3-D Visualization of soil macroporosity usingx-ray CAT scanning

J. PERRET1, S.O. PRASHER I, A. KANTZAS2 and C. LANGFOR02

JDepartmellt ofAgricultural and Biosystems Engineering, McGill University, 21111 Lakeshore Road, Ste-Anne-de-Bellevue,QC, Canada H9X 3V9; and 2Departmellt o/Chemical and Petroleum Engineering, University o/Calgary, 2500 UniversityDrive N.W., Calgary, AB, Canada T2N lN4. Received 18 March 1996; accepted /6 September 1997.

Perret, J., Prasher, S.D., Kantzas, A. and Langford, C. 1997. 3-DVisualization of soil macroporosity using x-ray CAT scanning.Can. Agric. Eng. 37:249-261. Computer assisted Tomography(CAT) offers considerable potential for reliable and nondestructivein-situ characterization of macropores occurring in agricultural soils.Several researchers have used CAT techniques for characterizingsoil macropores of small undisturbed soil cores. However, there isstill a need to develop comprehensive algorithms to automate theanalysis and interpretation of macropore geometry directly fromCAT scan data. Four undisturbed soil columns (800 mm long x77 mm diameter) were extracted from a loamy sand field in centralCanada and scanned for the visualization and characterization oftheir interconnecting macropore structure. A total of 240 scans of3-mm depth were taken for each column. After conversion of the rawCAT scan data into density matrices, two- and three-dimensional soildensity reconstructions were generated. With the elaboration of nu­merous computer programs in the PV-WAVE language, this analysisgives a detailed representation of the spatial variations of the macro­pore structure and heterogeneity of soil.

La technique de CAT scanning (Computer Assisted Tomography)offre une opportunite unique pour la caracterisation des cheminsd'ecoulement preferentiel presents dans les sols agricoles. Cetteapproche permet de visualiser et d'etudier les macropores du sol defa~on fiable et non destructive, et ainsi, de mieux comprendre Iemouvement rapide de I'eau et des composes chimiques atravers Iesol. II est essentiel de quantifier ce phenomene hydrologique afind'acquerir une meilleure comprehension de I'impact de cephenomene sur la contamination des eaux souterraines. Le nombrede macropore par unite de surface, leur diametre, leur orientation,leur circularite, ainsi que leur tortuosite influencenl directement Iephenomene de flot preferentiel et pourtant, ces parametres ne sontpas pris en consideration dans la plupart des modeles mathematiquesutilises pour la prediction du transport de I'eau et des composeschimiques dans Ie sol. Dans cet article, nous presentons ces differentsparametres tel qu'evalues aI'aide de rayon X en utilisant un scannermodele EMI CT5005. Plusieurs colonnes de sol (0.8 m x 77 mm dediametre) ont ete prelevees intactes dans un champ du centre duCanada. Un total de 240 sections de 3 mm d'cpaisseur ont etescannees permeUant ainsi la visualisation et I'analyse de la structuredes macropores de chaque colonne. Apres transformation des don­nees brutes generees par Ie CAT scanner en matrices represcn lant ladensite volumetrique du sol, la porosite de chaque colonne a etcredefinie en deux et trois dimensions. Cette analyse pemlet derepresenter en detail la variation spatiale des chemins d'ecoulementprCferentiel ainsi que les heh~rogeneites du sol.

INTRODUCTION

A number of investigators have established that the presenceof macropores results in rapid movement of water and asso-

ciated solute through the soil profiles (Beven and Gennann1982). Since flow through macropores is much faster thanthrough the soil matrix, travel time for water and dissolvedchemicals is directly affected by the number of macroporesper unit area and also their continuity. Short travel time maynot allow contaminants, such as pesticides, to be adsorbed onand into the soil surfaces and broken down by chemical andbiological action. To obtain a better understanding of thesesoil-water processes, the characterization of the macropores(ie: areal distribution, size, shape, continuity, etc.) is essen­tial.

Several researchers have used indirect approaches, such asthe use of breakthrough curves or tension infiltrometers tostudy macroporosity. However, indirect approaches onlyprovide qualitative information about soil porosity. Quantita­tive analysis of macroporosity provides a morecomprehensive and systematic approach and is nonnally ob­tained by direct methods. Koppi and McBratney (1991),Moran and McBartney (1992), Singh and Kanwar (1991),and VenneI et a1. (1993) used an impregnation and sectioningtechnique by intruding paraffin or epoxy resin into the soilprofile and sectioning the soil sample with a mechanical saw.Other researchers such as Booltink and Bouma (1991),Logsdon (1995), Trojan and Linden (1992), and Wu et aI.( 1993) characterized flow patterns along macropores usingdye tracers such as methylene blue. These two direct ap­proaches have a common disadvantage, ie., the destruction ofthe soil sample before verifying that the dye, the paraffin, orthe resin has been fully impregnated throughout the macro­pore structures of the soil profile.

In the early 1980s, CAT scan technology started to be usedin non-medical fields and its great potential for non-destruc­tive analyses was immediately recognized. In one of the firststudies involving soil science, Petrovic et a1. (1982) showedthat CAT scanning was a promising tool for rapid detennina­tion of soil bulk density. They found that the mean bulkdensity in a soil core was linearly related to the core's meanX-ray attenuation coefficient. A year later, Hainsworth andAylmore (1983) conducted experiments to examine the spa­tial changes in soil water content using CAT. They reportedthat computer assisted tomography was successful in moni­toring the changes in soil water content and wrote: "CATscanning presents an extremely exciting possibility for stud­ies of soil-plant water relations ". Crestana et al. (1985) usedCAT to observe the changes in X-ray attenuation coefficient

CANADIAN AGRICULTURAL ENGINEERING Vol. 39, No.4. OctobcrlNovemberlDcccmbcr 1997 249

Table I: Studies using CAT scanning for the evaluation of pore structure of intact soil cores

Research Institution

Department of AgriculturalEngineering / Department ofRadiology University ofMinnesota, SI. Paul, MN.

Saskatchewan Institute ofPedology, University ofSaskatchewan, Saskatoon, SK.

Department of Agronomy andDepartment of Civil Engineer­ing University of Missouri,Columbia, MO.

Department of Horticulture,Department of Agronomy, De­partment of Human Oncology,and Department of Radiology,University of Wisconsin,Madison, WI.

Biology and AgriculturalEngineering Department, De­partment of Crop and SoilScience, and the Institute ofEcology, University of Geor­gia, Athens, GA.

School of Engineering (Uni­versity of Guelph) and ImagingResearch Laboratory (RobartsResearch Institute), Guelph,ON.

Summary

Macropores were detected withCAT scanning. By sectioningthe soil core, the validity ofCAT scanning was alsoverified. The number and sizeof macropores were approxi­mately the same below a depthof50mm.

The soil macropore system anda compacted soil layer wereanalyzed using CAT scanning.The validity of CAT scanningwas verified with impregnatingtechniques. A soil macro­porosity of 15.7% wasmeasured. The average area ofa single macrofore was foundto be 20.4 mm .

