(Advances in agronomy 59) donald l sparks (eds ) advances in agronomy elsevier, academic press (1997)

The basic principles underlying maize breeding, i.e., that inbreeding reduces vigor, cross-breeding increases vigor, hy- brids could be produced by detasseling one parent, and that hybri

V O L U M E 5 9

Martin Alexander Eugene J Kamprath

Cornell University North Carolina State University

Kenneth J Frey

Iowa State University

Lany P Wilding

Texas A&M University

Prepared in cooperation with the

American Society of Agronomy Monograpbs Committee

William T Frankenberger, Jr., Chairman

D V A N C E S I N

Edited by Donald L Sparks

Department of Plant and Soil Sciences

University of Delaware Newark, Delaware

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Contents

CONTRIBUTORS

PREFACE

QUANTITATIVE GENETICS AND PLANT BREEDING John W Dudley I Introduction

I1 History

I11 Tools of Quantitative Genetics

Iv Application of Quantitative Genetics to Plant Breeding

V Future Role of Quantitative Genetics in Plant Breeding

References

USE OF ORGANOCLAYS IN POLLUTION ABATEMENT Shihe Xu Guangyao Sheng and Stephen A Boyd I Introduction

I1 Synthesis and Chemical Stability of Organoclays

I11 N In Sitzl Modification

V Biodegradation of Contaminants in Modified Soils

References

Sorptive Properties of Organoclays

PHENOLOGY DEVELOPMENT AND GROWTH OF THE WHEAT (TRITZCUMAESTWCM L.) SHOOT APEX: A &VIEW Gregory S McMaster I Introduction

I1 General Patterns of Grass Shoot Apex Development

Iv V Conclusion

References

I11 Morphological Nomenclatures

Shoot Apex Developmental Sequence

ix

xi

1

2

4

9

19

19

25

28

36

44

54

57

63

64

64

67

101

102

APPLICATIONS OF MICROMORPHOLOGY

Rienk Miedema

I Introduction 119

11 Methods Used in Micromorphology 123 I11 Soil Structure in Relation to Land Use 128

IV Conclusions and Future Research Needs 157

References 159

PHYSIOLOGICAL AND MORPHOLOGICAL RESPONSES OF PERENNIAL FORAGES TO STRESS Matt A Sanderson David W Stair and Mark A Hussey I I1 I11 rv v VI VII VIII I I1 111 Iv v VI VII VIII IX X XI htroduction

Water Deficit

Defoliation Stress

Nutrient Stress

Salt Stress

Plant Breeding for Abiotic Stress Tolerance

References

Low Light

Low-Temperature Stress

CROP MODELING AND APPLICATIONS: A COTTON EXAMPLE K Raja Reddy Harry F Hodges and James M McKinion Introduction

P h e n o 1 o gy

Growth of Individual Organs

Partitioning Biomass

High-Temperature Effects on Fruiting Structures

Nitrogen-Deficit Effects

Water-Deficit Effects

Model Development

Model Calibration and Validation

Model Applications and Bridging Technologies

Summary and Conclusions

References

172

173

179

183

187

191

199

203

208

226

231

240

253

255

257

265

267

273

275

281

282

CONTENTS vii

A Edward Johnston

The Rothamsted Experiments

Ecological Research and Long-Term Experiments

Approaches to New Long-Term Experiments

I Inaoduction

I1 111 The Agricultural Value of Long-Term Experiments

W V Long-Term Experiments and Environmental Concerns

VI The Need for Long-Term Experiments

VII References

291 293 294 3 1 3 319 325 327 329 INDEX 335

contributors

Numbers in parentheses indicate the pages on which the authors’ contributions begin

STEPHEN A BOYD (2 S), Department of Crop and Soil Sciences, Michigan State

JOHN W DUDLEY (I), Department o f Crop Sciences, University of Illinois at

HARRY F HODGES ( 2 2 9 , Department of Plant and Soil Sciences, Mississippi

MARK A HUSSEY (1 7 I), Department of Soil and Crop Sciences, Texas A&M

A EDWARD JOHNSTON (291), MCR Rothamsted, Harpenden, Herts A L 5

JAMES M MCKINION (226), USDA-ARS Crop Simulation Research Unit, GREGORY S MCMASTER (63), USDA-ARS, Great Plains Systm Research,

RIENK MIEDEMA (1 19), Department of Soil Science and Geology, Wageningen

K RAJA REDDY (22S), Department of Plant and Soil Sciences, Mississippi State

MATT A SANDERSON (1 7 l), Texas A&M University Agricllltural, Research

GUANGYAO SHENG (2 S), Department of Crop and Soil Sciences, Michigan

DAVID W STAIR (1 7 l), Department ofsoil and Crop Sciences, Texas A&M Uni-

SHIHE XU (2 5 ) , Health and Environmental Sciences, Dow Corning Corporation,

University, East Lansing, Michigan 48824

Urbana-Champaign, Urbana, Illinois 61 801

State University, Mississippi State, Mississippi 39762

University, College Station, Texas 77843

ZJQ, United Kingdom

Mississippi State, Mississippi 39762

Fort Collins, Colorado 80522

Agricultural University, 6700 AA Wageningen, The Netherlands

University, Mississippi State, Mississippi 39762

and Extension Centq Stephenville, Texas 76401

State University, East Lansing, Michigan 48824

versity, College Station, Texas 77843

Midland, Michigan 48640

ix

Preface

Volume 59 contains seven state-of-the art reviews of various crop and soil sciences topics The first chapter presents an overview of quantitative genetics and plant breeding, including historical aspects, the tools of quantitative genetics, the appli- cation of quantitative genetics to plant breeding, and the future role and impor- tance of quantitative genetics in plant breeding The second chapter reviews the use of organoclays in pollution abatement Topics discussed include synthesis,

chemical stability, sorptive properties of organoclays, in siru soil modification, and biodegradation of contaminants in modified soils The third chapter covers the phe- nology, development, and growth of the wheat shoot apex, including general pat- terns of grass shoot apex development, morphological nomenclatures, and shoot apex developmental sequences The fourth chapter applies micromorphology to agronomic scenarios The discussion includes methods that are used in micro- morphology and soil structure in relation to land use The fifth chapter discusses the physiological and morphological responses of perennial forages to stresses, in- cluding water deficits, defoliation, nutrients, low temperature, and salt The sixth chapter is a comprehensive review of crop modeling and applications, with cotton

