Elemental Composition of 

Corn Grains, Soybean Seeds, 

Pasture Grasses, and Associated Soils 

from Selected Areas in Missouri 

By JAMES A. ERDMAN, HANSFORD T. SHACKLETTE, and JOHN R. KEITH 

GEOCHEMICAL SURVEY OF MISSOURI 

G E 0 L 0 G I CAL SURVEY P R 0 FE S S I 0 N A L PAPER 954-D 

A study of geochemical variation between four 

vegetation-type areas as indicated by 

analyses of cultivated plants and soils 

UNITED STATES GOVERNMENT PRINTING OFFICE, WASHINGTON 1976 
UNITED STATES DEPARTMENT OF THE INTERIOR 

THOMAS S. KLEPPE, Secretary 

GEOLOGICAL SURVEY 

V. E. :McKelvey, Director 

Library of Congress Cataloging in Publication Data 

Erdman, James A. 

Elemental composition of corn grains, soybean seeds, pasture grasses, and associated soils from selected areas in Missouri. 

(Geochemical survey of Missouri) (Geological Survey Professional Paper 954-D) 

Supt. of Docs. no.: I 19.16:954-D 

1. Soils-Missouri. 2. Agricultural ecology-Missouri. 3. Field crops-Composition. 4. Biogeochemistry-Missouri. 5. Plant-soil 

relationships. 

I. Shacklette, Hansford T., joint author. II. Keith, John R., joint author. Ill. Title: Elemental composition of corn grains, 

soybean seeds ... IV. Series. V. Series: United States Geological Survey Professional Paper 954-D 

S599.M52E7 631.4'9778 75-619451 

For sale by the Superintendent of Documents, U.S. Government Printing Office 

Washington, D.C. 20402 

Stock Number 024-001-02828-0 
CONTENTS 

Page Page 

Abstract ............................................... D1 Methods of sampling plants and soils - Continued 

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Sampling techniques - Continued 

Effects of agricultural operations on natural ecosystems . . . . . . 2 

Description of sampling areas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 

Soils ........................................... D7 

Plants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 

Floodplain Forest . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 

Glaciated Prairie . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 

Unglaciated Prairie. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 

Oak-hickory Forest. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 

Laboratory procedures used . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 

Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 

Geochemical characteristics of cultivated soils. . . . . . . . . . . 10 

Chemical composition of selected crop plants . . . . . . . . . . . . 15 

Correspondence between the elemental composition of 

Methods of sampling plants and soils . . . . . . . . . . . . . . . . . . . . . . . 6 cultivated plants and that of associated soils . . . . . . . . . . 16 

Sampling design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 

Sampling techniques. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 

Summary .............................................. 17 

References cited . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 

ILLUSTRATIONS 

Page 

FIGURE 1. Map showing vegetation-type areas in Missouri, and location of quadrangles in which corn, soybeans, pasture grasses, 

and associated soils were sampled . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . D4 

2. Map showing Missouri crop and livestock reporting districts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 

3. Graphs showing correlations between the log concentrations of selected elements in crops and cultivated soils within 

four vegetation-type areas of Missouri......................... . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 

TABLES 

Page 

TABLE 1. Analytical methods used in this study.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . D8 

2. Approximate lower limits of determination for elements in soils and plant materials. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 

3. Elements commonly looked for, but rarely or never detected, by semiquantitative spectrographic analysis, and 

their approximate lower limits of determination . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 

4. Error variance attributed to laboratory procedures based on duplicate analyses of cultivated soils and crop plants 

from Missouri . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 

5. Components of logarithmic variance estimated for samples of plow zone soils from corn fields in four vegetation-type 

areas in Missouri. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 

6. Components of logarithmic variance estimated for samples of plow zone soils from soybean fields in four vegetationtype areas in Missouri . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 

7. Components of logarithmic variance estimated for samples of plow zone soils from pasture fields in four vegetationtype areas in Missouri . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 

8. Mean chemical composition and chemical variation of cultivated soils from corn fields in four vegetaion-type areas 

in Missouri . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 

9. Mean chemical composition and chemical variation of cultivated soils from soybean fields in four vegetation-type 

areas in Missouri . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 

10. Mean chemical composition and chemical variation of cultivated soils from pasture fields in four vegetation-type 

areas in Missouri . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 

III 
IV CONTENTS 

Page 

TABLE 11. Comparison of mean chemical properties of uncultivated soils and cultivated soils from the Floodplain Forest 

vegetation-type area in Missouri. ........................................... _............................ 16 