Undisturbed soil cores (76 mmdiameter x 76 mm 'long) werescanned for evaluating thestructural characteristics ofsoils (bulk density). Bulkdensity correlated well with thesize and location of artificialmacropores.

Macropore structures werereconstructed and visualized in3D from CAT scan data.

A theory for non-destructivedetermination of conductivityin soil cores (150 mm diameterx 350 mm long) in terms of thePoiseuille-Carman equationwas evaluated. It was foundthat the number of macroporesdecreases with depth.

A CT scanner was used toestimate the overall macro­porosity ofsix soil columns. Theyreported a decrease inmacroporosity with depth andfound a greater variabilitycloser to the surface.

Limitations

- Visual interpretation of scanimages

- Distance between scansvarying from 10 to 50 mm

- No consideration were given tothe geometry and three­dimensional parameters ofmacropores

- Small soil cores (160 mm inlength)

- Analysis of macroporesperformed on grey-scaleimages (not directly from theCAT scan raw data)

- No consideration was givento the geometry and three­dimensional characterizationof macropores

- Very small soil cores

- No consideration was givento the geometry and three­dimensional parameters ofmacropores

- This study neither quantifiednor characterized the 2D or3D geometry of macropores.

- Small soil cores- 50 mm distance between scans

- No consideration was givento the three-dimensionalparameters of macropores

- Small soil cores, 90 mmdiameter x 200 mm long

- Distance between scans was20mm

- No consideration was givento geometrical characterizat­ion and three-dimensionalparameters of soil macro­pores

References

Warner et al. (1989)

Grevers et al. (1989)Grevers and de long (1994)

Anderson et al. (1990)Peyton et al. (1992)

Hanson et al. (1991)

Tollner et a1. (1995)

Asare et al. (1995)

250 PERRET. PRASHER, KANTZAS and LANGFORD

Screen Artificial Macropore PVC Cap

SoilInlet PVC Pipe Outlet

Fig. I. Schematic illustration of the design of the soil t:olumn with the ~wtificial m3cropore.

with lime as a welting front passed through a homogeneoussoil corc. They dcmonslralcd the ability of scanners 10 detectwaler movement in soil and concluded Ihal CAT scanningwas opening new possibilities for nOll-destructive measure­ment of spatial and dynamic waler contents. They <Ilsodeveloped a CAT miniscanllcr for field analysis (Cresrana elal. 1986). Using small homogenized soil cores. Anderson ctal. (1988) showed that the relationship between volurncfraclion of solids in cores and mean X-ray allcnuation waslinear and found the CAT approach to be a powerful 1001 forsoil research. Jenssen and Heyerdahl (1988) applied CATscanning to study the packing arrangement and density ofsoil columns lIsed in experiments concerning waleI' transporland wastewater purification. They staled Ihat CAT scanning"offers fascinating possibilities in the field of soil science".

The above studies clearly indicate Ihal CAT scanning is avaluable tool for investigating soil-water processes. Otherinvestigators such as Phogal and Aylmore (1989) have alsodemonstrated its potential for determination of soil watercontent and bulk density.

However. all of the above studies werc pcrfonncd lIsingsmall corcs that had been uniformly packed with sieved andhomogenized soils. Therefore, these studies did not evaluatesoil structures in their native ficld conditions.

Warncr ct al. (1989) are among the first researchcrs 10

have used CAT techniques for characterizing Ihe spatialdistribution of soilmi:lcropores of undisturbed soil cores. Thefeasibility of CAT scanning for macropore characterizationwas assessed by physically sectioning the soil column alongthe scan plane in order to compare features of scan imageswith the physical section of the core. Warner et al. (1989)reponed that "the CAT scan process is a promising non-de­structive method for the characterization of macropores insoil", However. the scans were examined and il1lerprcted visu­ally, They pointed out the need to develop a comprehensivealgorithm to automate the interprctation or images produced bythe CAT scanllCr. Moreover. the distance betwcen consecutivescans in their study varied from 10 to 50 mm, leaving a big gapof "unexplored" soil. These gaps can cause a major problem inthe interpretation of the results since conlinuity and wnuosity ofmacropores cannot be assessed.

Grevers et al. (1989) also investigatcd a soil macroporesystem by comparing images from CAT scanning wilh im­ages obtained by physically sectioning the soil corc. Theyfound that the results of the CAT scan im,lges comp,Hcd wellwith the features observed in the sections of the soil columns.In their study. the length of the soil cores was limited 10160111 Ill. Thus, their investigation was limited 10 a small region

of the vadose zone.Following the pioneering work of Grevers et al. (1989)

and Warner el al. (1989). several researchers examined, ingreater detail, the use of CAT scanning for the charac­terization of soil macropores in intact soil cores. Table Iprovides an annotated reference list or the research work onCAT scanning for describing soil macroporosity in undis­turbed soil columns. Up to now. it can be stated that theapplication of CAT sc'lnning offers a very accurate andrepeatable way to bypass the resin impregnation and otherphysical slicing operations in the swndard optical approachto perform a pore characterization analysis. However. CAThas not been used to its full potential for the quantificationof soil macropores and investigation of preferel1lial nowprocesses. In most studies. the sizes of undisturbed soil coreswere 100 small and Ihe distances belween conseclltive scanswere 100 large to generate accurate and complete charac­terization or soil macropores.

Some recent studies. like Asare et al. (1995). have usedCAT scanning to investigate soil macropores. However, theirstudy was limited to the variations of macroporosity in the A

Fig. 1. I>osilion of the soil core in the CAT scanner.

CANADIAN AGRICULTURAL ENGINEERING Vol. ]lJ. No.~. Octohcr/No\'cmbcr/Dcl:clllbcr llJlJ7 251

and B horizons. Their relatively small soil columns (200 mmx 90 mm) were scanned every 20 mm, leaving a big gap ofunknown information between two consecutive scans. More­over, in their work, consideration was not given to thenumber of macropores, their size, position, and geometry. Inaddition, three-dimensional parameters, such as tortuosity,connectivity, etc. were not quantified.

Imagery capabilities of most CAT scanners used in soilstudies have been limited to two-dimensional serial scans.Very little work has been done to characterize the macro­porosity of intact soil cores in terms of theirthree-dimensional parameters. Tollner et al. (1995) pointedout the need for additional research to investigate reliableapproaches for computing tortuosity and connectivity of soilmacropores. Imaging in three-dimensions and quantificationof three-dimensional parameters of soil macroporosity arecritical in order to accurately correlate soil pore structurewith preferential flow phenomena and much additional workis needed in this area (Hanson et al. 1991).

We are currently investigating macroporosity and model­ing preferential flow processes in four large undisturbed soilcolumns (800 mm x 77 mm) using computer assisted to­mography with a X-ray based scanner. In this study, each soilcolumn was scanned in 240 positions leaving no gap ofinformation between two consecutive scans. Computer pro­grams were developed in PV-WAVE language for systematicquantification and visualization of soil macroporosity di­rectly from CAT scan data. Som~ of these computeralgorithms are presented in this paper. The visualization partof this work enabled us to generate 3D views of the structureof macropores to an unprecedented level.