as the crop of interest Discussions on phenology, growth of individual organs, par- titioning biomass, high-temperature effects of fruiting structures, nitrogen and wa- ter deficit effects, and model development, calibration, validation, and applications are included The seventh chapter is a historically rich overview of the importance

of long-term field experiments in agricultural, ecological, and environmental re-

search

I appreciate the first-rate reviews of the contributors

DONALD L SPARKS

xi

I Introduction

11 History

A Plant Breeding

B Quantitative Genetics

C Use of Quantitative Genetics in Plant Breeding

111 Tools of Quantitative Genetics

A Description of Genetic Variation

B Description of Environmental Variation

C Predicted Gain Equation

D Correlated Response Equation

E Multiple Trait Selection Index

W Application of Quantitative Genetics to Plant Breeding

V Future Role of Quantitative Genetics in Plant Breeding

I INTRODUCTION

The objective of this chapter is to review the relationship between quantitative genetics and plant breeding from a plant breeding perspective Plant breeding is the science and art of genetic improvement of crop plants Quantitative genetics is the study of genetic control of traits that show a continuous distribution in segre- gating generations Quantitative genetics is concerned with the inheritance of those differences between individuals that are of degree rather than kind, quanti-

1

A d v m r s in A p n n m y Volume 79

0

tative rather than qualitative (Falconer, 1989) Where do these disciplines inter- sect? At one extreme, Kempthorne (1977) defined plant breeding as applied quan- titative genetics Simmonds (1984) on the other hand, considered biometrical ge- netics “to have helped to interpret what has already been done and to point questions, especially about the all important matter of response to selection, but to have had little impact on the actual practice of breeding.” Baker (1984) provided

an intermediate view when he suggested an understanding of quantitative genetic principles is critical to the design of efficient breeding programs In this review, Baker’s viewpoint will be followed Because many of the most important traits with which breeders work are inherited quantitatively, quantitative genetics must

ry was erected in 1802 (Smith, 1987) Thus, planned, directed plant breeding ef- forts resulted in a cultivar that allowed development of a new industry 100 years before the rediscovery of Mendel’s laws The basic principles underlying maize breeding, i.e., that inbreeding reduces vigor, cross-breeding increases vigor, hy- brids could be produced by detasseling one parent, and that hybridization needed

to be done each generation if vigor was to be maintained, were known prior to 1900 (Zirkle, 1952)

With the rediscovery of Mendel’s laws, genetic principles began to be applied

to plant breeding Smith (1966) traces the developments from 1901 to 1965, in- cluding developments in statistical theory that had important implications for plant breeders The development of hybrid corn and the principles leading to it have been reviewed extensively (Crabb, 1947; Hayes, 1963; Wallace and Brown, 1956) and will not be reviewed in detail here

Because most of the traits of economic importance are under quantitative ge- netic control, quantitative genetics became an important contributor to plant breed- ing theory

QUANTITATIVE GENETICS AND PLANT BREEDING 3

B QUANTITATIVE GENETICS

Selection for quantitative traits began with the first person to select for produc- tivity of the plants from which seeds were saved for the next generation Howev-

er, the origins of quantitative genetics can be traced to Darwin’s concept of natur-

al selection (Griffing, 1994) Early statistical concepts, such as regression (Galton, 1889) and use of correlation and multiple regression to describe relationships among relatives (Pearson, 1894), were developed prior to rediscovery of Mendel’s laws Griffing (1 994) listed the demonstration of the environmental nature of vari- ation among plants within lines and the genetic nature of variation among lines (Johannsen, 1903, 1909) along with the establishment of the multiple factor hy- pothesis for inheritance of quantitative traits by the experimental studies of Nils- son-Ehle (1909) and East (1910) as keys to demystification of inheritance of quan- titative traits On the theoretical side, the development of the Hardy-Weinberg equilibrium concept demonstrated a mechanism for maintenance of genetic vari- ability in populations The study that formed the basis for most of the theoretical quantitative genetics work to follow was that of Fisher (1918), which showed that biometric results (involving correlations among relatives) could be interpreted in terms of Mendelian inheritance Griffing (1994) traces the history of quantitative genetics in detail A few additional milestones that he identifies include the work

of Cockerham (1954) and Kempthorne (1954) in partitioning epistatic variation and the contributions of Kempthorne (1957) in bringing together and interpreting

in a common statistical genetic language the diverse concepts of prominent statis- tical geneticists

As areas of plant breeding in which they were important are considered, other important steps in the history of quantitative genetics will be reviewed

C USE OF QUANTITATIVE GENETICS IN PLANT BREEDING

Quantitative genetic principles apply to almost any area of plant breeding Breeders recognize the need for more extensive testing for traits of low heritabil- ity than for traits of high heritability They cross good X good, understanding the principle that lines with similar means are likely to differ at fewer loci than dis- similar lines and thus transgressive segregants are more likely to occur However, the formal use of such quantitative genetic techniques as estimation of genetic vari- ances and prediction of genetic gain is rare in most plant breeding programs In this review, each of the steps in a plant breeding program will be examined and the utility of quantitative genetic techniques considered However, before describing the use of these techniques in plant breeding, a brief description of the tools avail- able from quantitative genetics is provided

III TOOLS OF QUANTITATIVE GENETICS

Because quantitative traits are those for which the effects of genotype and en- vironment cannot be readily distinguished, a major contribution of quantitative ge- netic theory was to provide methods for separating genetic effects from environ-

mental effects As a first step, genetic expectations of means and variances were

obtained

Based on the work of Fisher (1918) and the elaborations by Cockerham (1954) and Kempthorne (I 954), procedures for describing genetic variation in a popula- tion were developed These procedures are based on first describing within-locus variation in terms of average effect of substitution of an allele and deviations from that average effect Variation associated with the average effect of substitution is called additive genetic variance and variance associated with deviations is called dominance genetic variance (see Falconer, 1989, for details) Variance associated with interaction among alleles at different loci is termed epistatic genetic variance and can be subdivided into additive X additive, additive X dominance, and dom- inance X dominance variance when two loci are involved When additional loci are involved, higher-order interactions can be described Genetic variance com- ponents can be estimated from covariances between relatives as described by Cockerham ( 1963)

