sensor systems for measuring soil compaction: review and analysis

c o m p u t e r s a n d e l e c t r o n i c s i n a g r i c u l t u r e 6 3 ( 2 0 0 8 ) 89–103

avai lab le at www.sc iencedi rec t .com

journa l homepage: www.e lsev ier .com/ locate /compag

Review

Sensor systems for measuring soil compaction:Review and analysis

A. Hemmata,∗, V.I. Adamchukb

a Department of Farm Machinery, College of Agriculture, Isfahan University of Technology, Isfahan 84156-83111, Iranb Department of Biological Systems Engineering, University of Nebraska-Lincoln, Lincoln, NE 68583-0726, USA

a r t i c l e i n f o

Article history:

Received 31 August 2007

Received in revised form

4 February 2008

Accepted 5 March 2008

Keywords:

Soil compaction

Penetrometer

Sensor fusion

Soil mechanical resistance

a b s t r a c t

Spatially variable soil compaction often causes inconsistent growing conditions in many

fields. Various soil compaction sensor systems have been deployed to obtain georeferenced

maps of certain state and behavioral properties (e.g., soil strength, water content, air per-

meability) related to compaction. This publication classifies different prototype sensors,

and reviews alternative measurement concepts from the viewpoint of soil mechanics. The

majority of discussion is dedicated to a diversified family of soil strength sensors devel-

oped around the world. Through the follow-up analysis, a concept of sensor fusion has been

emphasized as an option capable of improving future applicability of soil compaction sensor

systems, while implementing site-specific control of localized compaction occurrences.

© 2008 Elsevier B.V. All rights reserved.

Soil mechanics

Air permeability

W

C

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0d

ater content

ontents

1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .2. Soil strength sensors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

2.1. Draft and vertical force sensors . . . . . . . . . . . . . . . . . . .2.1.1. Bulk soil strength sensors. . . . . . . . . . . . . . . . .2.1.2. Vertically actuated sensors . . . . . . . . . . . . . . .

2.2. Soil profile sensors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .2.2.1. Tip-based sensors . . . . . . . . . . . . . . . . . . . . . . . . .2.2.2. Tine-based sensors . . . . . . . . . . . . . . . . . . . . . . . .

3. Fluid permeability sensors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4. Water content sensors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.1. Integrated tip penetrating sensors . . . . . . . . . . . . . . . . . . . . .4.2. On-the-go water content sensors. . . . . . . . . . . . . . . . . . . . . . .

∗ Corresponding author. Tel.: +98 311 391 3493; fax: +98 311 391 2254.E-mail address: [email protected] (A. Hemmat).

168-1699/$ – see front matter © 2008 Elsevier B.V. All rights reserved.oi:10.1016/j.compag.2008.03.001

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90 c o m p u t e r s a n d e l e c t r o n i c s i n a g r i c u l t u r e 6 3 ( 2 0 0 8 ) 89–103

5. Sensor fusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 996. Sensor application . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1007. Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101

1. Introduction

In agricultural systems, the risk of soil compaction increaseswith the growth of farm operations and the drive for greaterproductivity causing farmers to use heavier machinery. Exces-sive soil compaction has negative effects for agriculture andthe environment. It adversely affects soil structure, reducescrop production, increases runoff and erosion, acceleratespotential pollution of surface water by organic waste andapplied agrochemicals, and causes inefficient use of water andnutrients due to slow drainage. Different energy-demandingfield operations and other land management treatments havebeen performed to ameliorate unwanted soil compaction(Johnson and Bailey, 2002).

According to SSSA (1996), soil compaction is “the pro-cess by which the soil grains are rearranged to decrease voidspace and bring them into closer contact with one another,thereby increasing the bulk density.” The major contributorto forming soil compaction is various loads applied to thesurface of unsaturated soils (Gill and Vanden Berg, 1968).These loads may have either natural or artificial origin. Spoor(2006) identified five types of soil compaction encounteredin non-urbanized environments: (1) general compaction fromthe surface downward, caused by external loads, or formedthrough soil slumping and hard setting in structurally unsta-ble soils, (2) local compacted layers at a specific depth, createdby implements or tires below their working depth, (3) sub-soil compaction below normal tillage arising from stressesapplied by excessive surface loadings, (4) secondary com-paction where a weak soil zone above a compacted layer alsobecomes compacted through surface loadings, and (5) natu-ral deep compaction in the form of cemented layers or claypans.

Quantitative assessment of soil compaction is necessaryto determine its severity and to identify suitable mechanical,chemical, or biological methods of intervention recommendedfor ameliorating or controlling soil compaction (Fig. 1). Somecommon direct measures of soil compaction include: dry bulkdensity, dry specific volume, void ratio, and porosity (Culley,1993). In addition, an increase in soil compactness can bedetected using indirect measures that rely on either increasein soil strength (mechanical impedance to penetrating objects)or reduction in interconnected pore spaces (fluid permeabil-ity). While the direct measures tend to assess the state ofsoil compactness, the indirect measures indicate changes inbehavioral response frequently (but not always) related to soilcompactness (Johnson and Bailey, 2002).

are labor-demanding and cost-prohibiting for large-scalefield mapping. Therefore, determination of indirect mea-sures along with their geographical coordinates has becomea more appealing alternative (Gaultney, 1989). In recent years,different prototypes of soil compaction sensor systems aredeveloped for mapping certain predictors of soil compaction.Current soil compaction sensor systems are based on soilstrength sensors, fluid permeability sensors, water contentsensors, or their combinations (Fig. 2).

The objectives of this publication are to: (1) review recentlyreported concepts of soil compaction sensor systems, (2) dis-cuss the shortcomings of on-the-go sensing options using soilfailure mechanics, and (3) identify the priority for evolved sen-sors development.

2. Soil strength sensors

Soil strength, or mechanical resistance to failure, has beenwidely used to estimate the degree of soil compaction. Soilstrength sensors can be used for (a) mapping the general orlocalized compaction in a specified soil layer by measuringthe draft or vertical force of a reference tool and (b) sensingsoil strength profiles throughout an agricultural field whichtypically involves either tip-based or tine-based soil sensors.

By nature, soil strength sensors are of soil failure-type. Asthis type of sensor is moved through the soil, it registers resis-tance forces arising from cutting, breakage and displacementof soil, as well as the parasitic (frictional) forces that developat an interface between the sensor surface and surroundingsoil. In this case, a chisel (knife) of a tine-based sensor acts asa simple rigid tine, whereas a shank (leg) equipped with a hor-izontal sensing tip (tip-based sensor) acts as a rigid tine withleading tip.

As shown in Fig. 3, there are two major variables whichdefine the type of soil disturbance for a given tine: (i)depth/width ratio (d/w) and (ii) rake angle (˛) (Godwin, 2007).For a rigid vertical tine (˛ = 90◦) working at shallow depths(d/w > 1) the soil is displaced forward, sideways and upward(crescent failure), failing along well defined rupture planeswhich radiate from just above the tine tip to the surface atangles of approximately 45◦ to the horizontal (Fig. 4). Crescentfailure occurs at a certain depth called the critical depth, belowwhich soil is displaced forward and sideways only (lateral fail-ure). Crescent failure occurs when shearing resistance to theupward flow of soil is less than the resistance to the lateralflow at a given depth. Critical depth means that the two resis-tances are equal (Godwin and Spoor, 1977). For a rigid tine with

With advances in precision agriculture, spatial variationof soil compaction has been under focused investigation bymany researchers. It has been recognized that the recom-mended methods for direct measures of soil compaction

leading tip operated below the critical depth, the soil failurepattern near the surface is dependent upon the width and rakeangle of the shank (leg) rather than of the leading tip (Spoorand Godwin, 1978). For a very narrow tine (knife), as shown

c o m p u t e r s a n d e l e c t r o n i c s i n a g r i c u l t u r e 6 3 ( 2 0 0 8 ) 89–103 91

Fig. 1 – Principles of soil compaction measurement.

il compaction sensor systems.

idosacg

isVraufadra

Fig. 2 – Classification of so

n Fig. 4, transition from crescent to lateral failure occurs at/w > 6 (Godwin and O’Dogherty, 2007). In addition to the ratiof d/w, the critical depth increases with: (1) smaller ˛, (2) drieroil, (3) higher bulk density, (4) lower surface soil surcharge,nd (5) slower operating speeds (Smith et al., 1989). The criti-al depth depends on the soil type as well. Owen (1988) foundreater critical depth in clay soil than in sandy soil.

