2 = 0.33. Observed differences in estimated parameters were due in part to the difficulties with obtaining data representing the same depths and in part to differences in sensor geometry and operating conditions, particularly when comparing the on-the-go sensors to the cone penetrometer. Based on its operation during Missouri field mapping, the instrumented blade proved to be a rugged and inexpensive sensor suitable for studying the spatial variability of the physical state of soils in the upper 30 cm of the profile.

Field comparison of two prototype soil strength profile sensors

Soil compaction that is induced by tillage and traction is an ongoing concern in crop production, and also has environmental consequences. Although cone penetrometers provide standardized compaction measurements, the pointwise data collected makes it difficult to obtain enough data to represent within-field variability. Moreover, penetrometer data exhibit considerable variability even at a single location, requiring several measurements to obtain representative readings. For more efficient data collection, on-the-go compaction sensors that obtain data at multiple depths are being developed by several research groups. The objective of this research was to evaluate and compare the field performance of two on-the-go compaction sensors. Tests were conducted at two central Missouri field sites where soil types ranged from sandy loam to clay. The soil strength profile sensor (SSPS) measured compaction to a 50-cm depth on 10-cm intervals. The soil compaction profile sensor (SCPS) also used five sensing elements and obtained data to 40.6 cm on a 7.6-cm interval. Cone penetrometer measurements of compaction were obtained at intervals along each transect for comparison. Data were compared between the two on-the-go sensors and were also related to penetrometer and soil property data. The repeatability of SCPS data was somewhat better than that of SSPS data. Data from the two sensors were linearly related, with similar regression equations for each individual site and for both sites combined. The agreement between SCPS and SSPS data ( r 2 = 0.56 over all sites and depths) was much better than between sensor and penetrometer data ( r 2 = 0.19–0.20). Maps of SCPS and SSPS data for a 13.5-ha field site showed very similar patterns. Maps of penetrometer data were also similar to those of on-the-go sensor data, but showed fewer spatial details. Variation in soil strength appeared to be primarily related to variations in soil physical properties (e.g., texture, water content). Due to the similarity between SCPS and SSPS data, we conclude that measurements obtained with the two on-the-go soil sensors were affected similarly by soil strength variations within the study sites. Side-by-side comparison of the on-the-go sensors provided a convenient approach to validate sensor performance. The study also provided information to improve on-the-go sensor design and to relate sensor data to other measures of soil compaction.

DESIGN AND VALIDATION OF AN ON-THE-GO SOIL STRENGTH PROFILE SENSOR

Soil strength has traditionally been determined using the cone penetrometer, an instrument that provides highlyvariable discrete point measurements, making it difficult to detect statistically significant differences in the soil strengthprofile among treatments or locations. Generally, this problem has been addressed by obtaining a large number ofmeasurements, a process that is time-consuming and labor-intensive. Our objective was to develop a soil strength profilesensor (SSPS) that could take measurements continuously and more efficiently while traveling across the field. The on-the-goSSPS was designed and fabricated using an array of load cells, each of which was interfaced with a soil-cutting tip. Thesemultiple prismatic tips were extended forward from the leading edge of a vertical blade and spaced apart to minimizeinterference from the main blade and adjacent sensing tips. Prismatic soil strength index (PSSI, MPa) was defined as the forcedivided by the base area of the sensing tip. The sensing tip had a 60 cutting or apex angle and a base area of 361 mm2. Thedesign maximum operating depth was 0.5 m, and the upper limit and resolution of soil strength were 19.4 and 0.14 MPa,respectively. Field tests determined that the optimum extension and spacing of the cutting tips were 5.1 and 10 cm,respectively. A significant (. = 0.01) linear relationship between PSSI and penetrometer cone index (CI), with a slope ofapproximately 0.6, was found for field data collected at a 30 cm depth. The ability to develop such relationships comparingpenetrometer and SSPS data will allow SSPS data to be interpreted with respect to the available body of penetrometerliterature.

SOIL FAILURE MODELS FOR VERTICALLY OPERATING AND HORIZONTALLY OPERATING STRENGTH SENSORS

Soil strength, or mechanical resistance of a soil to failure, has been widely used to estimate the degree of soilcompaction. Conventional measurements with cone penetrometers are laborious; therefore, an on-the-go soil strength profilesensor that collects data dense enough to show the spatial within-field variability in soil strength would be a desirablealternative. Because soil failure involves complex interactions among many variables, determining design parameters of asoil strength sensor and interpreting test results could be improved with a theoretical understanding of the soil failure process.Mathematical models to estimate the force required to penetrate (cut and displace) soil with a prismatic cutter travelinghorizontally and with a cone penetrometer traveling vertically were developed based on the passive earth pressure theory andthe concept of a variable failure boundary. Both models were expressed as additive forms of density, cohesion, and adhesioncomponents of the soil, with each effect multiplied by a corresponding dimensionless number. Charts of dimensionlessnumbers were developed to investigate the behavior of each strength component at various values of soil internal frictionangle, soil-metal friction angle, and tool cutting angle. The models were used in simulation to optimize design parametersof the sensor, including component dimensions and the location and spacing of sensing elements. Based on this optimization,a prismatic sensing tip with a 3.61 cm2 base area and a 60 cutting angle was selected, and the corresponding simulatedmaximum force and strength measurements were 2.2 kN and 6.0 MPa when operating at speeds up to 5 m s-1. Model validationshowed that the extension of the failure boundary was significantly correlated with soil properties such as bulk density, watercontent, and internal friction angle. The variable failure boundary model developed in this study more consistently andaccurately represented field data than did three previously developed modeling approaches.