The general procedure for estimating genetic components of variance is to de- vise a mating design that will estimate covariances between relatives (such as the covariance of full-sibs or half-sibs) The mating design is then grown in an envi- ronmental design The environmental design includes the choice of environments (usually locations and years) and environmental stresses (such as plant population, irrigation or lack thereof, fertility levels, etc.) as well as the experimental design (such as a randomized complete block, incomplete block, or other type of design) From the appropriate analysis of variance, design components of variance are es- timated and equated to covariances between relatives Estimates of covariances between relatives are then equated to expected genetic variance components and genetic variances are estimated (Cockerham, 1963) Such estimates have limita- tions Assumptions usually include linkage equilibrium in the population from which the parents of the mating design were obtained and negligible higher-order epistatic effects The epistatic effects assumed negligible vary with the mating de- sign, e.g., if only one covariance between relatives, such as half-sibs, is estimat-

ed, then all epistatic effects are assumed negligible if the covariance of half-sibs

is assumed to be an estimate of a portion of the additive genetic variance

QUANTITATIVE GENETICS AND PLANT BREEDING 5

As will be discussed later, estimates of genetic variance components can be used

to predict gain from selection (thus allowing comparisons among breeding meth- ods), determine degree of dominance for genes controlling quantitative traits, and compare heritability of different traits

B DESCRIPTION OF ENVIRONMENTAL VARZATION

For any plant breeding program to be successful, the environments in which the cultivars being developed are to be grown must be defined Selection is then con- centrated on developing cultivars that can take maximum advantage of that envi- ronment The one factor that dictates extensive, expensive testing of genotypes in

a plant breeding program is the existence of genotype-environment interaction

(GXE)

Four aspects of GXE need to be considered First, does GXE exist? Comstock

and Moll (1963) described in detail methods of estimating GXE components of variance and detecting the existence of GXE Second, if GXE does exist, are geno-

types ranked the same in different environments? If GXE effects are significant

because of differences in magnitude of differences between genotypes in different environments (non-crossover interaction) rather than differences in ranking of genotypes between environments (crossover interactions), then the GXE effects

are of little consequence to the breeder An extensive discussion of methods of measuring the importance of crossover and non-crossover interaction effects is given by Baker (1988) Third, which genotypes respond most favorably to changes

in environment? Regression of performance of a genotype on the average perfor- mance of a set of genotypes in an environment (Finlay and Wilkinson, 1963; Eber- hart and Russell, 1966) has been used to identify genotypes that respond favorably

to environments or that do not respond to increased environmental inputs Detailed

discussion is found in Lin et al ( 1 986) and Romagosa and Fox (1993) Fourth,

measures of GXE have been used to define geographic regions with similar envi-

ronments in order to identify areas in which test sites should be located (Ouyang

et al., 1995) Clustering procedures described by Ouyang et al., emphasize de-

tecting crossover interaction and allow computation of distances between envi- ronments for unbalanced or missing data

Although the procedures used for dealing with GXE are primarily statistical, the

traits being considered are quantitative and the genetic constitution of the entries being evaluated affects the results For example, Eberhart and Russell (1969) de- termined single crosses were, on average, less stable than double crosses How- ever, they found individual single crosses that were as stable as most double crosses The removal of GXE variance from estimates of genetic variance is an in-

tegral part of any attempt to estimate genetic variances for prediction of gain from selection Choice of environments for such a study is also critical A symposium

volume edited by Kang (1990) provides a detailed look at the interrelationships of GXE and plant breeding

One of the major contributions of quantitative genetics to plant breeding was the development of an equation for predicting gain from selection Griffing (1994) reviews the historical development of the prediction equation beginning with Fish- er’s ( I9 18) consideration of the ratios of U;/CT~ and as measuring the rela- tive importance of additive genetic and dominance contributions to correlation analysis Wright ( 1 92 1) originated the concept of broad-sense heritability and Lush (1935), using Fisher’s least squares gene model, partitioned the hereditary contribution into additive and nonadditive portions From this work came the con- cept of the ratio of ui/ug as a measure of heritability in the narrow sense A de- tailed discussion of the estimation of heritability is given by Nyquist (1991)

In its simplest form, the predicted gain equation has been expressed as R =

ia,@r,, which can be recast as R = ihiu,, where R is response to selection, i is the standardized selection differential, and h i is narrow-sense heritability This ex- pression assumes selection based on phenotype of individuals and recombination

of selected individuals However, there are a number of factors in plant breeding programs that complicate this simple expression Hallauer and Miranda ( 1988),

Empig et al (1972), and Nyquist (1 99 1) explore these factors in detail Because

selection in plant breeding programs is based on progenies and these progenies vary in the types and proportions of genetic variance expressed, the appropriate types of genetic variance to be included in the numerator of the selection equation vary In addition, the estimate of phenotypic variance to be included in the de- nominator varies with the experimental and environmental designs used The ba- sis for comparison of results from the prediction equation may also vary For ex- ample, selection procedures may be compared on either a per year or a per cycle basis Finally, the choice of whether recombination is such that selection is based

on both the male and female parents of the next generation or only on one sex will play a role in progress from selection

Given the factors mentioned in the preceding paragraph, a generalized predic- tion equation for gain per year can be written as follows (Empig et al., 1972):

where c is a pollen control factor (i if selection is after pollination, 1 if selection

is prior to pollination, and 2 if selfed progenies are recombined), y is the number

of years per cycle, i is the selection differential expressed as number of up, si is

the appropriate genetic variance for the type of selection being practiced, and a,,

is the appropriate phenotypic standard deviation for the progenies being evaluat-

QUANTITATIVE GENETICS AND PLANT BREEDING

ed in the selection program If comparisons on a per cycle basis are desired, then

y can be set as 1 for all types of selection being compared This equation is criti- cal for comparing selection procedures Examples of its use are given by Hallauer and Miranda (1 988) and Fehr (1987)

D CORRELATED RESPONSE EQUATION

When selection is applied by plant breeders, changes are likely to occur, not only

in the trait for which selection is being practiced but in other traits as well (corre- lated response) The extent of correlated response is a function of the heritabilities

of the primary and correlated traits, as well as the genetic correlation between the traits Falconer ( 1989) presents the correlated response equation as

CRY = ih,$iyrAupy,

where CRY is the correlated response in trait Y when selection is based on trait X,

i is the standardized selection differential for X , h, and h,, are the square roots of

heritability of traits X and Y, respectively, rA is the additive genetic correlation be-

tween X and Y and uPy is the appropriate phenotypic standard deviation for I: Mul-

tiplying CRY by c/y generalizes the equation to a form corresponding to Eq ( 1 )