Table II:

MATERIALS AND METHODS

Soil columns

In July 1995, four undisturbed soil columns, 800 mm long x77 mm diameter, were taken from a field site at the Macdon­ald Campus of McGill University in Ste-Anne-de-Bellevue,QC. The land slope was less than one percent. The columnswere extracted from an uncultivated field border that hadbeen covered for many years with a combination of quackgrass (Elytrigia repens), white clover (Trifolium repens) andwild oat (A vena !aflta). Periodic mowing during the summerwas the only cultural practice. The soil cores were obtainedby driving a polyvinyl chloride (PVC) pipe into the soil witha backhoe. The lower end of the PVC pipe was shaped to athin cutting edge in order to reduce the compaction inside thecolumn and to facilitate the insertion of pipes into the soil.After the extraction of the columns, the cutting edge wasremoved, allowing the end of the PVC pipe to be sealed witha PVC cap. The soil columns were extracted during a periodwhen the soil moisture was near field capacity. Between thetime of excavation and the time of scanning, the cores werefree to drain through a small outlet located at the bottom ofthe PVC pipes. Change in moisture content due to evapora­tion was minimal, since both ends of the columns were sealedto prevent any soil loss during transportation. One of the soilcolumns was drilled from top to bottom to verify the abilityof the CAT scanner to portray the size and the location of aknown pore. This artificial macropore consisted of a polyeth­ylene tube of 1 mm in outer diameter (Fig. I).

The soil where the soil columns were extracted is of theChicot series. The Chicot soils are developed from sandymaterials over a calcareous till and as a result they are gener­ally well drained (Lajoie and Baril 1954). They usuallycontain a high percentage of fine sandy loam. The soil prop­erties of the soil profile were determined by taking small

Selected Soil Properties of a Chicot soil under a combination of quack grass (Elytrigia repens), white clover(Trifolium repens) and wild oat (Avenafatua)

Depth Bulk pgl 002 Clay Silt Sand OM3 CEC4 pH Description

density(m) (Mg/m3) (Mg/m3) (%) (%) (%) (%)

0.0-0.15 1.36 2.51 23.9 6 12 82

1!Dark brown with fine crumb

0.15-0.30 1.27 2.52 24.7 5.5 12.5 82 3.96 9.66 6.32 structures - slightly firm

0.30-0.45 1.30 2.59 24.2 7 9 84 IBrown to yellowish brown0.45-0.60 1.30 2.60 21.5 5 8 87 - compact layer with occasional

rocks presence of earthwormchannels

0.60-0.75 1.46 2.64 11.8 8 8 84 1.20 8.01 6.0 I • Brown to greyish brown

0.75-0.90 1.64 2.59 14.2 14.5 8.5 77 !-gmVCIY layer with a significantincrease in clay content - very

... compact

I Mineral grain density 3 Organic matter content.,4 Cation Exchange Capacity (Cmol/kg)- Gravimetric water content at field capacity

252 PERRET. PRASHER. KANTZAS and LANGFORD

Fig. 4. Longitudinal views of the four soil columns.

ArtificialMacropore

DenseArea

Quant ificalion of soil macroporosit)1

The quantification of soilmClcroporcs seeks to identify inher-

macropores, based entirely on the CATscan dati1. These three algorithms permit athree-dimensional image to be recoll­stmclcd from lTIuhiple contiguous scans.The rirst program (Make3D.pro) isolatesmacropores in 2D matrices, cfunches thevalues of each pixel 10 a range of 0-255,and combines them into 11 3D ASCII array.The second program (Conv_binary.pro)converts the 3D ASCII array into BinaryI/O formal. The Binary I/O format is thesimplest and l11os1 efficient form of I/O.Images and large claw sets afC usuallyslored and manipulated using Binary I/Oin order to minimize the processing loadon the machine. The third program(R view.pro) produces a I iSl of veri ices andpolygons that describe lhe three-dimen­sional surface of macropores. Each vaxelis visited to find polygons formcd by themacropores. The polygons are thcn com­bined and rendered 10 reconstruct an cxactthrce-dimensional representation of the in­terconnected network of soil pores and

cavities. The reconstructed image allows the visualization ofsoil macropores as never seen before (Fig. 5). Severalm:lcro­pores arc displayed as vertical descending structures. Itshould be noted that the artificial macropore in column 4 isclearly visible.

Density0.0 g/cm3 .iii::~:::J 3.0 g/cm3

LightArea

Macropore

Cross·sectional im~lges; (a), (b) and (e) contrast enhancemenl usingditTerent color tables, (d) contour map, (e) partial threshold and(f) total threshold of the soil macropores.

Fig. 3.

Ihreshold to isolate soil macropores. To enhance or maskportions of the image. a binary threshold was used for betterdetection of soil macropores. The program was used exten­sively for the visualization of cross-sectional images and theexamination of shape. size, and distribution of macropores.Some of these cross-sectional images arc presented in Fig. 3.

Longitudinal views are useful for the visualization of thedistribution of low and high density areas along the length ofthe soil column. To generate longitudinalviews. another program in PV-WAVE(Longi_mak.pro) was developed. This pro-gram stacks up 240 sections. one on lOp ofthe olher. and "cuts" through a verticalplane to extract a vertical cross-sectionalslice from the three-dimcnsional block ofdata. The position of the plane that biseclsthe volumc of data is delermined using afixed pixel depth. For each column. 115longitudinal images can be generated in thex-direction as well as in the y-direclion.Figure 4 displays longitudinal views of thefour soil columns. using a pixel depth in thex-direction of 50 (middle of the columns).

In hospitals. three-dimensional imageryhas recently been possiblc with the aid ofpowerFul slercotactic radiosurgery com­puter programs (Hanson et <11.1991).However. these soflwarcs arc vcry expen-sive and not offered on typici.lI medicalscanners (Aylmore 1993). Since 3D imag-ing is critical in order to accuralelycorrelate soil pore structure and space withnow processes occurring in the soil. it wasdecided to develop our own Ihree-dimen-sional reconstructive methodology. Threeprograms in PV-WAVE werc developed togenerate three-dimensional models of

254 PERRET. PRASHER. KANTZAS and LANGFORD

forms CTN arrays into matrixes of bulk density. Part of thealgorithm also allows the computation of porosity distribu­tion of the soil. When the minerals constituting the soilparticles have been identified, the porosity of each individualpixel was estimated from (Kantzas 1990):

where<p = porosity of the volume element,pg = grain density (density of the mineral making up the

solid portion of the soil matrix),Pb = bulk density, andPI =fluid density.

The fluid density in this case is the density of air.An additional algorithm was added to the program for the

selection of a region of interest (ROI). Only part of the320 x 320 matrices is actually used for the investigation ofsoil macroporosity. The resulting matrix requires only 96kilobytes of disk space and is composed of an array of115 x 115 elements.