According to the concept of critical state in soil mechan-cs, the nature of soil failure is dependent upon the degree ofoil compressibility and the magnitude of confining stresses.ertical confining stresses increase with working depth, tineake angle and shear strength in the upper soil layers (Spoornd Fry, 1983). Stafford (1981) identified two modes of soil fail-re caused by a rigid tine: brittle and plastic flow (compressive)

ailure. Godwin and Spoor (1977) referred to these failure types
s crescent and lateral failure. The force predictive modelseveloped for the crescent-type failure are based on theo-ies of soil failure adjacent to a retaining wall. These modelsssumed that soil with rigid-plastic behavior fails according to Fig. 3 – Basic tillage tine geometry (Godwin, 2007).

92 c o m p u t e r s a n d e l e c t r o n i c s i n a g r i c u l t u r e 6 3 ( 2 0 0 8 ) 89–103

erns
Fig. 4 – Effect of tool depth/width ratio on patt
the quasi-static Mohr–Coulomb criterion and were based on afailure surface represented by a combination of a logarithmicspiral and a straight line (Hettiaratchi et al., 1966; Hettiaratchiand Reece, 1974). To estimate the forces for the part of tinewhich operates below the critical depth, the bearing-capacitytheory for deep foundations was employed (Godwin and Spoor,1977; Godwin and O’Dogherty, 2007). At a very slow speed(5 mm s−1), Stafford (1979) observed a clear difference in thenature of failure in front of a rigid tine between the wet anddry clay, whereas at a high speed (5 m s−1), the failure patternfor both wet and dry soils appeared to be a continuous flow ofmaterial. For intermediate moisture content and low speed ofoperation, failure in front of the 45◦ tine was brittle (same asfor a dry soil), whereas in front of the 90◦ tine it was plasticflow (same as for a wet soil). Therefore, he concluded that thetine rake angle affects the mode of failure as well.

2.1. Draft and vertical force sensors

Based on existing instrument technology, a family of sen-sor prototypes has been developed to measure overall draftand vertical forces. These prototypes were shown to be capa-ble of sensing physical soil state using bulk measures of soilmechanical impedance. The sensors have been operated ateither a constant depth bulk strength measuring sensors or achanging depth vertically actuated sensors.

2.1.1. Bulk soil strength sensorsMeasurement of moldboard plow draft has been suggested asa useful tool for continuous mapping of soil strength as a sur-rogate variable (Hayhoe et al., 2002; Lapen et al., 2002). Signalfiltering and spectrum analysis of the raw draft data using FastFourier Transform (FFT) provided an ability to better assessspatial soil behavior (e.g., local versus large scale variation)(Hayhoe et al., 2002). Thus, a high frequency oscillating loadusually resulted from the soil/tool interaction associated with
a particular mode of soil failure. Stafford (1981) determinedthat periodic loading on the tillage tool represented soil under-going brittle failure and that a lack of periodicity indicated flowfailure. Owen et al. (1990) stated that the transition from brit-
of soil failure (Godwin and O’Dogherty, 2007).

tle failure to flow failure could be interpreted to indicate thattool had surpassed the critical depth where soil fails laterallyas defined by Godwin and Spoor (1977). On the other hand,low frequency load changes indicated actual variation of criti-cal soil parameters, such as: soil moisture, soil texture, and/orcompaction (Owen et al., 1990; Hayhoe et al., 2002). However,Andrade-Sanchez et al. (2003) analyzed the tillage force dataof an instrumented tine using FFT and concluded that the fre-quency contents of the amplitude spectra depended on theconditions at which the test was conducted. Further analy-sis of the data revealed that the underlying phenomenon isnot deterministic chaos but pure Brownian motion. Regres-sion tree analysis by Lapen et al. (2002) indicated that draftvariability was best explained by location within a field, typeof crop, soil cone penetration resistance, and soil texture in theplow layer. The draft of a moldboard plow was found to gener-ally increase with the cone penetration resistance and soil claycontent. Lapen et al. (2002) suggested that draft data collectedduring normal field operation can be useful for producersinterested in identifying field areas where soil compactionmight limit the yield.

A method to improve determination of soil physical prop-erties using specific draft was proposed by van Bergeijk et al.(2001). In their study, information gathered automatically dur-ing plowing was used to predict spatial distribution of topsoilclay content. They stated that use of specific plow draft asa co-variable during the co-kriging process made it possibleto decrease the number of conventional topsoil clay contentmeasurements from 60 to 18 ha−1 with only a 20% increase inprediction error. In the same field, the spatial pattern of topsoilclay content was found to be similar to the yield map.

Another soil strength sensor was developed and tested bySirjacobs et al. (2002) and later was evaluated in more hetero-geneous field conditions by Hanquet et al. (2004). It consistedof a single chisel shank pulled through the soil at a con-stant depth of 30 cm with a constant speed of 5 km h−1. Soil
resistance forces were transferred to an octagonal ring trans-ducer fixed to the frame. The horizontal (draft) and verticalforce components as well as the moment were measuredand recorded. A significant correlation was found between

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c o m p u t e r s a n d e l e c t r o n i c s i n

he measured draft and average resistance to cone penetra-ion at 25 cm depth (r = 0.95) and soil moisture at 30-cm depthr = −0.95). They also concluded that the sensing method pro-osed proved its capability to reveal soil physical variationithin a field.

Earlier, spatial variation of draft force in a field wasmployed to differentiate among soil types. In research con-ucted by van Bergeijk and Goense (1996), specific plowingraft maps were used to locate different types of soil withinn agricultural field.

As mentioned above, such tillage force maps have beenompared with yield maps. For example, Nemenyi et al. (2006)eveloped a tillage force monitoring system using a singlehank subsoiler as a strength sensor and found the patternsf the tillage force and yield maps of maize to be very sim-

lar. They concluded that tillage force or, more specifically,actors causing high tillage force, can be confounded within

set of management zones where compaction-related yieldeduction can take place. However, the investigators found noorrelation of draft with selected soil properties usually usedo assess the degree of soil compaction.

In a different study, Mouazen and Roman (2006) could notbserve any clear correlation between measured draft and soilry bulk density or soil moisture. They suspected that draftas not a proper measure to indicate soil compaction while

gnoring other influencing factors, such as: soil type, moisture,nd working depth. Hall and Raper (2005) also stated that draftlone is not a good indicator of soil conditions, because differ-nt soils may have the same mean draft, but present differenthysical conditions (Gill and Vanden Berg, 1968; Smith et al.,994).