Hallauer and Miranda (1 988) describe calculation of genetic correlations Equa- tion (2) becomes important not only in determining the type of correlated response that may occur under selection but also in determining effectiveness of indirect se- lection If rAhx > hy then indirect selection for X will be more effective than di- rect selection for Y, all other factors being equal If, in addition, selection for X al- lows progress in an environment where Y cannot be measured, as may be true for marker-assisted selection, then additional benefits accrue from indirect selection

E MULTIPLE TRAIT SELECTION INDEX

The cultivars arising from plant breeding programs must satisfy a number of cri- teria to be useful For example, a high yielding cultivar susceptible to a prevalent disease would be of little use to a grower, Thus, plant breeders must select for a number of traits Three general procedures-tandem selection, independent culling levels, and index selection-have been used to approach the question of simultaneous improvement of a population for multiple traits (Falconer, 1989) A

number of forms of the equation for gain from index selection for multiple traits are available Smith (1936) was the first to present the concept of index selection Smith presented an index of the form:

I = b,X, + b2X2 + b,X,,

where I is an index of merit of an individual and 6, 6 , are weights assigned to phenotypic trait measurements represented as X, X, The b values are the prod- uct of the inverse of the phenotypic variance-covariance matrix, the genotypic variance-covariance matrix, and a vector of economic weights, A number of vari- ations of this index, most changing the manner of computing the b values, have been developed These include the base index of Williams (1962), the desired gain index of Pesek and Baker (1969), and retrospective indexes proposed by Johnson

et al (1988) and Bemardo (1991) The emphasis in the retrospective index devel- opments is on quantifying the knowledge experienced breeders have obtained Al- though breeders may not use a formal selection index in making selections, every breeder either consciously or unconsciously assigns weights to different traits when making selections

F MOLECULARMARKERS

Although molecular markers are not a direct product of quantitative genetics, the explosion of interest in their use in plants is in large part because of the impli- cations they have for helping solve problems that are common to quantitative ge- netics and plant breeding The use of markers as a potential aid in selection dates back to Sax (1923) who found seed color related to seed size in beans Stuber and Edwards (1986) pioneered the use of molecular markers in plant breeding with work based on isozymes Stuber (1992) reviewed this work The use of markers for selection in plant breeding programs is the application of a form of indirect se- lection The use of markers to manipulate genes was reviewed in detail by Dudley (1993) Lee (1995) gave a comprehensive review of use of molecular markers in plant breeding The availability of molecular markers provides an additional di- mension to the use of quantitative genetics in plant breeding Potential applica- tions of molecular markers include marker-assisted selection, identification of the number of genes controlling quantitative traits, grouping germ plasm into related groups, selection of parents, and marker-assisted backcrossing

G GENERATION MEAN ANALYSIS

The broad area of generation mean analysis is summarized by Mather and Jinks (1982) In essence, the procedure expresses the means of generations derived from the cross between homozygous lines in genetic terms The generation means are then analyzed to estimate additive, dominance, and epistatic effects The reference population is either the F, mean or the mean of homozygous lines resulting from selfing the F, Procedures for estimating the number of effective factors affecting

a particular trait in the cross being studied are provided One of the major limita-

QUANTITATIVE GENETICS AND PLANT BREEDING 9 tions of the procedure is the assumption that, for the trait being studied, one par- ent contains all the favorable alleles and the other all the unfavorable alleles at seg- regating loci The procedure has found a great deal of use in studying genetics of disease resistance (Campbell and White, 1995; Carson and Hooker, 1981; Moll et

al., 1963) An advantage cited by those using it is that the progenies used to de-

termine segregation for single genes can also be used for generation mean analy- sis In addition, means are less variable than variances

Iv APPLICATION OF QUANTITATIVE GENETICS

T O PLAN" BREEDING

Plant breeding consists of selection of parents, crossing those parents to create genetic variability, selection of elite types, and synthesis of a stable cultivar from the elite selections Quantitative genetic principles play a role at each of these stages In this section, the role of quantitative genetics in each of these stages of the plant breeding process is considered

A CHOICE OF PARENTS

The choice of parental germ plasm with which to begin a breeding program is the most important decision a breeder makes However, it is only relatively re- cently that quantitative genetic theory has been applied to this question

1 Self-Pollinated Crops

Discussion of choice of parents in self-pollinated crops will be in the context of selecting parents from which selfed lines will be derived using a pedigree system, single-seed descent, or some other method of deriving inbreds In self-pollinated species, these lines usually are evaluated for their per se performance In cross- pollinated species, in which hybrids are the end product, similar breeding proce- dures are used with the exception that the end product will be a hybrid Thus, the criterion for selection is combining ability of some form rather than line per se per- formance

The objective when choosing parents is to maximize the probability of gener- ating new lines that will perform better than the best pure line currently in use The parents chosen should generate a population for selection that will meet the crite- rion of usefulness described by Schnell (1983) as discussed in Lamkey et al (1995) Usefulness of a segregating population was described by Schnell as the mean of the upper a% of the distribution expected from the population Mathe-

matically, U(a) = Y 2 AG(a), where U(a) is usefulness, Y is the mean of the un- selected population, and AG(a) is gain from selection This statistic takes into ac- count both the mean and the genetic variability, thus emphasizing a basic axiom

in plant breeding: Both a high mean and adequate genetic variability are needed

to produce a superior cultivar

Another basic principle of plant breeding is to cross good x good to obtain some- thing better The quantitative genetic basis for this axiom was demonstrated by Bailey and Comstock ( 1976) Their results demonstrated, based on probability the-

ory and computer simulation results, the importance of each parent contributing favorable alleles from nearly equal numbers of loci that are segregating in the cross Their results can be illustrated by considering 60 loci segregating in an F, With no selection, the probability of a line having >39 loci fixed at homozygosity

would be 0.0067, whereas the probability of a line having greater than 30 loci fixed

would be 0.4487 Thus, if each parent line contributed favorable alleles at 30 loci,

the probability of obtaining a line with a higher number of loci fixed with favor- able alleles than the better parent would be relatively large However, if one par-

ent contributed favorable alleles at 40 loci and the other at only 20, the probabili-

ty of obtaining a new line better than the better parent would be small

Dudley (1 982) suggested backcrossing one or more times to the superior parent

if one parent was much superior to the other The number of backcrosses needed de- pended on the relative number of favorable alleles coming from each parent-the greater the divergence between parents, the more backcrossing would be needed Given the criteria of a high mean and relatively high genetic variance, what tools are available to a breeder to identify parents that will provide segregating genera- tions with these characteristics? Baker (1984) reviewed this question in light of a