Selection of programming language

Presumably, any high level programming language, such asFORTRAN, could have been used for post-processing andmanipulation of the two-dimensional matrices. FORTRAN iscommonly used in problems requiring intensive computa­tions. Unfortunately, the imaging capabilities of FORTRANare poor. The PV-WAVE language is a comprehensive pro­gramming environment that integrates state-of-the-artnumerical and graphical analyse. This programming lan­guage is widely used for analyzing and visualizing technicaldata in many fields, such as medical imaging, remote sens­ing, and engineering. PV-WAVE is an ideal tool for workingwith arrays, such as the CAT scan data, because of its array­oriented operators and its ability to display and process datain both ASCII and Binary I/O format. Therefore, PV-WAVEwas chosen as the programming language to be used for thisstudy. Another reason was PV-WAVE's ability to be usedunder both UNIX platform and PC environment.

Visualization of soil macroporosity

Visual inspection of bulk density and porosity matrices is animportant step towards the understanding and analysis of thecomplex structure macropore. In this section, various ways ofvisualizing soil macropores are presented. .

An interactive algorithm (Jofran.pro) was developed In

PV-WAVE for comprehensive inspections of the bulk den­sity and porosity matrices and creation of cross-sectionalimages. To generate images, the program converts ASCIImatrices into BINARY format. Each pixel value is scaledbetween 0-255 to form the image. In this context, an imageis a two-dimensional array of pixels for which each elementis attributed to a color, depending on its value. This programwas specially designed to allow: I) selection of differentcolor tables for contrast enhancement, 2) continuous map­ping, 3) contour mapping, 4) region of ~nt~rest exa~inat~on

(with the determination of summary statIStics), 5) estimationof feature coordinates, 6) GUI (graphical-user-interface)

samples from five locations at the field plot. The soil of thissite was predominantly a loamy sand with an A horizonthickness of around 0.4 m. A summary of the results of soilanalysis is presented in Table II. For determination of soilbulk density, percentage of clay, silt, and sand, and gravimet­ric water content, the reader is referred to Mehuys (1995). Fordetermination of particle density and chemical analysis ofsoil, an X-ray spectrometer was used, following the methodgiven by Jones (1982). The determination of organic matterwas achieved by following the methodology given by Nelsonand Sommers (1982). For cation exchange capacity and pH,the reader is referred to Hendershot et al. (1993a, 1993b).

Computer tomography process

Each of the four columns were scanned separately using anEMI CAT5005 full body scanner. In tum, each column wascarefully placed horizontally in the CAT unit so that theX-ray beam would intersect the soil column perpendicular toits longitudinal axis (Fig. 2). During the computer tomogra­phy process, an X-ray source and an array of detectors rotatein synchrony around the column. A multiple set of data isgenerated from a number of views around a section of thecore. More precisely, during a scan with the EMI CAT5005,the scanning assembly rotates in incremental steps of tendegrees around the core. This sequential rotation is repeatedfor 180 degrees to collect sufficient data to reconstruct asingle slice. The X-ray attenuations obtained from the differ­ent angular positions are combined to generate the cells orpixels (picture element) of a 320 x 320 element matrix. Eachindividual pixel represents a specific CTN value (ComputerTomography Number) or a specific X-ray attenuation coeffi­cient, normalized with respect to water. The CTNs constitutethe standard output of a CAT scanner (CAT scan raw data)and are usually expressed in Hounsfield Units (HU). In thisstudy, the CAT scan system parameters were set to 140 peakkV and 28 mA. A total of 240 sections or scans were obtainedfor each column in order to leave no gap between two con­secutive scans. For each scan, the volume element size, oftenreferred to as voxel, was 0.75 by 0.75 by 3.0 mm.

Matrix conversion and selection of region of interest

Each scan was recorded on a magnetic tape and transferredto a UNIX workstation and to a Pentium 133 MHz computerfor further data manipulation. Although expressed in HU, aCTN value is a dimensionless quantity. The CTN for water isroughly 0 and it is -420 for air. The CTN values or X-r.ayattenuation coefficients are a function of the electron density(bulk density) and atomic number of the material. It has beenpreviously demonstrated that the CTNs are linearly related t~

the bulk density of the soil (Anderson et al. 1988). The SOIlcolumns were mounted inside a core holder assembly madeof a hollow Plexiglas annulus partitioned into four chambersfilled with two liquids. Water and oil were used as referencematerials. By plotting CTNs versus the bulk density of refer­ence materials and using a simple linear regression, one caneasily derive a calibration curve that relates bulk dens.ity tothe X-ray attenuation coefficient of the scanned matenal. AFORTRAN program (Convert.f) was developed to computethe calibration line of each scan. Once the linear calibrationequations have been established, a computer algorithm trans-

Pg-PbPg-PI

(1)

CANADIAN AGRICULTURAL ENGINEERING Vol. 39. No.4. OClobcr/Novcmber/Deccmber 1997 253

RESULTS AND DISCUSSION

(3)

(4)A cross s('cliOIl

AboxR

The rectangularity can never excecd one. Rectangularilyclose to one implies that the macroporc lends to be rectangu­I~lr in shape.

For each column. the algorithm examines more than310.000 data values in order to characterize mJcroporosity.The first task accomplished by the program is 10 partition thetwo-dimensional arrays into regions of I for the pores and 0for (he soilmalrix. Thc pores contain either water or air (i.e ..density less than 1). Thus. by applying a threshold 011 all thepixels in the bulk density matrices having a value lower thanonc. the pore can be isolated (Fig. 6), This process is calledsc!!mentation. Once the two-dimcllsionalmiltrices have beentr~~lsformed into aand I elements. thc algorithmlllust recog­nize each individual pore. registcred as a sct of contiguousI·s. Two matrix elements having a valuc or I arc said to bepart 01" thc same porc if they arc sharing a COl11mon side. Inother words. to be pan of the same pore. a pixelnceds to havea value of I and 10 be locared in Olle of Ihe four nearestneighbour locations of the other pixel. In a single pass of thetwo-dimensional array. our algorithm recognizes and re­groups pixels belonging 10 the sUl1le pore. This part of theprogram is referred to as the clustering algorithm (Fig. 7). Asubroutine in the clusterin1? al1?orithm assesses the number ofpixels. perimeter. and rect;ng~lariIYof the pore. Some of thepores are 100 small 10 be classified in the macropore catc­gory. If the equivalent diameter of the pore is less than I mm,then the pore is removed frolllthc two-dimensional matrix byresetting each of its pixels to O. This simple process is calledfiltering. After filtering. all macropore attribules are com­puted. The program can be used eithcr for one section or forall the 2..tQ sections of a soil column. All macropore auributesare stored in an ASCII file for further analysis on a work ..sheet.