.1.2. Vertically actuated sensorsn addition to the integrated (bulk) measure of draft, someools working as narrow and very narrow tines have been usedo assess vertical variation in soils. A general goal of suchttempts was to scan for a hardpan layer by moving the tool upnd down while moving across a field. For instance, Staffordnd Hendrick (1988) compared two methods for detecting theepth of soil hardpan in soil bin tests using different soil typesnd conditions. They reported that sensing forces on the tip ofsubsoiler (acted as a narrow tine) failed to identify the pres-

nce of a pan. However, both horizontal and vertical forceseasured with a small backward raked slitter blade (acting

s a very narrow tine), mounted behind a subsoiler tine androjected down into undisturbed soil, were sensitive to soiltrength variations with depth and therefore to the positionf a pan. Manor and Clark (2001) designed an instrumentedubsoiler to determine the strength and depth of soil hardpany measuring vertical force on the subsoiler tip and the tipepth. In the preliminary field tests, they observed that whenhe shank tip was above a soil hardpan, the soil force on theip acted upward, and became downward when the shank tipas below the hardpan.

The vertical impedance force applied to a very narrow tinedisc coulter) was also used as an indicator of soil compact-
ess. A soil impedance sensor based on an 81-cm disc coulteras developed and tested by Pitla and Wells (2006). Using aydraulic actuator, the coulter was oscillated between depthsf 10 and 33 cm as it moved forward. The vertical impedance
r i c u l t u r e 6 3 ( 2 0 0 8 ) 89–103 93

force along with operation depth was recorded continuously.The average cone index (CI) between depths of 10 and 33 cmwas compared to the average coulter index (Cul; N mm−1),defined as the penetration force divided by the perimeter ofthe segment of coulter disc in contact with soil (R2 = 0.51). Themaximum average CI in a 0.4-ha square grid occurred at adepth of 15.2 cm, whereas the maximum average Cul occurredat a depth of 10.2 cm. It was found that CI could be predictedfrom the coulter index (Cul) using an empirical linear equa-tion. However, for the regression line reported Cul = 0 N mm−1

resulted in CI = 3 MPa, which meant that the equation wasvalid only for the range of measurements obtained.

2.2. Soil profile sensors

To define the extent of the general compaction or to detect thedepth of locally compacted layers (plow pan or hardpan), soilstrength profile sensors have been developed. These sensorsshould be capable of accurately mapping both spatial and ver-tical variation in soil mechanical resistance. Current prototypesystems include either tip-based or tine-based sensors.

2.2.1. Tip-based sensorsSoil penetrability is a measure of the effort required to force anobject through the soil media. Penetration resistance of soil isrelatively easy to measure and it can be related to soil strength,which affects trafficability, resistance to seedling emergenceand root development, and soil compaction. Generally, pene-tration resistance depends on soil bulk density, water contentand potential, texture, aggregation, cementation and miner-alogy (Vaz and Hopmans, 2001). A recently introduced modelfor penetration resistance of soil contains two main addi-tive terms: one represents the degree of compactness of thesoil, whereas, the other represents the effect of water (Dexteret al., 2007). Theoretically the mechanism of penetrometerswas analyzed by several researchers (e.g., Bengough et al.,2001). They indicated that penetration resistance is governedby several basic properties, including: soil shear strength, com-pressibility, and soil/metal friction.

Tip-based penetrometers (sensors designed to measuresoil penetration resistance) include: (1) standardized verti-cally operating cone penetrometer (ASAE, 2004), (2) single-tiphorizontal soil impedance sensor (Alihamsyah et al., 1990),(3) multiple-tip horizontal soil impedance sensor (Chung andSudduth, 2003a,b, 2006; Chung et al., 2003, 2004a,b, 2005, 2006;Chukwu and Bowers, 2005), and (4) vertically oscillating shankwith horizontal single-wedge sensor (Hall and Raper, 2005).While the vertically operated sensor presents the conven-tional means for measuring soil strength profile, horizontallyoperated sensors have been deployed for on-the-go mapping.

Several different studies (Farrell and Greacen, 1965; Rohaniand Baladi, 1981; Yu and Mitchel, 1998; Tekeste et al., 2007)have addressed soil behavior while being tested using verticalcone penetrometers. These studies were based on: (1) bearingcapacity theory, (2) cavity expansion theory, (3) steady statedeformation, (4) finite element analysis, and (5) laboratory
experimental methods.
Using the bearing capacity theory, a certain shape of soilfailure surface was assumed to solve the limit equilibrium offorces over the soil–tool system. Chung and Sudduth (2006)

i n a
94 c o m p u t e r s a n d e l e c t r o n i c s
developed an analytical model to estimate the force requiredto penetrate (cut and displace) soil with a cone penetrometermoving vertically using the bearing capacity theory of foun-dations and the concept of a variable failure boundary. Theyalso devised an analytical model for a prismatic cutter trav-eling horizontally assuming the same failure mode. However,the mode of soil failure for a horizontally operating penetrom-eter depends on the position of the sensing tip relative to thecritical depth. Therefore, the assumed bearing capacity-typefailure model is valid as long as the prismatic tip is operatedbelow the critical depth for the tine carrying the tip. Otherwise,the soil failure mode is a crescent-type failure and the sens-ing tip would not sense the same soil strength as the verticallyoperated cone penetrometer. Actually, their model was a com-bination of three previous models (Terzaghi, 1943; Meyerhof,1951; Hu, 1965) and was expressed as an additive function ofsoil weight, cohesion, adhesion, and operating speed. For thehorizontally operating device, the cohesive component wasdominant, whereas for the vertically operating cone, the grav-itational component was equally important. They used thedeveloped model to optimize design parameters of the sensorwith multiple horizontal prismatic tips.

On the other hand, Tekeste et al. (2007) stated that theanalytical approaches may not be ideal for explaining thedynamics of soil during vertical cone penetration, especiallyin layered and heterogeneous conditions. They pointed outthe difficulties associated with pre-defining the shape of thesoil failure zone prior to the force equilibrium analysis. There-fore, they developed an axisymmetric finite element model tosimulate cone penetration for the prediction of the hardpanlocation in a layered Norfolk sandy-loam soil. The simula-tion showed that the size of plastic deformation zone variedaccording to the strength of the soil layers. Zones observedabove the hardpan were larger than those within the hard-pan layer. The plastic deformation that extended from thecone might suggest that the cone penetration resistance wasa measure of soil reaction within the zone of influence, whichwas about 3 times the diameter of the cone. In another study,Garciano et al. (2005) measured the failure zone (zone of influ-ence) around a vertically operating cone penetrometer usinga pressure-sensing mat under laboratory conditions. Theyreported that the failure zone of a 12.83-mm diameter conepenetrometer had the radius of about 76.2 mm from the cen-ter of the cone penetrometer shaft. The difference between thepredicted (Tekeste et al., 2007) and the measured (Garciano etal., 2005) zone of influence may be due to the differences insoil textures and methodologies.

Because of the relatively small zone of influence, soilmechanical resistance to tip penetration represents a localmeasure of soil strength. Soil strength profile can be obtainedif the vertically operated penetrometer registers measure-ments at different depths. Spatial variation of soil penetrationresistance can be addressed using multiple point measure-ments or when operating the penetrating tip horizontally.

2.2.1.1. Vertically operating cone penetrometers. Cone pen-
etrometry has been traditionally used to assess the soilstrength within a soil profile (ASAE, 1999, 2004). The simplestpenetrometer is a hand-held device that is pushed downwardat a constant rate at a given point on the surface. The cone
g r i c u l t u r e 6 3 ( 2 0 0 8 ) 89–103

penetrometer consists of a rod (shaft) with a 30◦ cone-shapedtip and a load-measuring device. It registers the force requiredto insert the cone tip into the soil. Cone index is calculated bydividing the insertion force by the area of the cone base andis expressed in units of stress or pressure. Cone index is anempirical measure of soil state and represents the net effectof several soil properties.