paper by Busch et al (1974) who evaluated F4 and F, bulk populations, random

F,-derived F5 and F, lines, and midparent values as predictors of cross perfor-

mance Baker suggests any of these methods should be useful predictors of the mean performance of lines from an F, with the caution that midparent values might

be the weakest of the methods Toledo (1992) found use of the midparent value and the inverse of Malecot’s coefficient of parentage to be effective in selecting

crosses that would produce superior lines in soybeans (Glycine m a L., Merrill) Panter and Allen (1995) suggested using best linear unbiased prediction (BLUP) methods to predict the midparent value of soybean crosses BLUP methods take into consideration the performance of lines related to the line for which perfor- mance is being predicted They concluded BLUP had advantages over least squares estimates of midparent values They found a correlation of -0.47 between coefficient of parentage and genetic variance in progeny Based on these results, they suggested that an effective method of choosing parents would be to identify pairs of lines with high midparent values estimated from BLUP and to select among such pairs those which were the most genetically diverse based on the ge-

QUANTITATrVE GENETICS AND PLANT BREEDING 11 netic relationship matrix Their suggestion is supported by the results of Toledo (1992) With the availability of genetic markers, degree of relationship between lines can be established from molecular marker data (Lee, 1995) This provides an alternative method of determining relatedness when pedigree information is un- available or of uncertain accuracy

2 Cross-Pollinated Crops (Hybrid Cultivars)

For development of hybrid cultivars, there are two aspects to the choice of parents: (i) choice of parents to cross to form base populations for selfing, and (ii) choice of parents to form a cultivar for use by farmers These two aspects will

be addressed separately

a Choice of Parents to Form Base Populations

Conceptually, the problem of developing improved inbreds for use in hybrids is one of adding favorable alleles from a donor source to an elite inbred without ma- terially reducing the frequency of favorable alleles already present in the elite in- bred (Dudley, 1982) The basic question in choosing parents is identification of those lines or populations that contain favorable alleles not present in a hybrid be- ing improved Dudley ( 1984a) framed the following questions relative to choice

of parents for a hybrid corn breeding program: Which hybrid should be improved? Which lines should be chosen as donors to improve the target hybrid? Which par- ent of the target hybrid should be improved? Should selfing begin in the F, or should backcrossing be used prior to selfing?

Procedures for answering these questions were developed based on the concept

of classes of loci This concept was first explored in Dudley (1982) The basic con- cept assumes that for any pair of lines the loci at which the lines differ for a given trait can be divided into two classes: those loci for which P, contains favorable al- leles and P, does not and those for which P, contains favorable alleles and P, does not When a donor inbred is considered, eight classes of loci exist as illustrated in Table 1 Of critical interest is the class of loci for which the donor contains favor- able alleles and both parents of the target hybrid have unfavorable alleles Using this concept, methods of identifying donors with the greatest numbers of such loci were devised for cases in which the donor was an inbred or a population (Dudley, 1984b,c, 1987a,b) Modifications of these methods were proposed by Gerloff and Smith (1988), Bernard0 (1990a,b), and Metz (1994) Evidence for their effective- ness in selecting superior parents and identifying heterotic relationships was pre- sented by Dudley (1988), Misevic (1989), Zanoni and Dudley (1989), Pfarr and Lamkey (1992), and Hogan and Dudley (1991) These methods are beginning to

be used in commercial breeding programs in corn and sorghum [Sorghum bicolor (L.) Moench]

Table I Genotypes for the Classes of Loci Possible for

the Parents of a Hybrid to Improve (P, and Pz)

and a Donor Inbred (PJ

++

_ _ _ _ _ _ _ _ _ _

a + + , The line is homozygous for the dominant fa- vorable allele; - -, homozygous for the recessive unfa- vorable allele

b Choice of Parents of a Hybrid Cultivar

Choice of parents to produce a cultivar directly is usually the result of extensive testing of a number of combinations of potential parents One of the major prob- lems facing breeders is reducing the number of possible hybrids to be tested to a reasonable number In general, breeders work with heterotic groups and crosses likely to be successful as cultivars are usually between inbreds from different het- erotic groups (Hallauer eral., 1988) However, even if breeding is restricted to two heterotic groups, thousands of potential hybrids are possible

Bernardo (1994) proposed applying BLUP to this problem In this procedure, information on hybrid performance of a subset of lines is combined with infor- mation on genetic relationship between the lines tested and an untested set of lines

to predict the performance of untested hybrids This procedure has been widely used in dairy cattle breeding (Henderson, 1988) Bernardo (1994), using a limited number of hybrids, found correlations between observed and predicted perfor- mance ranging from 0.65 to 0.80 He compared RFLP-based estimates of rela- tionship with pedigree-based estimates and found higher correlations for the RFLP-based estimates In a study (Bernardo, 1996) involving 600 inbreds and

4099 tested single crosses, correlations between predicted and observed yields ranged from 0.426 to 0.762 Bernardo concluded BLUP was useful for routine identification of single crosses prior to testing

QUANTITATIVE GENETICS AND PLANT BREEDING 1 3

3 Cross-Pollinated Crops (Synthetic Cultivars)

The mean of a synthetic is,a function of the mean of all possible crosses among parents and inbreeding depression (Hallauer and Miranda, 1988) Predicted mean

of a synthetic is given by Wright’s equation Y2 = Y, - (Y, - Yo)/n, where Y2 is

the predicted mean of the synthetic, Y, is the average performance of all possible single crosses among the parents, and Yo is the mean of the parental inbreds used

to produce the synthetic A general formula for predicting yield of synthetics that considered the frequency of selfing, the number of parents, the coefficient of parentage of the parents, and ploidy level was given by Busbice (1970)

4 Role of Molecular Marker Technology

Use of molecular markers to determine relationships among potential parents has been proposed in a number of species (see Lee, 1995, for a review) Such in- formation is useful for assigning inbreds to heterotic groups in hybrid breeding programs (Mumm and Dudley, 1994) Marker-based relationships could also be substituted for pedigree-based relationships using the methods proposed by Pan- ter and Allen ( I 995) and Toledo (1 992) for predicting genetic variability in cross-

es between homozygous lines Bernard0 (1994) suggested using genetic relation- ships based on molecular marker information and BLUP methodology to predict performance of untested hybrids

B SELECTION DURING INBREEDING

Comstock (1978) suggested that development of a theoretical basis for com- paring breeding methods was one of the most significant contributions of quanti- tative genetics to maize breeding Baker (1984) suggested this statement could be extended to all economically important crops Because breeding procedures are similar for both self- and cross-pollinated crops, discussion of application of quan- titative genetics to selection procedures will be divided into selection during in-

breeding and recurrent selection procedures As Hallauer et a/.( 1988) point out, the methods used to select during inbreeding and recurrent selection procedures are complementary parts of a breeding program In fact, because one result of se- lection during inbreeding is the development of improved lines that are then crossed and another round of selection carried out, selection during inbreeding is one form of recurrent selection

Two major questions exist relative to selection during inbreeding First, how should resources be divided between number of crosses to be evaluated and num- ber of plants or lines to sample per cross? Second, at what stage in the inbreeding

process should replicated testing for yield and other traits of low heritability begin?