12. Components of logarithmic variance estimated for corn grains from four vegetation-type areas in Missouri . . . . . . . . . . . 17 

13. Components of logarithmic variance estimated for soybean seeds from four-vegetation-type areas in Missouri . . . . . . . . 20 

14. Components of logarithmic variance estimated for pasture grasses from four vegetation-type areas in Missouri . . . . . . . 20 

15. Mean chemical composition and chemical variation in the ash of corn grains from four vegetation-type areas in Missouri 21 

16. Mean chemical composition and chemical variation in the ash of soybean seeds from four vegetation-type areas in 

Missouri . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 

17. Mean chemical composition and chemical variation in the ash of pasture grass stems and leaves from four vegetationtype areas in Missouri . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 

18. Correlations between the concentrations of elements in corn grains, soybean seeds, and pasture grasses and in the 

associated cultivated soils from four vegetation-type areas in Missouri....................................... 22 
GEOCHEMICAL SURVEY OF MISSOURI 

ELEMENTAL COMPOSITION OF CORN GRAINS, 

SOYBEAN SEEDS, PASTURE GRASSES, 

AND ASSOCIATED SOILS FROM SELECTED AREAS IN MISSOURI 

By JAMES A. ERDMAN, HANSFORD T. SHACKLETTE, and JOHN R. KEITH 

ABSTRACT 

Plant parts and soils, sampled according to a three-level 

geographically nested design, were analyzed to determine the 

nature of the geographic variation in chemical composition. Only 

about one-half of the soil constituents that were measured 

exhibited significant variation between vegetation-type areas; 

most variation was within these areas and was largely between 

sites within 71

12-minute quadrangles. Soils from the Glaciated 

Prairie tended to be high and those from the Floodplain Forest, 

low, in the concentrations of most elements. Differences in 

concentrations of certain elements in cultivated and uncultivated 

soils suggest that agricultural practices may have caused slight 

element depletion. Almost all the variation in elemental 

composition of plant materials was at the between-site level. For 

the most part, the concentrations of elements in the plant materials 

do not clearly reflect the total elemental compositions of the 

associated soils. 

INTRODUCTION 

Cultivated plants and soils predominate in most 

arable land areas of the central United States, the 

native plants and uncultivated soils generally 

persisting only at locations where steep grades and 

stony, shallow soils make cultivation impractical. A 

study of the geochemical characteristics of these areas 

should include both the cultivated and uncultivated 

plants and soils; however, crop and pasture plants 

now provide the major biogeochemical influence on 

chemical-element cycling and soil development in 

many parts of this country. An earlier geochemical 

study of native plants and uncultivated soils of 

Missouri revealed significant differences in concentrations of many elements in these materials from the six 

vegetation-type areas of the State (Erdman and 

others, 1976). The present geochemical study was 

planned as a second phase of this work, in which the 

effects of abundance of elements in the soil on the 

concentrations of these elements in soybeans, corn 

grains, and pasture grasses could be examined, and 

baseline data on the elemental composition of these 

plant products could be established. 

The scope and general objectives of the Missouri 

geochemical investigations, of which the present 

study is a part, were outlined by U.S. Geological 

Survey (1972a) and by Connor and others (1972), and 

were discussed further by Miesch (1976) and by 

Erdman, Shacklette, and Keith (1976). These reports 

emphasized that these investigations constituted a 

pilot study for the development of methods for 

geochemical surveys of large areas. Particular 

attention was given to the use of efficient methods of 

sampling and sampling design and to the synthesis of 

geochemical data in a rigorous, scientifically 

defensible manner. Special efforts were niade in these 

studies to unify methodology in sampling, chemical 

analysis, statistical evaluation, and data presentation 

for the several disciplines, so that results from each 

study would be comparable with results of the other 

studies, insofar as that would be appropriate. 

Informal collaboration of the U.S. Geological Survey 

projects and the Environmental Health Surveillance 

Center, University of Missouri, was promoted by 

seven semiannual releases of progress reports (U.S. 

Geological Survey, 1972a-f, 1973), which described the 

current status of the geochemical studies and gave 

results of these studies as available. The surveillance 

center was simultaneously conducting e:pidemiological 

studies in Missouri, in the search for possible 

Dl 
D2 GEOCHEMICAL SURVEY OF MISSOURI 

geographical patterns of animal and human health 

problems that might correspond to patterns of 

geochemical abundances in natural materials. In order 

to make our geochemical data readily useful in 

epidemiological and other studies, maps of element 

concentrations at a regional scale for the several 

sampling media were prepared, where possible. 