Although standardized, cone penetrometer measurementshave limited applicability. A cone penetrometer should beoperated at a constant insertion speed, which can be diffi-cult to achieve manually. Also, the measurement is made ata single discrete point. To account for small-scale spatial het-erogeneity, multiple cone penetrometer measurements havebeen recommended (ASAE, 1999). Therefore, use of the conepenetrometer method has been viewed as a time-consumingprocess, especially for mapping an entire agricultural field.

To automate cone penetrometry, Raper et al. (1999)developed a multiple-probe system which consisted of fiveindependent probes in line and was capable of spanningacross a typical crop row. This unit was mounted on athree-point hitch of an agricultural tractor. Similar prototypesystems have been deployed to gather spatial data related tothe variation of soil penetration resistance across the field.

Gorucu et al. (2006) developed an algorithm to determinethe optimum tillage depth using a series of cone penetrom-eter profiles. They were able to assess the thickness and thedepth of the hardpan layer for different profiles and use theinformation extracted to define proper tillage depth based ona set of defined rules.

However, even an automated stop-and-go approach doesnot achieve the sufficient measurement density necessary formapping large-size fields (Hall and Raper, 2005). Tekeste et al.(2006) stated that the success of site-specific tillage dependson accurate soil compaction sensing addressed through detec-tion of the magnitude and depth of a compacted layer(hardpan). For the Pacolet sandy-loam soil of the Southeast-ern U.S., they recommended cone penetrometry based on a20 m × 20 m grid. In a different study, Domsch et al. (2006)suggested a sampling interval of 10 m to determine the soilloosening depth necessary to eliminate zones with high soilstrength on a sandy deposits overlaying boulder clay. There-fore, at least a 10 m × 10 m square grid approach appears to beadequate when it comes to mapping.

2.2.1.2. Single-tip horizontal soil impedance sensors. Based onthe lateral earth pressure theory, there is a relationshipbetween horizontal and vertical soil stresses. The initialstress state in soils is characterized by the coefficient ofearth pressure at rest, which has been accepted as thehorizontal-to-vertical stress ratio. The extreme values of thehorizontal-to-vertical stress ratio are referred to as active andpassive earth pressure coefficients representing limit (yield-ing) soil states (Michalowski, 2005). Therefore, an existingrelationship between soil mechanical impedance measuredusing vertical and horizontal (lateral-type failure) cone pen-etrometers can be expected.

A horizontal cone penetrometer was developed and testedby Alihamsyah et al. (1990) with the objective of providinga continuous signal for automatic control of soil interact-ing implements (Alihamsyah and Humphries, 1991). However,

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ith the introduction of the Global Positioning System (GPS)o agriculture, mapping soil mechanical impedance measuredn-the-go has become feasible. Cone- and prismatic-shapedenetrometer tips were mounted by Alihamsyah et al. (1990)n specially designed shanks and coupled with load cells mea-uring penetration resistance forces. A field evaluation withwo rates of horizontal penetration, three soil types and two

oisture contents revealed that the penetration resistancesecorded using the horizontal penetrometer were correlated tohose obtained using a vertical cone penetrometer. They alsotated that a prismatic, 30◦ apex tip provided an indicationf soil impedance with less variation among nearby measure-ents than a conical tip. The supporting argument for the

cceptable readings of the prismatic-tip penetrometer wasxplained by Alihamsyah et al. (1990) as follows. The prismaticip was loaded by the soil from its sides while the cone tip wasoaded radially from all directions. The apex of the prismaticip penetrometer coincided with the shank and experiencededuced soil resistance as compared to the cone tip penetrom-ter, which protruded forward approximately 28 mm from thehank. For the cone tip, soil was displaced radially whichncreased soil compaction ahead of the advancing cone tip.onversely, the apex of the prismatic tip caused soil displace-ent only in the directions of its sides, which decreased soil

ompaction ahead of the advancing tip. However, the effects ofize and position of the tips were not addressed in this study.

.2.1.3. Multiple-tip horizontal soil impedance sensors. Otheresearchers (Chung and Sudduth, 2003a,b, 2006; Chung et al.,003, 2004a,b, 2005, 2006; Chukwu and Bowers, 2005) focusedn measuring soil compaction occurring at different depthsimultaneously. They extended the idea of a horizontal pen-trometer to multiple-tip sensors to differentiate the degree ofoil compactness at discrete depths with the intent of deter-ining the depth of a hardpan. A soil strength profile sensor

SSPS) was designed and tested by Chung et al. (2006). It usedultiple prismatic tips with an apex angle of 60◦ and base

rea of 361 mm2 (19 mm × 19 mm) mounted on a shank (verti-al tine) with a width of 25.4 mm and cutting (wedge) angle of0◦. This on-the-go SSPS was designed and fabricated using anrray of load cells interfaced with corresponding soil cuttingips. The tips were extended forward from the leading edgef the tine and spaced apart. Different tip extension and tippacing distances were tested; a 5.1-cm extension and a 10-m vertical spacing were selected to minimize interferencerom the main blade and adjacent sensing tips.

For the field data, a linear relationship (0.6 slope of lin-ar regression) between soil strength measurements obtainedsing PSSI and a cone penetrometer was found for the depthf 30 cm, but not for the depth of 10 cm. The lack of statisticalignificance in the 10 cm depth was attributed by the authorso the relatively low spatial variation of soil strength at thatepth. However, this could also be explained by different fail-re modes. In the top 10 cm, soil was above the critical depth

or the 25.4-mm wide shank (15.2 cm), which corresponded tohe crescent failure mode. The soil ahead of the cone tip of
he penetrometer was always in the bearing-capacity failure
ode.When the depth of a soil strength sensor is such that it acts

s a very narrow tine, soil above the critical depth is loosened

r i c u l t u r e 6 3 ( 2 0 0 8 ) 89–103 95

and displaced in a forward and upward fashion. Therefore,a sensing tip placed at such a depth is moved through dis-turbed soil with little resistance, which comes mainly fromfriction. However, the same sensing tip operated below thecritical depth pushes soil sideways and forward, similar towhat a cone does during its vertical soil penetration.

Soil bin tests on the sensor and the cone penetrometershowed differences between CI and PSSI profiles. The CI pro-file was nonlinear, whereas the PSSI profile increased linearlyas a function of depth (Chung et al., 2004a). At an operatingspeed of 0.5 m s−1, the linear regression of CI as a function ofPSSI was not significant for the 10-cm depth, and for the othertwo depths, 20 and 30 cm, was statistically significant only atP = 0.1. As the speed increased to 1.5 and 2.5 m s−1, linear rela-tionships for all depths were significant. These results couldbe clarified by the fact that at a speed of 0.5 m s−1, the sensingtip at the 10-cm depth was working above the critical depthwithin a crescent failure region, while at the other two oper-ating speeds all the sensing tips were below the critical depth,which decreased at higher speeds.

Chukwu and Bowers (2005) modified the horizontally oper-ating single-tip penetrometer developed by Alihamsyah et al.(1990) so that it could measure soil mechanical resistance atthree depths simultaneously. They used three prismatic tips,with a 30◦ apex angle and 323 mm2 base area, and three loadcells similar to the one used in the single tip sensor. The pris-matic tip bases were extended 40 mm ahead of the shank witha 30◦ apex angle, but the width of the shank was not provided.A 10.2-cm vertical spacing was chosen to minimize measure-ment interference from one tip to the next. Soil mechanicalimpedance measurements were made in a soil bin at threesimultaneous depths of 178, 278, and 381 mm. When operatedat a speed of 30 mm s−1 through soil with artificially createdvertical variations in soil compactness, the sensor detectedthe differences in soil mechanical impedance with depth at a5% significance level. A linear regression was used to comparethe soil mechanical impedances measured by the on-the-gosensor and corresponding cone index values obtained usinga standard vertically operated cone penetrometer (R2 = 0.76).The relatively high correlation could be explained by the factthat all three of the tips were working below the critical depthof the soil strength sensor. Therefore, both instruments (verti-cal and horizontal penetrometers) operated at the same speed(30 mm s−1) had a bearing capacity-type failure mode.