Baker (1984) considered application of quantitative genetics to the question of

the optimum allocation of resources to selection among crosses versus selection within crosses Optimum allocation of resources was a function of among and within cross heritabilities and additive genetic variances With a fixed number of plots, the optimum proportion of lineskross to crosses varied with heritability Al- though the equations presented by Baker provided insights into the problem of al- location of resources, he concluded there was a lack of objective criteria for de- termining the appropriate number of crosses to evaluate

The appropriate selfing generation in which to begin testing for yield is a major question in any breeding program from which inbreds are to be produced In species in which cultivars are inbreds, testing is for line per se performance In species in which hybrids are to be produced, testing is for combining ability The two cases will be considered separately

1 Line per se Performance

As inbreeding progresses, variability among lines increases and variability

within lines decreases (Hallauer and Miranda, 1988) This is a basic principle of

quantitative genetics An application of this principle to breeding of self-pollinat-

ed crops that had major impact was development of the modified pedigree (single-

seed descent) method This procedure was proposed by Goulden (1941) and its ad- vantages in quantitative genetic terms were detailed by Brim (1966) Brim noted

most genetic variance in soybeans was additive Thus, means did not change dur- ing selfing generations Furthermore, variance among lines increased with in- breeding and an advantage in terms of gain from selection almost always occurred when selection was delayed to at least the F, and often to the F4 The advantage was particularly apparent when selfing generations could be advanced rapidly in the off-season The extent of use of single-seed descent or a modification thereof

varies with the species In soybean [Glycine max (L.) Merrill], single-seed descent

procedures are used extensively (Fehr, 1987), but less extensive use has been made

in winter wheat (Allan, 1987)

A breeding method related to the single-seed descent method is the use of dou- bled haploids In this procedure, homozygous lines are produced by doubling hap- loid plants arising from gametes, thus reducing the time required to obtain homozy-

gous lines Choo et al (1985) cite empirical results indicating similar efficiencies for

the two methods The most extensive use of this procedure has been in barley Work

on doubled haploids in maize was discussed by Chase (1974) Both single-seed de-

scent and doubled haploid procedures assume that gains from early generation test- ing are offset by the increased gain from selection among homozygous lines and the reduced time necessary to obtain homozygous lines using these procedures

QUANTITATIVE GENETICS AND PLANT BREEDING 15

2 Combining Ability

Early in the development of hybrid corn, the importance of testing for combin- ing ability was recognized The correlations between inbred traits and hybrid per- formance were generally low and not predictive of hybrid performance (Hallauer

et al., 1988) Thus, some method of measuring the value of lines in hybrid com- bination was needed Smith (1986) presented the theoretical basis for the correla- tion between testcross and per se performance His computer simulation results suggested that for traits conditioned by a large number of genes showing complete dominance, correlations between line per se performance and testcross perfor- mance are expected to be less than 0.5

Two major decisions, which can be approached from a quantitative genetics per- spective, exist First, what tester should be used? Second, when should testing be- gin? The principles related to the second question are the same as those for early generation testing when the objective is a pure line That is, as inbreeding advances testcross variation increases among lines and decreases within lines

a Choice of Tester

A major step in evaluating the type of tester to be used was the development of the concept of general and specific combining ability (Sprague and Tatum, 1942) This work supported use of a broadbase tester for preliminary screening for gen- eral combining ability, followed by testing in specific combinations One method

of evaluating for specific combining ability was use of a diallel cross Griffing (1994) reviews the development of the analysis of the diallel cross Griffing (1956) provided clear statements of methods of analysis of diallel crosses in terms of gen- eral and specific combining ability and the circumstances in which each method

of analysis should be used Hallauer and Miranda (1988) review the use of dial- lels in corn breeding

The choice of a tester to use in a hybrid breeding program is dictated by the ob- jectives of the program and the type of gene action controlling the traits of inter- est If the objective is to improve population per se performance, then the tester should be one that has a low frequency of favorable alleles at the loci for which the population needs improvement If additive gene action is of primary impor- tance, then any tester will be effective However, if dominance, partial dominance,

or overdominance are important the tester should be one that has a high frequen-

cy of recessive alleles at loci for which improvement is needed Mathematically, this can be seen from the expression for genetic variance among testcross means for a single locus presented by Homer et al (1969):

(3)

where p and 4 are frequencies of favorable and unfavorable alleles, respectively,

in the population of lines being tested, F is the inbreeding coefficient of the lines

uT$ = 0.5pq( 1 + F)[a + d(Q - P)I2

being tested, a is half the difference between homozygotes, d is the deviation of the heterozygote value from the midparent, and P and Q are frequencies of favor- able and unfavorable alleles, respectively, in the tester If the tester is homozygous, then either P or Q = 1 Several points are apparent from this equation If d = 0, i.e., there is no dominance, gene frequency in the tester does not affect uTz and any tester will be satisfactory If dominance exists, then the higher the frequency

of the recessive allele in the tester, the higher the testcross variance Likewise, the greater the inbreeding of the lines being tested, the greater the testcross variance