We are indebted to many U.S. Geological Survey 

colleagues for their assistance during the course of 

this study. A. T. Miesch provided valuable guidance 

both in coordinating the Missouri geochemical studies 

as a whole and in using statistical techniques. 

Josephine G. Boerngen provided technical assistance 

in the computer processing of the data. Chemical 

analyses of plant materials were performed by Thelma 

F. Harms, Harriet G. Neiman, and Clara C. S. Papp. 

The soil samples were analyzed by Leon A. Bradley, 

F. W. Brown, G. T. Burrow, Joseph W. Budinsky, J. 

P. Cahill, I. C. Frost, Johnnie Gardner, B. A. McCall, 

Leung Mei, Violet M. Merritt, Roosevelt Moore, 

Harriet G. Neiman, Ramona L. Rahill, G. D. Shipley, 

M. W. Solt, J. A. Thomas, J. S. Wahlberg, and T. L. 

Yager. We acknowledge with gratitude the facilities 

and services provided by Dr. Carl J. Marienfeld and 

his associates of the Environmental Health 

Surveillance Center, University of Missouri. 

EFFECTS OF AGRICULTURAL OPERATIONS 

ON NATURAL ECOSYSTEMS 

Agricultural operations commonly have a great 

impact on soil-plant relationships when natural 

ecosystems are changed to artificial ones. Tillage 

changes the structure of soils by altering the natural 

soil horizons within the plow zone (generally 6-8 inches 

(15-20 em) thick); it mixes surface materials, including 

vegetation, throughout the cultivated profile. This 

mixing affects element mobility through changes in 

soil-moisture relationships and aeration, and in 

chemical interactions among the materials. Less 

weathered minerals may be brought to the surface 

where oxidation and thermal alteration are 

accelerated. 

Microbial communities react to the altered soil 

profile by changes in population numbers and species 

composition, often with the result that the more 

chemically active microfloral populations increase and 

the microfauna! populations decrease. With proper 

management practices, tillage tends to improve the 

fertility of soils-that is, the ability of soils to produce 

economically important plants. Improperly managed 

tillage may lead to excessive erosion and leaching, by 

which essential chemicals are lost from the plow zone, 

or to compaction and hardpan formation, which 

interfere with the drainage and aeration that are 

essential for high crop yields. 

The effects of other practices are superimposed on 

the effects of tillage in the agricultural system. 

Manufactured fertilizers add nutritive chemical 

elements (principally nitrogen, phosphorus, and 

potassium), commonly along with other elements 

found in materials that are included as fillers in the 

fertilizer. Natural fertilizers (manures and composts) 

contain, in addition to essential elements, organic 

materials that alter soil texture and may greatly 

influence the action of soil micro-organisms. 

Agricultural lime that is used to reduce soil acidity, to 

hold phosphate fertilizers in a form more available to 

plants and to improve soil structure, also affects the 

availability of certain elements to plants and therefore 

influences element cycling. The application of 

pesticides to crop plants provides an additional supply 

of chemical elements to agricultural soils, although 

because of the controls now in effect on the 

composition of the pesticides, the present addition is 

probably small. 

Crop plants are, in general, herbaceous annuals and 

therefore promote element cycling that is rapid 

compared with that of native vegetation, which is 

composed largely of woody species (trees and shrubs) 

in forested regions and perennial forbs and grasses in 

prairie regions. The annual crop plants generally are 

shallow rooted, and the geochemical cycling they 

promote is most active in the plow zone of soils. In 

contrast, the deep-rooted woody and herbaceous 

perennial species of natural plant communities may 

transport elements to the surface from lower soil 

horizons and from soil parent materials. 

Cultivated plants are ordinarily grown in a 

"monoculture" system-that is, only a single species is 

grown in a field. Accordingly, all plants in the field 

have the same requirements for nutritive elements 

and the same tendency to accept or reject the 

non-nutritive ones. The physiological reactions of this 

monoculture vegetation are locally uniform. This 

uniformity contrasts strongly with the varied 

reactions brought about by the more diverse native 

vegetation. The effects of monoculture on geochemical 

cycling are only slightly diminished by rotation of 

crops in a field, especially if only one annual species is 

alternated with another. Of all agricultural lands, 

pasture land for grazing livestock is probably the least 

affected by cultivation practices. In many farming 

systems, however, pastures are rotated with 

cultivated crops or are fertilized and seeded in a 

manner designed to encourage a monoculture system. 