2.2.1.4. Vertically oscillating single-tip horizontal soilimpedance sensor. Hall and Raper (2005) argued that thelimitation of the single-tip horizontal soil impedance sensorswas that measurements were taken only at a fixed depth. Thedevelopment of the multiple-tip horizontal soil impedancesensor was one step toward being able to sense the entire soilstrength profile. However, relatively expensive multiple-tipsensors could provide erroneous data when they happen tobe between adjacent measuring tips. Therefore, a perfectedsystem should allow scanning the soil profile continuously,like a vertical cone penetrometer (Raper et al., 2005). As a
result, Raper and Hall (2003) developed a new design thatallows sensing the entire soil mechanical resistance profileon-the-go by vertically oscillating a horizontal single-tipsensor as it moved forward through the soil.

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The on-the-go soil strength sensor (OSSS) developed hadone measurement tip mounted onto the leading edge of ashank, which moved up and down using a reciprocating drive.A 30◦ prismatic sensing tip was used and a “wedge index” (WI)was defined as the measured force divided by the base area ofthe tip. The shank was 37.5 mm wide with a 30◦ beveled angle.

First, they evaluated the sensor in a soil bin using a seriesof steady-state depth settings (100, 175, 250, and 325 mm) anda 625 mm2 (25 mm × 25 mm) tip (ST2) extended 30 mm in frontof the shank. At the 100-mm depth, it was found that the WIwas approximately 50% less than the corresponding CI. It wasalso observed that at shallow operating depths, the soil flowacross the wedge was not completely lateral. Some of the soilwas lifted up (soil upheaval). The researchers suspected thatthere could be a shallow transition zone where OSSS was notcapable of collecting valid soil strength data.

To resolve the small force measuring limitation at shal-low depths, the size of the sensing tip was increased to2500 mm2 (50 mm × 50 mm) (ST3) and the OSSS was tested atthe same steady-state depth settings again. In results, WI val-ues obtained using ST3 were found to be lower than using ST2.This reduction was contributed to the increased tip size. Thelarger tip was also used for the dynamic testing of the OSSSwhen it was actuated vertically at a rate of 0.1 m s−1 whilemoved forward at 0.45 m s−1.

As with ST2 tip, Hall and Raper (2005) also reported thatthe OSSS with ST3 was ineffective in acquiring accurate soilstrength data at depths less than 150 mm, however, belowthat depth the shapes of the soil strength profiles obtainedusing the OSSS cone penetrometer were similar. In theory,the OSSS operated at a shallow depth could be considered asa narrow tine with a leading tip. At a fixed 100-mm depth,the 25-mm wide tip was clearly operating in the crescent fail-ure zone since the critical depth was approximately 150 mm(6 × 25 = 150 mm). When the 50-mm wide ST3 was used, thecritical depth was around 225 mm with the potential reductiondue to the beveling of the frontal area of the shank. Therefore,the non-consistency between WI and CI values in the first 100and 150 mm of depths for the ST2 and ST3 sensing tips, respec-tively, could be attributed to different failure modes. The largerwidth of the sensing tip made the difference between soil fail-ure in front of the vertical and horizontal measurements moredistinct.

When comparing WI and CI for ST2, CI was 1.52 timesgreater than WI with R2 = 0.97. For ST3, the slope of regres-sion increased to 2.99 (R2 = 0.98). Also, it was found that OSSSmeasurements were more closely correlated to bulk densityrather than CI. Although it was concluded that a universalequation relating CI and WI might not exist, it appeared thatfor the identical shape of both penetrometers, the WI/CI-likeratio could represent the apparent coefficient of passive earth pres-sure for given soil conditions. This ratio would be maintainedas long as the soil failure mode for sensors operated verticallyand horizontally would be of a lateral type.

2.2.2. Tine-based sensors
In addition to multiple-tip soil impedance sensors, severalattempts have been made to use tine-based sensors to con-duct continuous measurements of the entire profile. Thereare two approaches for these sensors: (1) using an array of
g r i c u l t u r e 6 3 ( 2 0 0 8 ) 89–103

strain gauges mounted on a rigid tine (Glancey et al., 1989;Adamchuk et al., 2001a,b) and (2) multiple active cutting edgessupported by independent load cells (Andrade et al., 2001,2002, 2004; Khalilian et al., 2002).

As with previous sensors, soil strength measured using atine-based sensor and a standard cone penetrometer shouldhave the same nature of soil failure in front of the sensor.Therefore, emphasizing measurements provided by the tine-based sensor below its critical depth could be recommended.

While designing a tine-based sensor it is also necessaryto address the downward insertion of the sensor prior to themeasurements. For example, Hall and Raper (2005) cut the bot-tom of the shank to a 45◦ angle and beveled it to a 30◦ angle sothat 600-mm deep measurements could be made. To preventthe formation of the soil wedge in front of the advancing tineand to obtain consistent force values, the leading edge of thetine should also be beveled (Gill and Vanden Berg, 1968; Halland Raper, 2005).

2.2.2.1. Cantilever beam sensors. It is assumed that since thebending stresses in a cantilevered tool are proportional to thesoil forces acting on the tool, strain gauges located at discretepoints along a tine can be used to obtain measurements of themoments acting on the tine (Glancey et al., 1989). At each ver-tical position, the bending stress depends on the distributionof forces below that position. For example, an instrumentedchisel equipped with a wedge-shaped cutting edge was devel-oped by Glancey et al. (1989) using an array of strain gaugesattached to the chisel shank. Although the tool developed andused by these researchers estimated the force profile, therewere some concerns related to the accuracy of the resistanceforce measurement in the top part of the soil profile near thesoil surface. Sensor measurements were compared with: bulkdensity, water content, and cone index profiles to a 305-mmdepth. Force distribution over the tillage depth was linear ata shallow operating depth (153 mm) in both tilled (plowed)and untilled soils, while the distribution was nonlinear at agreater depth (305 mm) in untilled soil. However, at the higheroperating speed (3.2 km h−1), the predicted force distributionshowed discontinuity (as the authors reported) at a depth cor-responding to the prior tillage depth, whereas at the lowerspeed (0.8 km h−1) this behavior was not observed. During thisexperiment, the chisel acted as a very narrow tine and thedepth at which the sudden change of distribution occurredcould be considered as the depth of the change in soil failuremode (from crescent to compressive failure). As the operat-ing speed increased, soil particles could be mobilized andpushed together, which caused an increase in the predictedforce distribution below this critical depth. At a slow speedthe soil particle mobilization might not occur (assuming thatthe depth of tillage was the same as the operating depth of thesensor).

Similarly, another system with an array of strain gaugesattached to the backside of a vertical rigid tine was developedand tested by Adamchuk et al. (2001a). The system was capa-ble of estimating soil mechanical resistance at three depth
intervals. It was reported that a relatively low signal to noiseratio made it difficult to predict soil mechanical resistancenear the soil surface. Considering the frontal width of thetines (18.6 and 15.9 mm) and the working depths of the above-

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operating above the critical depth (in the crescent-type fail-


entioned two sensors, the sensors acted as very narrow tinesnd the soil near the surface in both cases was in crescentailure. Therefore, the low signal to noise ratio was due to theact that the top part of the sensors was moving in the dis-urbed soil with very low resistance imposed on the gaugess well as due to the short torque arm. In addition, any errorade while assessing deep soil mechanical resistance would

e amplified while being accounted for during calculation ofhe topsoil resistance. Another prototype of the vertical rigidine equipped with an array of strain gauges was used both tostimate a spatial pattern of soil resistance and to identify therend of soil resistance change with depth, assuming a linearhange of resistance pressure with depth (Adamchuk et al.,001b).