Thus, with complete dominance maximum uTz will occur when the tester is

homozygous recessive and the lines being tested are homozygous

Because interest is in increasing frequencies of favorable alleles at loci where the line to be used in combination with the line being developed has recessive al- leles, the tester should be closely related to the line to be used in the ultimate hy- brid This minimizes genetic variability in testcross progeny at loci that do not need improvement and allows increased gain in gene frequency at important loci These concepts support the generally accepted practice of identifying heterotic groups

and selecting testers from an opposite heterotic group (see Hallauer, et al., 1988,

for a discussion of heterotic groups) Extensive experimental data support the theory behind choice of tester (Hallauer and Lopez-Perez, 1979)

b Early vs Late Testing

The question of when to begin testing for combining ability was hotly debated

in the early days of corn breeding The principle of increased variance between lines and decreased variance within lines as inbreeding progressed applies here as well as in development of inbreds for use as lines, per se Jenkins (1935) and Sprague (1946) concluded that high-combining lines could be identified by test- ing early in the inbreeding process and at least half of them could be discarded, thus allowing more effort to be placed on testing the remaining lines later in the inbreeding process Richey (1944) eloquently stated the case for selection for line per se performance prior to selecting for combining ability in a poem (to this au- thor’s knowledge, the only poem ever published in Agronomy Journal)

Bemardo (1 992) developed theory for the genetic and phenotypic correlations between testcross values of lines tested in a given selfed generation and their self-

ed progeny As selfing advances, the correlation increases Bemardo showed the genetic correlation between lines in different generations to be [( 1 + Fn)/( 1 + F,,)]

where F,, and F,,, are inbreeding coefficients in generations n and n’ Heritability

of testcross means also affect the correlation between early generation phenotyp-

ic values and expected genetic values of progeny Based on theory and simulation

results, Bemardo suggested saving approximately 25% of lines based on S , or S,

testing if heritability is 0.25 or 0.5 in the S, generation He also presented tables showing the probability of retaining lines in the upper a% of a distribution of ho-

mozygous lines given that a line selected in a preceding generation ( S n ) was in the

QUANTITATIVE GENETICS AND P L m r BREEDING 17 upper a% of lines in the S,, generation Empirical results previously published by Jensen et al ( 1 983) agreed with these results Hallauer and Miranda (1988) pro-

vide an extensive review of the literature dealing with early testing in corn In gen- eral, most corn breeders use some form of early testing (Bauman, 1981)

The objective of recurrent selection is to increase the frequency of favorable al- leles affecting a trait in order to enhance the value of the population Increased fre- quency of favorable genes is advantageous for either population per se perfor- mance, as in the case of synthetic cultivars, or for inbreeding to produce improved homozygous lines Hallauer (1 985) demonstrated the theoretical advantages of in-

creasing gene frequency prior to selection Mechanically, recurrent selection in- volves repeated cycles of selection and recombination Four major steps include selection of the starting population, development of progenies, evaluation of prog- enies, and recombination of selected individuals The importance of selection of the starting population is detailed under the section on selection of parents Com- parisons among recurrent selection procedures can be made on a theoretical basis

using the prediction Eq (1) Hallauer (1985) details the types of progenies that

may be used and the various forms of recurrent selection and provides examples from a number of species Prediction equations appropriate for a number of dif- ferent recurrent selection procedures are given in Empig er al (1972) and Hallauer

and Miranda (1988)

The development of recurrent selection procedures was given major impetus by the controversy over the genetic causes of heterosis Based on the data that sug- gested early testing should be effective, Jenkins (1940) outlined a procedure that

came to be known as recurrent selection for general combining ability In this pro- cedure, selection was based on half-sib family selection and took advantage of ad- ditive effects Hull (1945) considered overdominance to be of major importance

in controlling grain yield in corn and suggested a recurrent selection scheme us- ing an inbred tester that emphasized specific combining ability and would take ad- vantage of loci showing overdominance Comstock et d (1949) suggested recip-

rocal recurrent selection based on half-sib families to take advantage of both general and specific combining ability The procedure was designed to maximize progress regardless of whether dominance or overdominance was important in hy- brid performance Hallauer and Eberhart ( 1970) outlined reciprocal full-sib selec-

tion, which increased emphasis on nonadditive effects and provided an efficient method of simultaneously improving population cross performance and develop- ing new inbreds Details of these procedures and their use are provided in Hallauer and Miranda (1988)

Recurrent selection principles, developed in cross-pollinated crops, have been

utilized in self-pollinated crops (see Hallauer, 1985, for a review) A major limi- tation is the difficulty of making crosses to provide recombination between cycles Brim and Stuber (1973) outlined a method of using genetic male sterility to facil- itate recurrent selection in soybeans They developed prediction equations for se- lection among and within half-sib families Burton and Carver (1993) compared the effectiveness of S , , selfed half-sib, and selfed full-sib families for recurrent se- lection using male sterile genes in soybeans and wheat The advantage of using selfed half-sib or full-sib families was an increase in the amount of seed available for testing No consistent advantage to using S , families was found Although the quantitative genetic basis for effective use of recurrent selection in self-pollinated species is the same as that for cross-pollinated species and procedures are avail- able for overcoming the difficulties of recombination, use of recurrent selection in self-pollinated species has been limited (Hallauer, 1985)

be greatest when the proportion of the additive variance accounted for by marker effects is greater than the heritability of the trait This suggests selection based on markers has its greatest advantage when heritability of a trait is low However, identification of marker-QTL associations requires precise experiments in which heritability is as high as possible (Dudley, 1993) Thus, maximum benefit from marker-assisted selection may occur when marker-QTL associations are identified under conditions of high heritability and selection is done when the trait of inter- est cannot be measured

In a survey reported by Lee (1993, the most common use of marker-assisted selection was to assist in transferring native monogenic factors or transgenes Al- though the survey did not specifically request the information, Lee concluded that the primary breeding method involved was backcrossing At least seven re- searchers indicated use of markers for transfemng QTL Thus, marker-assisted se- lection is in use in some plant breeding programs

QUANTITATIVE GENETICS AND PLANT BREEDING 19

IN PLANT BREEDING

Predicting the future is a hazardous occupation However, certain aspects are evident The principles of quantitative genetics are an integral part of plant breed- ing and will continue to be for the foreseeable future Thus, training of plant breed- ers will continue to require exposure to quantitative genetic principles and their use in plant breeding programs

During the past several years, the most exciting development related to quanti- tative genetics and plant breeding has been the development and availability of large numbers of molecular markers that allow marking relatively small segments

of chromosome At the same time, transformation procedures that allow the intro- duction into cultivated plants of genes from other species have become available The availability of molecular markers has enabled investigators to attack quanti- tative genetic questions such as number of genes affecting a quantitative trait, the location of such genes, the type of gene action associated with them, the impor- tance of epistasis, and the effect of environment on each gene To date, the tech- nology allows dealing only with chromosome segments and not individual genes, but further advances may allow this type of refinement As transformation be- comes more common, questions such as the importance of genetic background for the introduction of new genes will be important Evaluation of questions such as this will require use of quantitative genetics