In agricultural ecosystems, various amounts of 

chemical elements are continually being removed from 
COMPOSITION OF CORN, SOYBEANS, GRASSES, AND ASSOCIATED SOILS D3 

the area through the sale of produce, both vegetable 

and animal. Estimates of the pounds of elements per 

acre removed annually from the soil by crops in a 

standard rotation were given (Utz and others, 1938, p. 

87) as follows: nitrogen, 60 (327 kilograms/hectare); 

phosphorus, 25 (136 kg/ha); potassium, 50 (272 

kg/ha); calcium 30 (164 kg/ha); and magnesium, 20 

(109 kg/ha). The amounts of elements removed 

annually from an acre by the sale of grazing livestock 

doubtless are much less than those removed by the 

sale of plant products, because livestock return much 

of the total consumed elements to the soil in animal 

wastes. To these losses through the sale of produce 

must be added the amount of elements lost through 

erosion and leaching. Utz and others (1938, p. 87) 

reported the following average annual losses (pounds 

per acre) in drainage waters from cultivated silt loam 

that was devoid of vegetation: nitrogen, 69.0 (376 

kg/ha); phosphorus, a trace; potassium, 86.8 (473 

kg/ha); calcium, 557.2 (3,036 kg/ha); and magnesium, 

104.4 (569 kg/ha). 

The agricultural ecosystem was characterized in a 

report of the Workshop on Global Ecological 

Problems, University of Wisconsin (1971, p. 20-21) as 

follows: 

Domestication of animals and selection of crop plants began the 

progressively intensive management of ecosystems which 

culminated in modern industrialized agriculture whose levels of 

production were undreamed of by our ancestors. To maintain this 

system, however, requires an enormous flow of fertilizers to 

replace the plant nutrients taken up by the crops or otherwise lost 

from the soil. It requires an application of pesticides to eliminate 

unwanted weeds and plant-eating insects and a tremendous input 

of fossil fuel energy for the mechanized operations. There is little 

recycling within this system. Man adds phosphorus to the land at a 

rate of over seven million metric tons per year, and all of it is soon 

lost, diluted beyond recovery in soils and sediments. 

Natural ecosystems, in contrast to agricultural 

ecosystems, closely approach a steady state wherein 

input and output of chemical elements are nearly in 

balance. Duvigneaud and Denaeyer-DeSmet (1968) 

reported studies of a natural forest ecosystem in 

Belgium which indicated that only 10 percent or less of 

the nutrient flow depended on inputs through rain and 

snow, and that there were no other sizable inputs. The 

report of the Workshop on Global Ecological 

Problems. University of Wisconsin (1971, p. 101) 

commented on this Belgian study as follows: 

It seems to be a universal condition in such undisturbed forests 

that the mineral nutrients are for the most part bound up in the 

living plants and animals. As a consequence, the recycling is very 

tightly controlled. A forest such ?.s the one in Belgium is then 

almost self-contained, or put another way, it is weakly coupled with 

its external environment. Similar results have been reported for 

the second growth Douglas Fir ecosystem of the Pacific Northwest 

of the U.S.A. 

In view of these great differences in element cycling 

of the two ecosystems, the measurement of the 

differences by means of geochemical studies may seem 

to be possible. However, the reported losses from 

agricultural ecosystems are so small in proportion to 

the total amount present that they may be impossible 

to measure by any practical scheme of sampling and 

laboratory analysis. Furthermore, these losses may be 

balanced by the additions of fertilizers to agricultural 

lands, or reduced by aerial deposition of particulates 

and by soluble elements in precipitation. In a study of 

the geochemistry of Georgia soils, Shacklette, Sauer, 

and Miesch (1970) found that concentrations of many 

elements in samples from two areas of the State 

differed greatly, but that within each area the 

chemical composition of garden soil and uncultivated 

forest soil samples was not different. They concluded 

(p. C35), "The cultivation of garden soils apparently 

has not greatly altered their content of the elements 

that were studied, if j:udged by the concentrations of 

these elements in uncultivated soils." 