In another study, the soil mechanical resistance profilesstimated using an instrumented deep-tillage implementere significantly lower than those generated using cone pen-

trometer measurements (Adamchuk et al., 2004a,b). Theysed a commercial straight standard subsoiler to house the

nstrument. The subsoiler consisted of a 51-mm wide shanknd a triangular custom point with 6.6-cm base length. Theperating depth of the system was in the range of 35–50 cm.t appears that the system was working above the criticalepth for the first depth range with a crescent-type soil fail-re, whereas the cone penetrometer had a bearing capacityoil failure type. The resistance given by the soil in forwardnd sideways movement, as experienced by a cone penetrom-ter, was significantly higher than that with the soil movingorward and upward, as experienced by the deep-tillage imple-

ent working above its critical depth (Spoor and Godwin,978). Therefore, the differences in the soil strength profilesgain can be explained by the different soil failure modes, andot by the nature of both instruments (vertical penetrationersus horizontal tillage) as stated by the authors.

Another instrumented knife used as a soil profile sensoras developed by Christenson et al. (2004) for mapping soilechanical resistance modeled as a second order polyno-ial profile. The system consisted of a cutting edge which

ransferred the load from soil cutting to the shank instru-ented with an array of strain gauges. Force was transferred

etween the cutting edge and the shank at three locations.n the next stage, Adamchuk and Christenson (2005) devel-ped a prototype integrated soil physical properties mappingystem (ISPPMS) and tested it in a set of long-term tillage com-arison plots. The system, which included mechanical (soiltrength), dielectrical (capacitance) and optical (reflectance)ensors, was developed and tested. The output of the soiltrength profile sensor was compared with the cone indexeasured with a tractor-mounted 3.23-cm2 cone penetrome-

er. The results of the comparisons showed that the coefficientf determination (R2) for linear correlation between the inte-rated load of upper and lower parts of the sensor and theverage cone index profile had values of 0.24 and 0.55. The loworrelation between the integrated load of the upper part andhe cone index could be attributed to the different soil failureones in front of the sensor and ahead of the cone penetrom-
ter, while the failure mode for the lower part was similar tohat of the penetrometer.
A multiple tine soil mechanical resistance mapping sys-em (SMRMS) was developed and tested by Siefken et al. (2005)

r i c u l t u r e 6 3 ( 2 0 0 8 ) 89–103 97

using three independent sensing tines (shallow, 10 cm; inter-mediate, 20 cm; and deep, 30 cm). The frontal edge of eachtine was equipped with a 19.1-mm wide cutting edge with a45◦ bevel. The field evaluation showed that depth significantlyaffected the relationship between corresponding soil mechan-ical resistance measurements obtained using the multiple tineSMRMS and a cone penetrometer. Comparison of the measure-ments obtained using the multiple tine SMRMS and a conepenetrometer for each tine showed that the regression linemoved closer to 1:1 line in the order of deeper to intermedi-ate to shallow working tine. The slope of the regression linesbetween CI and SMRMS measurements was 1.97, 1.32, and 0.93for shallow, intermediate, and deep working tines. It seemsthe modes of failure for the shallow and deep working tinesof the multiple tine SMRMS were crescent and lateral failuretypes. When the measurements obtained using the multipletine SMRMS were corrected for depth, an acceptable correla-tion of R2 = 0.76 was achieved.

Adamchuk et al. (2006) compared data obtained with twoon-the-go soil mechanical resistance sensors including a ver-tical tine with a strain gauge array above soil surface (as a partof ISPPMS) and a vertical tine equipped with five prismatichorizontal sensing tips providing resistance data at discretedepths (SSPS described earlier). Data obtained with both sen-sors were compared to cone penetrometer measurements (CI).It was reported that the 10-cm depth SSPS data were not cor-related with the corresponding CI and the ISPPMS estimateseven had a negative correlation with the CI in the first 10-cmsoil layer. The width of the vertical tines used in the ISPPMSand SSPS was 19.05 and 25.4 mm. Therefore, the first part ofthe working depth of both the ISPPMS and SSPS systems had acrescent failure mode in addition to the measurement disrup-tions caused by the heavy crop residue present on the surfaceof the field, as reported by the authors.

2.2.2.2. Direct load sensors. Similar to the multiple-tip sen-sors, direct load sensors use load cells installed inside ashank to measure soil resistance forces applied to an arrayof independent cutting edges. Andrade et al. (2001) developeda soil cutting-force profile sensor (UCD-CPS) that could takemeasurements up to a 63-cm depth on a 7.5-cm increment(5-cm active cutting elements separated by 2.5-cm dummy ele-ments). This device consisted of eight cutting edges supportedby independent load cells. The soil cutting forces were influ-enced by soil water content, depth of operation of the tine,and location of the cutting edge within the soil profile. Exten-sive field tests showed that the effect of the operating speedwas not significant between 0.65 and 1.25 m s−1 (Andrade etal., 2002). Chung et al. (2006) stated that one potential issuewith this sensor design was the possibility that interactionsbetween the adjacent cutting edges and between the mainshank and cutting edges would affect soil strength measure-ments.

In the first version of the UCD-CPS, a backward rakedshank with a frontal width of 51 mm was employed. Based onsoil-tine failure mechanics, the first two cutting edges were

ure zone) and could transfer to the load cells relatively lowresistance forces. The way the cutting force changed with thedepth (Andrade et al., 2001) and the effect of the soil rise ahead

i n a
of the sensor (Andrade et al., 2002) support this statement. Inaddition, Andrade et al. (2004) developed a more compact andless expensive sensor that could sense soil strength profilesto a depth of 46 cm. The improved version of the UCD-CPShad a shank width of only 27 mm with a 90◦ rake angle. Theinstrumentation in the top 8 cm of the shank was removed,which resulted in an effective sensing depth ranging from7.5 to 45.7 cm. It was stated that analysis of the data fromthe first layer showed little significance in the case of theoriginal version of the UCD-CPS. They concluded that theimproved UCD-CPS could detect differences in the compactionstate of the soil profile reasonably well. The correlation coeffi-cient (r) between the UCD-CPS output and the cone index forthe average subsoil profiles was in a range between 0.44 and0.70. However, when the operating depth and its interactionwith CI were considered in the regression equation the mul-tiple coefficients of determination (R2) improved significantly(Andrade-Sanchez et al., 2007).

Khalilian et al. (2002) developed another tine-based sen-sor with five independent cutting edge section supported byload cells. They also indicated >75% (>90% below 22.5 cm) cor-relation between measurements produced using the systemdeveloped and a cone penetrometer.

In another study, Verschoore et al. (2003) developed andtested a horizontal soil compaction profile sensor, which wascalled a “wing penetrometer”, using six 50-mm long wingswhich resulted in a total measuring depth of 30 cm. Thewings were mounted on the frontal part of a vertical tinewith a wedge angle of 30◦ and equipped with strain gaugesto measure the bending moment induced on the wings. Itwas reported that only the measurement for the upper layercould be influenced by the vertical movement of the soil. Acorrelation (R2 = 0.41) between a cone penetrometer and thehorizontal sensor output was achieved.