Because of the importance of molecular markers, increasing emphasis on link- age and its manipulation will be required both in training of students and in re- search A question of primary interest to plant breeders is how can favorable link- age blocks be held together while introducing new favorable alleles into an existing genotype? Perhaps the combination of molecular marker technology, transformation, quantitative genetics, and the science of plant breeding can com- bine to answer this question

In the future, to perhaps a greater degree than in the past, integration of quanti- tative genetics into plant breeding programs will be a team effort Involved in this effort will be knowledge of molecular biology principles, plant breeding princi- ples, and quantitative genetic expertise This combination of expertise is much more likely to be found in a team, each of whose members is an expert in one or more of these disciplines and can and is willing to communicate with other team members, than in one individual

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pp 1-13 Iowa State College Press,Ames

USE OF ORGANOCLAYS

Shihe Xu,* Guangyao Sheng, and Stephen A Boyd+

Department of Crop and Soil Sciences Michigan State University East Lansing, Michigan 48824

I Introduction

11 Synthesis and Chemical Stability of Organoclays

A Adsorption of Organic Modifiers by Clay Minerals

B Desorption of QACs in Subsoils

C Abiotic Decomposition of the Adsorbed Organic Modifiers

A Sorption of Hydrophobic Organic Contaminants by Organoclays

B Sorption of Ions by Organoclays

C Effect of Sorption on Contaminant Transport

A QAC Adsorption Kinetics

B Modeling Cationic Surfactant Adsorption

C Hydraulic Conductivity of Modified Soil

V Biodegradation of Contaminants in Modified Soils

A Toxicity of QACs to Bacteria

B Bioavailability of Sorbed Contaminants

*Current address: Health and Environmental Sciences, Dow Coming Corporation, Midland, Michi- +To whom correspondence should be addressed

gan 48640-0994

2s

Advancrs in Agronmq, Voiunir f9

surfactant solutions are injected into the subsurface or sprayed onto the surface of contaminated soils at concentrations greater than the critical micelle concentration (CMC) When the surfactant solution percolates through the soil or aquifer mate- rial, organic contaminants (e.g., petroleum hydrocarbons) are solubilized into sur- factant micelles or mobilized by the emulsion The surfactant solution is then pumped out of the soil matrix, and the volatile components are separated from the

aqueous phase, for example, through air striping (Clarke et al., 1991) The non-

volatile contaminants are then separated from the surfactant solution, for example,

by solvent extraction (Gannon et al., 1989) The resultant surfactant solutions are often reused Surfactant-enhanced soil washing/flushing technologies are still in a relatively early stage of development However, dramatic increases (10-100

times) in the efficiency of removing organic contaminants show the potential util- ity of this technology (Wilson and Clarke, 1994; West and Harwell, 1992; Chawla

et al., 1991)

In contrast to soil washing/flushing technologies that seek to mobilize organic

contaminants, the second type of application attempts to use surfactants to immo- bilize hydrophobic organic contaminants dissolved in water The materials utilized

in these applications are cationic surfactants, which are combined with alumi- nosilicate clays to form organoclays Naturally occurring clay minerals do not ef- fectively sorb most hydrophobic organic compounds This is due to the hydration

of native inorganic exchangeable ions of clays that creates a hydrophilic environ- ment at the clay surfaces Replacing the strongly hydrated native inorganic ex- changeable ions with organic cations, e.g., cationic surfactants such as quaternary ammonium compounds (QACs), may change the clay surfaces from hydrophilic

to organophilic The resultant organoclays have greatly enhanced sorptive capa- bilities for a variety of organic contaminants In a similar application, anion sur- factants such as sodium dodecyl sulfate (SDS) are used to replace the native ex- changeable anions on iron and aluminum oxides (Park and Jaffi, 1993,1995) SDS

adsorbed on oxide surfaces forms hemimicelles (Fuerstenau, 1970) that substan- tially enhance the capability of oxides to sorb hydrophobic organic compounds from water via partitioning into the hemimicelles The primary application of such modified oxides is water treatment An interesting point is that some iron oxides (e.g., magnetite and maghemite) are magnetic and thus SDS-treated iron oxides can

be separated from water or soil suspension with magnets (Park and Jaffi, 1995) Organoclays are produced by replacing the exchangeable inorganic cations on layer silicates with organic cations such as quaternary ammonium (Boyd et al.,

1988b, 1991), phosphonium (Kukkadapu and Boyd, 1995), and alkylpyridinium

(Wagner et al., 1994) compounds The resultant organoclays can have vastly im-

proved and unique sorptive properties toward organic contaminants, depending on the nature of both organic cations and the types of layer silicates used Important-

ly, organoclays have potential of being used both ex situ and in situ For example, organoclays can be used in place of or in conjunction with activated carbon for wa-

USE OF ORGANOCLAYS IN POLLUTION ABATEMENT 27

ter purification (Beall, 1985) The use of organoclays as landfill liner components may decrease the transport of organic compounds through the liner, reducing the potential of contamination (Smith and Jafft5, 1994a)

Perhaps the most unique feature and important advantage of this chemistry is

that it can be applied in situ Subsoils and aquifer materials contain negatively charged clay minerals and hence possess a cation exchange capacity (CEC) In ear-

lier research, we demonstrated that sorption of common organic groundwater con- taminants by aquifer materials or soils can be increased by at least two orders of

magnitude by using cationic surfactants to convert soil clays into sorptive organ-

oclays (Boyd et al., 1988a, 1991; Lee et al., 1989a) These results suggested the

possibility that aquifer materials or subsoils could be modified in situ via injec-

tions of cationic surfactant solutions, and the modified soil materials could func- tion as “sorptive zones.” Such sorptive zones, if properly placed, could intercept and immobilize contaminant plumes containing dissolved organic chemicals as shown schematically in Fig 1 The immobilized contaminants could then be detoxified by various chemical or biological means, as for example, through bioremediation using native microbial populations or introduced organisms Con- taining contaminant migration in this fashion has the important advantages of

preventing further downgradient aquifer contamination and of concentrating con-

taminants in a defined zone that can be managed to enhance remediation For ex-

Figure 1 Schematic of proposed in siru modification of aquifer material to create contaminant sorp-

tion zone and coupled sorption and biodegradation of organic contaminants for groundwater cleanup