c=_P­deq IT

Since the circumfcrence is the smallest closed line thatembraces a two-dimensional ligure, circularity can never beless than one. Circularity value of one implies that the macro·pore is circular. A circularity much greater than one indicatesthat the macropore is elliptical. Rcctangularity is given by thearea of the macropore divided by the area of a bounding box.fanned around Ihe macropore (A,JOx) (Tollner et al. 1995).and is written in mathematical terms as:

ent m3cropore charaClCristics. such as their number. size. andgeometry. These characteristics arc used to describe macro­pores or the atlributes of macropores prior 10 the subsequenttask of classification and modeling. A program (Macro.pro)was written to recognize. extract and quantify the fcatures ofinterest in each of the two-dimensional arrays. This compre­hensive program provides a variety of mcasures of soilmacropores, such as the number of macropores per scan.surface area of each macropore. equivalent cylindrical di­amcter. pcrimcter, circularity. and rectangularity. The size ofthe macropores is usually described in tenns of its surfacearea (Across Sl'l'tio,,) and its perimeter (P). A more intuitiveindicator of macropore size is the equivalent cylindrical di­ameter (deq) of the pore, It is usually derived from thc surfaceare;:l as:

Fig. 5. Thrcc-dimcnsional rcconstruclion of soilmacroporcs of the four soil columns. ThearlificialmHcroporc can be obsc\'cd in columl1 4.

The shape of Ihe macropore is generally characterized bycomputing its circularity (C) and rectangularity (R). Thecircularity is deJlned as the ratio of the perimeter of thel11acropore.over the circumference of a circle. having a di­ameter equal to the equivalent diameter of the Illacroporc(Perret et 1.11. 1996), It can be wrilten as:

~4/\ cros.\ .w'l,tio"dN /=

"(2)

Variations in bulk density and total porosity were investi­gated as the first basic properties orthe soil. As noted earlier.the density matrix is based on the X·ray altenuation coeffi­cient of each voxel of the SCi.II1. Each voxel contains a mixtureof solid purticles (mineral grains. organic matter). air. andwater. Therefore. the X-ray attenuation coefficient ~lnd henceIhe bulk density matrix is affected by the waterCQIlIent oflhesoil at the lime of scanning. In other words. the densitymatrices represent the wcl bulk density of soil. II was us­sumed that the soil columns were at field capacity during the

CANADIAN AGRICULTURAL ENGINEERING V(II. :19. No, ..L O\:lobo.:r/No\'crnl~r/Dccernbcr 1997 255

CAT scan process. Gravimetric moisture content of the soil,at field capacity. was estim:'lIcd at 20%. With the gravimetricmoisture conlent known, the dry bulk density was calculated as:

where:

pbdry = dry bulk density (Mg/m3).pi,,,'" = wet bullk density (Mglm\ andro ;;; gravimetric moisture content.

With this formula, the dry bulk density was calculated andaveraged for every section of the soil columns. In addition.the total porosity of the soil was evaluated by:

~

a a a a a a a a a a a a a a a a aa 1 1 a a a a a a 1 1 a a a a a aa 1 1 1 1 a a a a 1 1 1 a a a a aa a 1 1 1 1 a a a 1 1 1 1 a a a aa a 1 1 1 1 a a a a a 1 a a a 1 aa a a 1 1 a a a a a a a a a 110a a a a a a a a a a 1 1 a a 110a a a a a a a a 1 a 1 1 1 1 a a aa a a a a a a 1 1 1 1 1 a a a a aa a a a a a a 1 1 1 1 1 a a a a aa a 1 a a a a a 1 1 a a a a a a a0,1 1 1 a a a a a a a a a a a a aa 1 1 1 010 a a a a 1 1 a a 1 1 aa a 1 a 010 a a a 011 1 a a a a aa a a a a a a a a 010 a a a a a ay

x

PhWefPIx/no =-­. I + (J)

Phll'("<\>=1--­

J + (J)

(5)

(6)

Illustration of the clustering algorithm. (a) Initial matrix. (b) The lirstpixel is located and the four nearest neighbors are chccked for valuesof I. (e) Thc visitcd pixel changed to a value different than I (2 in thiscase) and the investigation moves to the neighbor having a valuc of I(if two or more neighbors have a value of I, the algorithm puts them in··memory'·). The four new ncighbors are evaluatcd. Two neighboringpixels have a value or I. therefore. one or them is put in memory(denotcd by IIll). (d) The previous pixel is changed to 2. onc orthe four neighboring pixels has a valuc of I. thus. the algorithmmoves to the pixel in mcmory. (e) A value 2 is substituted in thepixels and the new neighbors are investigated. None have a value of 1previous and no pixel in memory can be recalled. (I) The evaluationof this pore is completed.

o 0

o °11 ° 0~O

o 0oo

where:<\> = 10lal porosilY. andpg ;;; mineral grain density (Mg/m3).

The mineral grain density. also known as the soil panicledensity, was estimated by X-ray Fluores­cence with a P\V240 spectrometer. II wasmeasured at six depths and the averagevalue for the soil profile was found to be2.58 Mg/m3. Figure 8 shows the variationsorthe dry bulk densily and the IOtal porositywith respect 10 depth. for each soil column.In 1995, the soil columns were scanned atfield capacity (gravimetric moisture content:= 20.2%) whereas. in 1996, the soil was dryduring scanning. Therefore. higher bulkdensity and lower porosity are expected for1995. Figure 8 confirms this supposition.

The bulk density of the soil ranges fromapproximately 1.2 to 1.89 Mglm3 while theminimal and maximal value for lotal poros­ity is 53.7 and 27.5%. respectively. Thefield site, frOin which thc soil columns wcreextracted. is used as passageway for ma­chinery during the summer activities.Marshall and Holmes (1988) mentioned Ihalthe bulk density of a sandy loam soil. whichhas been compacte<! by regular tmffic. couldreach 1.90 Mg/m.) with porosity valuesaround 28%. Thus. the results presentcd inFig. 8 appropriately describe soil conditionsprevalellt at the field sitc. The density tendsto increase with depth. This observationmay be attributed (Q an increase in the com­paction of soil panicles and a decrease inthe organic matter conte!1l with respect todistance from the soil surface.

Spatial resolution of the image. as deter­mined by the scanner and the reconstructionalgorithm, is 0.75 mm. If the boundary of ap;re falls in the middle of a pixel. the scan­ner will generate a CTN value that is an

o 0

o 0o 0o .~

o 0

0 0 0 0 00 OJi 0 00 ~.~ :2: 0"

0 0 0 0 00 0 0 0 0

c

ooo

oo

Figure 6 - Partial view of the 2Darray after segmentation.

0 0 0 0 00 0 ,4.~ 0 0

°I'~'t~;t; .~ 0..'.- .0 0 0 0 00 0 0 0 0

a

0 0 0 0 0 0 0 00 0 :..~. 0 0 .2· 0 00 .1.m Z ,2 2' °0 0 0 0 0 0 0 00 0 0 0 0 0 0 0

d e f

y

Fig. 7.

Fig. 6. Partial view of the 2D array after segmentation.