Sharifi et al. (2007) further explored the idea of using mul-tiple wings to estimate soil mechanical resistance at eightdepths. The sensor consisted of a series of instrumented flaps.Each flap was designed as a sensing element comprising one-half of a pointed leading edge mounted to the leg of the tine.Sets of strain gauges were placed on the rear faces of theflaps. A series of soil bin tests revealed that differences in soilstrength at given depths caused by different surface-appliedloads and tire inflation pressure could be detected using thesensor developed. However, the flap located right below thesurface had a negligibly low force measurement. Based on thefield evaluation of the developed sensor, they recommendedmounting the array of flaps at depths greater than 200 mmonly, or simply place a single flap at a depth between 300and 400 mm. This would allow mapping compaction belowthe depth of primary tillage. However, no data on correla-tion between the output of the sensor and cone penetrometermeasurements were provided.

3. Fluid permeability sensors

To assess the effect of soil compaction limiting root growth,additional soil physical properties should be considered(Mosaddeghi et al., 2007). Normal and shear stresses couldextensively affect soil pore size distribution, hydraulic con-

g r i c u l t u r e 6 3 ( 2 0 0 8 ) 89–103

ductivity, and air permeability at constant pore volumes (Horn,2002). Mosaddeghi et al. (2007) suggested that we should notlimit ourselves to strain-related properties as the dependentvariable for the determination of soil pre-compaction stress(compaction strength), but should also consider further soilquality attributes.

These soil quality attributes can be called fluid permeabil-ity and are related to the soil structure and interconnectedpore spaces. Laboratory- or field-based measurements of fluidpermeability often use water as the fluid that is propagatedthrough the bulk soil. A low rate of water movement throughthe soil has been used to show the presence of surface com-paction (surface crusts) created by surface irrigation (Sakai etal., 1992), general and localized compaction (plow pan) dueto surface traffic and plowing in wet conditions. In a recentstudy by Hemmat et al. (2007), the effect of using differentplow shares on plow pan formation was shown by measuringthe water infiltration into the soil of the furrow bottom.

Besides water, the use of air as a soil propagating fluid couldminimize fluid–soil interactions and may provide a more con-sistent solution adoptable for on-the-go mapping. Therefore,mapping soil compaction was attempted by measuring thepressure required to inject a constant flow of air into the soilas an indication of the relative soil pore space and the conti-nuity of the pores (Clement and Stombaugh, 2000). The air wasforced into the soil at a depth of 30 cm using a subsoiler shank.The soil above the point of subsoiler was disturbed; thus, themeasured pressure resistance could be a measure of the airpermeability of the subsoil as long as the air flow rate is keptconstant. The flow rate of an orifice depends upon the orificesize as well as the pressure drop across it. Therefore, if a fixedorifice is used, the flow rate would change with the changeof soil resistance. It was stated that the sensor was capableof detecting changes in soil structure/compaction, moisturecontent, and soil type. Cone penetration resistance was alsomeasured. It was speculated that the wetter soils would have alower cone index, and, therefore, a higher resistance pressure.This could also be explained by the fact that the air-filled poreswould be decreased as the soil moisture content increased.During preliminary field tests, the system was able to differ-entiate between several tillage treatments. Later, Koostra andStombaugh (2003) redesigned the first version of the air per-meability sensor to minimize the soil disturbance induced bythe wide point of its shank. However, no data on the field per-formance of the sensor in soils with different degrees of soilcompactness were provided.

4. Water content sensors

Hydrodynamic water content variation was proposed to eval-uate the effect of compaction on soil structure (Alaoui andHelbling, 2006). The method was based on soil water contentmeasurements via time domain reflectrometry (TDR). Usingthis method, the authors could differentiate the effect of com-paction on soil structure caused by load traffic and intensive
stock trample.
Among the soil parameters that affect CI, soil water con-tent and bulk density are the most significant (Ayers andPerumpral, 1982). Stitt et al. (1982), for example, conducted a

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omprehensive study of factors affecting CI in coarse-texturedoils in the Atlantic Coastal Plain, and used a stepwiseegression method to relate mechanical impedance to various

easured soil properties. The highest correlation coefficientsere found for a regression model that included soil water

ontent, soil particle roughness, and bulk density. Shaw et al.1942) concluded that soil moisture was the dominant factornfluencing the force required to push a penetrometer into theoil, as CI values increased at lower moisture contents. In anxperimental study by Henderson et al. (1988), it was foundhat the CI was slightly affected with a decrease of soil waterontent to ∼70% of field capacity. However, the CI increasedxponentially with a further reduction of the water contentn a sandy soil. Therefore, because soil mechanical resistancetrongly depends on moisture content, it is beneficial to simul-aneously measure soil water content and soil mechanicalesistance. Therefore, several soil moisture sensors have beenntegrated into vertically operating cone penetrometers andorizontal soil impedance measuring systems.

.1. Integrated tip penetrating sensors

ver the past decade, several types of moisture compen-ated vertical penetrometers have been developed. The firstpproach was to use the popular TDR sensors (Young et al.,001; Vaz and Hopmans, 2001; Vaz et al., 2001). The secondpproach was to insert a NIR (near-infrared) reflectance sensornto the rod of the cone penetrometer (Newman and Hummel,999; Hummel et al., 2004). In addition, dielectric (capacitance)ensors were combined with the rod (Singh et al., 1997) or theone (Schulze Lammers and Sun, 2004) of cone penetrometers.

.2. On-the-go water content sensors

tafford (1988) identified two types of sensing systems thatan be used to estimate real-time soil water content fromobile instruments: contact and non-contact. A contact sen-

or physically disturbs soil as the sensing element moves ands mostly suitable for use in cultivated soil. In contrast, a non-ontact sensor does not disturb soil surface so that it could besed even when the root system of the plant was established.urrently, very few prototypes have been developed to senseoisture on-the-go.Whalley et al. (1992) developed a capacitance sensor used

o measure soil water content dynamically as a tractor drovehrough the field. This sensor was found to be sensitiveo fluctuations in the soil bulk density as well. Lui et al.1996) also evaluated a dielectric-based moisture sensor underynamic conditions by incorporating it into a nylon blockhat was attached to an instrumented tine. It was reportedhat this sensor had the advantage of low cost and very fastesponse. However, additional tests conducted by Andradet al. (2001) on a commercially available low-resonant fre-uency dielectric sensor indicated that this type of waterontent sensor responded to soil moisture as well as toalinity, soil texture, and temperature. Later, Andrade et al.
2004) modified the sensor and mounted it behind a tillageool. Additional field tests revealed an improved relation-hip between estimated conductance values and soil moistureontent. Recently, a capacitance sensor was also combined
r i c u l t u r e 6 3 ( 2 0 0 8 ) 89–103 99

with the cone of a single-tip horizontal penetrometer forsimultaneous on-the-go mapping of soil water content andmechanical resistance (Sun et al., 2006; Schulze Lammers etal., 2007).

In addition, NIR absorbance spectroscopy has been consid-ered as an attractive technique for measuring water content.Such sensors are based on the fundamental property of waterto absorb light energy at certain bands of the spectrum (Norris,1964). A fiber-type visible and near-infrared (NIR) spectropho-tometer was used by Mouazen et al. (2005b) to develop a sensorfor the on-line measurement of water content. The sensorwas attached to a subsoiler chisel backside to detect lightreflectance from the bottom side of a trench opened by thechisel. It was reported that the spatial patterns of soil watercontent obtained using the sensor, and with the oven-dryingmethod were similar.

5. Sensor fusion

Based on the assumption that soil texture and the level ofcompaction influence the ability of soil to retain nutrients,Lui et al. (1996) developed a real-time texture/compactionsensor system using the reference tillage tool developed ear-lier by Glancey et al. (1996). This draft-measuring sensor wasequipped with a dielectric-type moisture sensor, a radar gun tomonitor the speed, a linear potentiometer to measure depth,and a GPS receiver. It was acknowledged that the measureddraft was affected by the geometry of the reference tool, soilproperties, operating depth, and travel speed. When this draftwas also compensated for changing soil water content, a tex-ture/compaction index (TCI) was defined. Since soil texture istemporally constant, the TCI can be used to infer the level ofsoil compaction. Therefore, an empirical equation was usedto estimate the TCI based on the measured moisture contentand the draft of the reference tillage tool operated at a constantspeed and depth.