256 PERRET. PRASHER. KANTZAS and LANGf-'ORD

Column 4B"ko..Ity (g/crJ)

2

I,,=..

t..I

{:< ?

cD\

J {I .

oo

aoo

200

2

i~,

S:I

~

~•~,.at):

r

oo

aoo

200

2

Column 2B~kDmsity (g/cJ)

\~".l ~

~ .

~::

~.

1 I~,

j .,.

oo

lIOO

1110

200

2

1~~~~

-<c ~

If'l\

\:I. ~) ..

J t

oo

m

--1IlB•••••••1JiIS

---SlI8......... -1995

---S8lS......... ttSl5

---filS............ '&95

Fig. 8. Dry bulk density changes with depth of the soil profile.

Column 1

Macropore Count

Column 2

Macropore Count

Column 3

Macrop«e CotI'lt

Column"

Macropore Q)unt

302D10

700++-+---+-.......

eao+---I--+---+---t

2DO +--";'--=::;;;;"-+--4

100+--+-+---+---1

......._....._----

.r:. 4ClO ......-=::1---+---11i.~ sao +---.f-+--1---I

302010

8OO~-""'-"""---'

100 +---+-~-+---t

2m+--...--+---t

E 300 +-~IIIf---+---tE-=4OD+-----.;;poo,..::---t---tDoG

Q eoo +---+:...-=+---t

302D10

6OO+-Y--+--+--f

1m -1-+--+---+--4

2m +--+--+---+---1

100 +-~;=+---+--i

I 3m +----tfE~._..--1-t.-~ eoo+--~~ .........-__t

302D10

700 .f..4--f---+--f

2DO+-~~--+---t

fIX) -I--':----f---+--i

I--.r:. 400 +-~~--+---t15.'~ sao ......",J--+--+--__t

800 800 ....._ ......_ ........---'

Fig. 9. Number of macropores with respect to depth.

average of the attenuation of the soil matrix and air. Thepossibility that a pore of approximately 0.75 by 0.75 mmcoincides with a pixel is very small. Thus, a pore must besignificantly larger that 0.75 mm to enable detection andaccurate identification. Pores greater than 1.0 mm in diame­ter can be easily identified and characterized. This categoryof pore was defined as macropores by Luxmoore et al.(1990). However, it should be mentioned that the geometryof soil pores is rarely circular and, therefore, the concept ofdiameter is no longer adequate. Consequently. the termequivalent cylindrical diameter is used to describe the size of

non-circular/circular pores. For every section of the soil col­umns, the number of pores having an equivalent cylindricaldiameter greater than or equal to I mm (macropores) wasevaluated. The results are shown in Fig. 9. In general, thenumber of macropores decreases with depth. The decrease inthe number of macropores is due to a decrease in biologicalactivity. The number of macropores close to the soil surfacemay be affected by plant roots and species of oligochaete(earthworms, potworms, bristleworms, etc.) that are not pre­sent deeper into the soil profile. A high biological activitywill result in the formation of more macropores near the soil

CANADIAN AGRICULTURAL ENGINEERING Vol. 39. No.4. October/November/December 1997 257

'"..COlumn 4

M1croporosly (%)

~

?>i<)

I

oo

'"

700

'"

'00

'"10

Column 3M1croporos~y (%l

)

~)

'l')

~,-.?

oo

'"

700

000

200

'00

'"10

<

I?') ,

)~

oo

Column 2M1croporosity (%l

100

200

'00

'"10

c'-;5

"-...,

./(

)

f

Column 1M1croporos~y (%l

oo

'"

"'"100

'00

Fig. 10. Areal distribution of soil macropores will reSI)cct to deplh.

34 42 50 511 ee 7.

Depth (em>

investigated by dividingthe sum of all pixels be­longing 10 soilmacropores by the totalnumber of pixels in thesection. In other words.the areal distribution ofthe soil macropores.sometimes referred to asmacroporosity, is givenby the ratio of the surfacearea occupied by macro­pores divided by the totalsurface area of the sec­lion. The arealdistribution was evalu­ated for every depth andis presented in Fig. 10.Since the biological ac­tivity close to the soilsurface is more intense,one should anticipate alower m:lcroporositydeeper in the soil profile.As expected, m<lcro­porosity decreases withdepth. A comparison ofthe total porosity 10 Ihemacroporosity of the soilcan indicate the relativecontribution of soilmacropores 10 Ihe poros­ity of the porous medium(Fig. I I). Figure I I

shows similar trends for the tOlal porosity and for the macro­porosity of soil columns. Although macroporosity representsa minor portion of the soil porosity, it clearly affects thebehaviour of the total porosity of the soil. White (1985)reported that soil macropores comprise a small percentage ofthe IOtal porosity (I to 5%l, Edwards et al. (1990) observed

10 18 26 34 C2 50 511 85 7.

Depth (eml

:~u::::l=~::s:l: tJAct;mn~~~:C:o~lu:m~n=i4~

~35

f:ll.2O

15

10

5

o2

:u=!=u::::l=~:s:l451\-+-+-+++~~~~~

""~35~30

~:15

10

5o.pill1~lQll~$Sl~~4

2101826

10 18 26 34 42 50 5& ee 74

Depth (em)

10 18 2e 34 42 50 511 ee 74

Depth <em>

:~~~~+--+ Column 3 t-"+-+-+--+-I-+':-J,-=~=-'T;':"':;~

~: tJm!A1l!AA~- }enI++-l~30

~25ll.20

15

10

5 """''''''!ii!\l"",,oF?~~;;a!~F4:!3tiiiiii¥iU.l

2

;m~~_ Column 1

""~35~30

!l255 20ll.

15

'05

o2

Fig. II. Relative contribution of soil macroporosit.y with respect to del>th.

surface. However, in column 3, this trend is not as obvious asit is for the other columns. During transportation, the soilfrom the middle of column 3 may have been accidentallyloosened and could have led 10 the jumbled m<lcropore countobserved in the columll.

The areal distribution of the soil macropores was also

258 PERRET. PRASHER, KANTZAS and LANGFORD

Column 1 Column 2 Column 3 Column 4

ECD(nm) ECD(nm) ECD(nrn) ECO(nrn)

0 2 .. 8 a '0 2 .. 8 a 0 2 4 8 a 0 2 .. e a0 0 0 0

100 100 100 100

200 200 2DO200

1300 I- i- I3(M)- - -.c 400 .c400 .c 400 .c400~ ~ 1L 1l~500 ~500 t!500 ~500

600 lSOO 800 eoo

700 700 700 700

aoo 800 aoo aoo A.-_L........,,_....r._....

Fig. 12. Average equivalent diameter of the soil macropores with respect to depth.

Column 1 Column 2 Colul1Vl3 Column 421o

Oi---4-+-......q--t---.