Later, Mouazen et al. (2003a,b) stated that such an equationmay have a narrow range of applicability due to relatively highsoil heterogeneity and rather complex relationships amongvariables involved. Therefore, it might be more appropriateto develop a technique capable of simulating the interactionbetween draft, dry bulk density, moisture content, and depth.As a result, Mouazen et al. (2003a,b) proposed a method to pre-dict soil dry bulk density (BD) as a function of the cutting depth(d) and measured horizontal force (D) of a soil mechanicalresistance sensor, and soil moisture content (MC). A single-shank subsoiler with a 6-cm wide chisel tip was used as the soilmechanical resistance sensor. First, Mouazen et al. (2003a,b)used a numerical (finite element) statistical hybrid modelingscheme to establish an equation relating the variation in drybulk density with soil MC, d and D of the soil mechanicalresistance sensor (Mouazen and Roman, 2002). The finite ele-ment analysis showed that the draft increased with dry bulkdensity and depth, whereas it decreased with moisture con-tent. With a fusion of soil mechanical sensor, depth measuring
sensor, and moisture sensor, a unique system was developedfor evaluating soil compaction (Mouazen and Roman, 2006).On-line measurements of draft (D) and depth (d) were per-formed with a single-ended shear beam load cell and a metal

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wheel equipped with a linear variable differential transducer(Mouazen and Roman, 2006). A depth control system wasdeveloped to ensure that soil compaction is measured at a rel-atively constant depth (Mouazen et al., 2004, 2005a; Anthoniset al., 2004; Saeys et al., 2004). The soil moisture content wasmeasured on-line with a fiber-type visible and near infraredspectrophotometer sensor (Mouazen et al., 2005b). The sys-tem was evaluated by pulling the subsoiler at a depth of 15 cmin a perpendicular direction to the tramlines in a field with asandy-loam soil. The soil samples for measuring soil bulk den-sity were taken before running the subsoiler. They stated thatthe spatial pattern of bulk density maps produced using on-the-go measurements and obtained directly were similar withcorrelation coefficient (r) of 0.75 (Mouazen and Roman, 2006).The BD prediction model using D, d, and MC was developed fora specific soil (loam and sandy-loam); therefore, a predictionequation for each soil type should be obtained before usingthe on-line measurement system in other fields.

As shown by Lui et al. (1996) and Mouazen and Roman(2006), integrating (fusing) different measurement conceptsinto a single mapping unit can improve our understanding ofthe spatial variation of soil compaction within an agriculturalfield. Involvement of a soil strength profile sensor or a verti-cally oscillating tool could further increase the applicability ofthe knowledge gained.

For example, Benjamin et al. (2003) emphasized that bulkdensity gave little insight on the underlying soil environmentthat affects plant growth. They used the concept of least lim-iting water range (LLWR) introduced by Silva et al. (1994), asa measure of management effects on soil potential produc-tivity. The LLWR combined limitations to root growth causedby water-holding capacity, soil strength, and soil aeration intoa single number that could be used to determine soil physi-cal behavior. Therefore, fusion of soil mechanical resistance,moisture, and air permeability sensors could result in a uniquesystem capable of mapping an index such as LLWR to addressthe response of plants to spatially variable physical soilstates.

Therefore, properly delineated field areas associate withyield-limiting combination of multiple sensor measurements,which can be obtained using sensor fusion method, canbecome finite management units deemed to be adequate forthe deployment of given treatments allowing improve localcrop growing environments.

6. Sensor application

As shown in Fig. 2, measured soil compaction can be assesseddirectly, following a series of recommended test procedures,or can be predicted using one or several indirect (behavior)measures of soil compaction, which are feasible using thedescribed soil compaction sensor systems.

Potentially, producers could use on-the-go sensors to deter-mine the local depth of a hardpan layer threatening to limityield, or simply identify field areas presenting soil mechani-
cal characteristics needing special intervention for improvedfield productivity. Variable depth tillage, spot tillage, spatiallyvariable water treatments, localized chemical application, anddeployment of biological organisms have been a few options
g r i c u l t u r e 6 3 ( 2 0 0 8 ) 89–103

currently discussed as possible ways to utilize sensor-basedmaps to improve economic and environmental outcomesof crop production. For example, site-specific tillage, whichmodifies the physical properties of soil only where tillage isneeded for optimum crop growth, has several advantages.Raper (1999) estimated that the energy cost of subsoiling couldbe decreased by as much as 34% with variable versus uni-form tillage. Fulton et al. (1996) reported that fuel consumptioncould be reduced by 50% using site-specific tillage compared tosubsoiling the entire field. In another study, Raper et al. (2007)found a 43 and 27% reduction in fuel use, and 59 and 35%reduction in draft force for site-specific subsoiling in shallow(25 cm) and medium (35 cm) depth hardpan plots, as comparedto uniform deep (45 cm) subsoiling in the same plots. Similarly,Khalilian et al. (2002) found the energy savings of 43% and fuelsaving of 28% through variable-depth tillage as compared touniform-depth tillage.

Recently, penetrometer resistance has become an impor-tant measurement while assessing whether roots canpenetrate soil (Whalley et al., 2005). It was shown that theresistance of a soil to a penetrometer can be a factor up to3 times greater than the actual force resisting root penetra-tion (Bengough and Mullins, 1990). Partially, this difference hasbeen explained by reduced friction between roots and soil ascompared to metal and soil (Bengough and McKenzie, 1997).However, it can be expected that the greater the resistance ofsoil media to cone penetration, the higher the resistance toroot development. Generally, it is accepted that a fixed (non-rotating) penetrometer resistance in excess of 2.5 MPa willseriously restrict root elongation (Groenevelt et al., 2001).

To use on-the-go soil impedance sensors, horizontallyobtained measurements of soil mechanical resistance havebeen compared with different derivatives of cone index pro-files. However, in order to be able to compare the soil strengthmeasured by a tine- or tip-based sensor to standard cone pen-etrometry, the nature of the soil disturbance ahead of themshould be similar. As stated earlier, the soil failure mode aheadof a vertically penetrating cone is of a bearing-capacity fail-ure type; whereas for a narrow tine, the same failure modeoccurs only below the critical depth. Therefore, predictabilityof corresponding cone index values using on-the-go sensorscan be improved if principles of soil failure mechanics are con-sidered at the design and evaluation stages. For example, todelineate field areas with relatively high surface compaction,a very narrow tine (e.g., disc coulter, Hemmat et al., 2008) canbe employed and followed by a vertical tine to measure soilmechanical resistance deeper in the profile.

7. Summary

Through the adoption of precision agriculture many pro-ducers have considerably altered their soil treatments toaccount for spatially variable soil characteristics, includingcompaction. Although compaction is described using a setof direct measures such as bulk density, indirect (behavior)
characteristics have been addressed by the various sensorsdiscussed in this publication. Numerous approaches havebeen used to measure soil strength as a predictor of root pene-tration resistance imposed by soil to emerging crops. Knowing

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he soil failure mode is essential when developing horizon-ally operated sensors and comparing their outputs to thetandardized cone penetrometer measurements. Variable pre-iction models have been developed to relate physical soilroperties and sensor measurements. Integrating differentensors into a soil compaction sensor system has shown to bepromising approach. Simultaneous mapping of soil mechan-

cal resistance at different depths, water content, and fluidermeability could significantly improve our knowledge ofpatially variable soil physical states and potentially increasearming efficiency.

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