700 -I---ClH.--4'--I---I

100 ~-.....+-~~+---t

800~-_.....--......-'

~Ciraarity-Rectq_1y

eoo +----'I---+--~-+---I

300 +---4--I---+-+---I

I-ga

21oo +--~+--+-t--.,

500 -I--oO--I--....-+----4

700 +---++-+---t----4

100 +-~t-+--tfC--+---I

eoo ......--.....------~Citaarity-o-RocUrv_tty

300 +--~-+-.......--t---t

I-!~

2oo +--9-+--~-I--..,

100 ~-.....+-~-t--.....

500 +---O-+-4--t--.....

700 +--4-+-+--f--~

200 +---O-+---oI..-t--....

800 .I....__"--__L...-I

-"-CItcUlrIty -o-RcqlAnty

300 -I---Q-+--;l--+-~

I-=4)() +--4-+-~-t--.....

!

21oo +--.......-....-1---.

700 +--+-+-4--+--1

600 +--4-+--+--f--f

500 +--~+-4--f--t

100 +--...q...+-4--f--t

800 """---"'----"---

-ClrcuIIwity -O-Rcq_ity

300 +---Q~-1---4-+--I

I-=4)() -i---4-+-.#f--+---1

!

Fig. 13. Average circularity and rectangularity of soil macropores with respect to depth.

macroporosity having a range from 0.4 to 3.8%. However, As mentioned earlier, the size of the macropores may bethese figures were estimated with infiltration techniques and inferred from their equivalent diameter. The average equiva-thus some dead-end macropores, which do not participate in lent diameter was computed for each section of soil in ordercarrying water flux, were not considered. to investigate changes in the size of macropores with depth.

CAT scanning provides a more systematic approach for The results are presented in Fig.12. The assumption is that theestimating macroporosity since all soil cavities are taken into size of macropores changes with depth, however, it is diffi-consideration. Thus, higher values of macroporosity are ob- cult to recognize a trend or a pattern in the fluctuations of thetained using CAT scanning. Asare et al. (1995), for instance, equivalent diameter. The presence of roots and arthropods,have reported values of macroporosity ranging from 13.8 to such as ants or beetles, close to the soil surface could have led36.1 %. Therefore, the results obtained in our study seem to to two distinct regions in the soil profile. However, the sizebe reasonable. of the macropores does not seem to be affected by depth. The

CANADIAN AGRICULTURAL ENGINEERING Vol. 39. No.4. Octobcr/November/Dccember 1997 259

geometry of a macropore may be investigated by estimatingits circularity and rectangularity. Circularity is defined as theratio of the perimeter of the macropore over the circumfer­ence of a circle having a diameter equal to the equivalentdiameter of the macropore. Since the circumference is thesmallest closed line that embraces a two dimensional figure,the circularity can never be lower than one. A circularityequal to one implies that the macropore is circular. A circu­larity much greater than one indicates that the macropore iselliptical. Rectangularity is given by the area of the macro­pore divided by the area of a bounding box, formed aroundthe macropore. The rectangularity can never exceed one. Arectangularity close to one implies that the macropore tendsto be rectangular in shape. The average circularity and rectan­gularity was calculated for every section of the soil columnin order to examine the changes in the geometry of soilmacropores with respect to depth (Fig. 13). The geometry ofsoil macropores seems to be independent on the distancefrom soil surface. Although the circularity and rectangularityfluctuate, there is no clear evidence of a tendency to increaseor decrease with depth. It should be noted, however, that therectangularity oscillates around 0.70. This means that thegeometry of the macropores tends to occupy a rectangularsurface at approximately 70%.

Although macropores are less numerous deeper into thesoil profile, they tend to have the same size and geometry.This implies that the origin or mode of formation of macro­pores is approximately the same throughout the soil profile.In temperate regions, earthworms dominate the soil's inver­tebrate biomass (Curry 1994). The formation of burrows is adistinctive feature of earthworm activity. Normally, largespecies, such as Lumbricus terrestris, which can weigh morethan 5g per worm, contribute substantially to the formationof long and continuous burrows. This species of earthwormhas been observed in the soil columns used in this study.These earthworms usually make vertical burrows down todepths of 2 m or more (Edwards et al. 1990; Ehlers 1975).These channels have a diameter ranging from 1 to 12 mmwith smooth walls cemented with mucus secretions. Theburrowing species create permanent and empty channels,which tend to run in the vertical direction. Since these typesof macropore are present both close to the soil surface anddeeper into the soil profile and therefore, it is possible that,on average, the equivalent diameter, circularity, and rectan­gularity do not decrease nor increase with depth in our 0.72m long soil columns.

SUMMARY AND CONCLUSIONS

The integration of computer programming in the PV-WAVElanguage, hardware, and medical imaging devices in soilstudies gives us the ability to investigate the interconnectedpore space of large undisturbed soil columns to an unprece­dented level. With the development of computer programs inPV-WAVE, the analysis of soil macropores was performeddirectly on the CAT scan data. Pores larger or equal to 1.0mm in equivalent diameter were readily detected, visualized,and quantified. The data generated by the CAT scan processwas manipulated in order to accentuate different features ofthe soil. Soil macropores were isolated by thresholding cer­tain values of the density matrices. This approach was

260

utilized for each section of the soil columns in order toevaluate: the number of macropores, the surface area, theequivalent diameter, the circularity, and the rectangularity ofeach individual macropore. Both the number and the surfacearea occupied by soil macropores decrease with depth. It wasalso observed that the size of the macropores is not affectedby the distance from the soil surface. Moreover, the geometryof the macropores is apparently not a function of the distancefrom the soil surface.

3D imaging is critical in order to accurately correlate soilpore structure and space with flow processes occurring in thesoil. Programs in PV-WAVE were develop.ed to visualize thecomplex three-dimensional network of interconnected porespace. These 3D reconstructions are unique.

Additional research is needed, particularly with respect tothe continuity and tortuosity of the macropore. In the nearfuture, geostatistics and fractal analysis will be used to com­plete the quantification of the soil macropores.

REFERENCES

Anderson, S.H., C.J. Gantzer, J.M. Boone and R.l. Tully.1988. Rapid non-destructive bulk density and soil-watercontent determination by computed tomography. SoilScience Society ofAmerica Journal 52:35-40.

Anderson, S.H., R.L. Peyton and C.l. Gantzer. 1990.Evaluation of constructed and natural soil macroporesusing x-ray computed tomography. Geoderma 46:13-29.

Asare, S.N., R.P. Rudra, W.T. Dickinson and A. Fentser.1995. Investigating soil macropores using a volume CTscanner. CSAE Paper No. 95-110. Saskatoon, SK: CSAE.

Aylmore, L.A.G. 1993. Use of computer-assistedtomography in studying water movement around plantroots. Advances in Agronomy 49: 1-54.

Beven, K. and P. Germann. 1982. Macropores and water flowin soils. Water Resources Research 18: 1311-1325.

Booltink, H. W. and J. Bouma. 1991. Physical andmorphological characterization of bypass flow in awell-structured clay soil. Soil Science Society ofAmericaJournal 5:1249-1254.

Crestana, S., R. Cesareo and S. Mascarenhas. 1986. Using acomputed tomographiy mini-scanner in soil science. SoilScience 142:56-61.

Crestana, S., S. Mascarenhas and R.S. Pozzi-Mucelli. 1985.Static and dynamic three dimensional studies of water insoil using computed tomographic scanning. Soil Science140:326-332.

Curry, J.P. 1994. Grassland Invertebrates. London, England:Chapman and Hall.

Edwards W.M., M.J. Shipitalo, L.B. Owens and L.D. Norton.1990. Effect of lumbricus terrestris L. burrows onhydrology of continuous no-till corn fields. Geoderma46:73-84.

Ehlers, W. 1975. Observations on earthworm channels andinfiltration on tilled and untilled loess soil. Soil Science119:242-249.

Grevers, M.C.J. and E. de Jong. 1994. Evaluation of soil-porecontinuity using geostatistical analysis on macroporosity

PERRET. PRASHER. KANTZAS and LANGFORD

in serial sections obtained by computed tomographyscanning. In Proceedings of Symposium on Tomographyof Soil-Water-Root Processes, eds. S.H. Anderson andJ.W. Hopmans, 73-86. Special publication no. 36.Madison, WI: Soil Science Society of America.

Grevers, M.C.J., E. de Jong and R.J. St. Arnaud. 1989. Thecharacterization of soil macropores with CT scanning.Canadian Journal ofSoil Science 69:629-637.

Hainsworth, J.M. and L.A.G. Aylmore. 1983. The use ofcomputer-assisted tomography to determine spatialdistribution of soil water content. Australian Journal ofSoil Research 21 :435-443.

Hanson, J.E., L.K. Binning, R.A. Drieslien, D.E. Stoltenberg,M.A. Gehring and M.A. Bonanno. 1991. A new methodof validating pesticide preferential flow throughthree-dimensional imagery of soil pore structure andspace using computed tomography. In Preferential FlowProceedings of the National Symposium, eds. T.J. Gishand A. Shirmohammadi, 129-141. St. Joseph, MI: ASAE.

Hendershot, W.H., H. Lalande and M. Duquette. 1993a. Ionexchange and exchangeable cations. In Soil Sampling andMethods of Analysis, ed. M.R. Carter, 167-175. BocaRaton, FL: Lewis Publishers.

Hendershot, W.H., H. Lalande and M. Duquette. 1993b. Soilreaction and exchangeable acidity. In Soil Sampling andMethods of Analysis, ed. M.R. Carter, 141-145. BocaRaton, FL: Lewis Publishers.

Henssen, P.D. and P.H. Heyerdahl. 1988. Soil columndescriptions from x-ray computed tomography densityimages. Soil Science 146: 102-107.

Jones, A. 1982. X-ray fluorescence spectrometry in methodsof soil analysis. In Methods of Soil Analysis. Part 2.Chemical and Microbiological Properties, 2nd edition,ed. A. Page, 85-121. Series of Agronomy No.9. Madison,WI: American Society of Agronomy and Soil ScienceSociety of America.

Kantzas, A. 1990. Investigation of physical properties ofporous rocks and fluid flow phenomena in porous mediausing computer assisted tomography. Ill-Situ14(1):77-132.

Koppi, A.J. and A.B. McBratney. 1991. A basis for soilmesomorphological analysis. Journal of Soil Science42: 139-146.

Lajoie, P. and R. Baril. 1954. Soil Survey ofMontreal, Jesusand Bizard Islands in the Province of Quebec. Ottawa,ON: Queen's Printer.

Logsdon, S.D. 1995. Flow mechanisms through continuousand buried macropores. Soil Science 160:237-242.

Luxmoore, R.J., P.M. Jardine, G.V. Wilson, J.R. Jones andL.W. Zelazny. 1990. Physical and chemical controls ofpreferred path flow through a forested hillslope.Geoderma 46: 139-154.

Marshall, T. J. and J. W. Holmes. 1988. Soil Physics, 2ndedition. Cambridge, UK: Cambridge University Press.

Mehuys, G.R. 1995. Soil Physics 372-331B. LaboratoryManual, 5th edition. Department of Natural ResourcesSciences, McGill University, Montreal, QC.

Moran, C. J. and A.B. McBratney. 1992. Acquisition andanalysis of three component digital images of soil porestructure. I. Method. Journal ofSoil Science 43:541-549.

Nelson, D.W. and L.E. Sommers. 1982. Total carbon,organic carbon, and organic matter. In Methods of SoilAnalysis, Part 2. Chemical and MicrobiologicalProperties, 2nd edition, ed. A. Page, 539-594. Series ofAgronomy No.9. Madison, WI: American Society ofAgronomy and Soil Science Society of America.

Perret, J.S., H. Pizarro, S.O. Prasher, A. Kantzas and C.Langford. 1996. Quantification of soil macropores bycomputer assisted tomography. In Proceedings of theInternational Conference on Porous Media and itsApplications, eds. K. Vafai and P. Shivakumar, 446-467.Columbus, OH.

Petrovic, A.M., J.E. Siebert and P.E. Rieke. 1982. Soil bulkdensity analysis in three dimensions by computedtomographic scanning. Soil Science Society of AmericaJournal 46:445-450.

Peyton, R.L., B.A. Haeffner, S.H. Anderson and C.J.Gantzer. 1992. Applying x-ray CT to measure macroporediameters in undisturbed soil cores. Geoderma53:329-340.

Phogat, V. K. and L. A. G. Aylmore. 1989. Evaluation of soilstructure by using computer assisted tomography.Australian Journal ofSoil Research 27:313-323.

Singh, P. and R.S. Kanwar. 1991. Preferential solutetransport through macropores in large undisturbedsaturated soil columns. Journal ofEnvironmental Quality20:295-300.

Tollner, E.W., D.E. Radcliffe, L.T. West and P.F. Hendrix.1995. Predicting hydraulic transport parameters fromX-ray CT analysis. ASAE Paper No. 95-1764. St. Joseph,MI: ASAE.

Trojan, M.D. and D.R. Linden. 1992. Microrelief and rainfalleffects on water solute movement in earthworm burrows.Soil Science Society ofAmerica Journal 56:727-733.

Vermel, V.R., J.D. Istok, A.L. Flint and J.L. Pikul. 1993. Animproved method for quantifying soil macroporosity. SoilScience Society ofAmerica Journal 57:809-816.

Warner, G.S., J. L. Nieber, J.D. Moore and R.A. Geise. 1989.Charaterizing macropores in soil by computedtomography. Soil Science Socety of America Journal53:653-660.

White, R.E. 1985. The influence of macropores on thetransport of dissolved and suspended matter through soil.Advances in Soil Sciemce 3:95-120.

Wu, L., J.B. Swan, J.L. Nieber and R.R. Allmaras. 1993. Soilmacropore and layer influences on saturated hydraulicconductivity measured by borehole permeameters. SoilScience Society ofAmerica Journal 57:917-923.

CANADIAN AGRICULTURAL ENGINEERING Vol. 39. No.4. Oclober/November/Decembcr 1997 261