DESCRIPTION OF SAMPLING AREAS 

The basis for the sampling plan used in this study 

was the same as that used in the earlier study of 

native plants and uncultivated soils-the delineation 

of vegetation-type areas as modified from Kuchler's 

(1964) map-except that we reduced the vegetationtype areas that were sampled to four (fig. 1). Although 

data were given by Missouri Crop and Livestock 

Reporting Service (1970) on production of corn and 

soybeans in the Oak-hickory-pine Forest and Cedar 

Glade vegetation-type areas, these crops were not 

produced at sites that were characteristic of the 

vegetation-type areas. In the Cedar Glade area, the 

characteristic native plant communities sampled in the 

earlier study occurred on thin, dry soils overlying 

carbonate bedrock of flats, ridges, and slopes. In the 

Oak-hickory-pine Forest area, these plant communities grew only on shallow overdrained soils overlying 

sandstone bedrock of ridges. Both of these kinds of 

sites are not suitable for conversion to agricultural use 

by tillage and consequently, the crops that are grown 

within these two vegetation-type areas occur on valley 

alluvium or, to a lesser extent, on slopes that have 

deeper, more moist soils than those that support cedar 

and pine forests. These two vegetation-type areas, 

therefore, were excluded from the sampling plan for 

cultivated plants and soils. 

A discussion of the original and present natural 

vegetation and soils of the vegetation-type areas in 

Missouri, including the areas sampled in this study, 

was given by Erdman, Shacklette, and Keith (1976); 
D4 GEOCHEMICAL SURVEY OF MISSOURI 

EXPLANATION 

~ Glaciated Prairie 

~ Unglaciated Prairie 

D Oak-hickory Forest 

f::::::::~::~::~:~:~~::::::~1 Oak-hickory-pine Forest 

e Location of sampled 

quadrangle 

FIGURE 1.-Vegetation-type areas in Missouri, and location of 

quadrangles in which corn, soybeans, pasture grasses, and 

associated soils were sampled. The Cedar Glade and 

Oak-hickory-pine Forest areas were not sampled. Map modified 

from Kuchler (1964). 

therefore, only a synopsis of this discussion will be 

presented in the descriptions of sampling areas that 

follow. Statistics of agricultural production in Missouri 

in 1969 that were given by the Missouri Crop and 

Livestock Reporting Service (1970) are used to 

indicate the relative importance, expressed as acres 

devoted to a crop and the yield per acre, of corn and 

soybeans in the four areas that were sampled. 

Statistics for pasture grasses were not given by the 

reporting service; however, the relative importance of 

these grasses among the sampling areas can be 

roughly evaluated from the data that were given on 

hay production, because meadows are often mowed 

for hay or are grown in rotation with other hay crops. 

The Missouri Crop and Livestock Reporting Service 

(1970) divided the State into nine reporting districts, 

as shown in figure 2. Summaries of agricultural 

production by reporting districts were discontinued 

Northwest North Central 

FIGURE 2.-Missouri crop and livestock reporting districts. 

Numbers on the map indicate locations of reporting-district 

offices. From Missouri Crop and Livestock Reporting Service 

(1970). 

(except for beef cattle) after 1969; therefore, crop data 

for 1969 are used in this report, although our sampling 

of the cultivated plants and soils was done in 1971. 

These reporting districts roughly coincide, or can be 

grouped so that their combined areas generally 

coincide, with the vegetation-type areas that were 

sampled. The climatological data were obtained from 

the same reporting service and are based on records of 

the U.S. Environmental Science Services Administration. 

FLOODPLAIN FOREST 

This vegetation-type area in Missouri (fig. 1) 

formerly was densely forested land that was mostly 

swampy. It has since been cleared of timber and 

drained by means of an extensive system of canals and 

ditches, and so now it consists almost entirely of 

highly productive farm land. The remnants of native 

vegetation grow mostly on roadsides and banks of 

drainage streams. The area generally has low relief; 

moreover, some fields have been leveled by machines 

until they are nearly flat. The soil is deep and mostly 

alluvial in origin, and its composition reflects changes 

in the nature of the waterborne deposits with time. 

Consequently, the texture of the surficial layer may 

range from sand to dark organic and clay mixtures 

within the lateral extent of only a few metres. The 

technical classification of soils of the area was given by 

the U.S. Soil Conservation Service (in U.S. Geological 

Survey, _1970, p. 86) as principally Haplaquepts 
COMPOSITION OF CORN, SOYBEANS, GRASSES, AND ASSOCIATED SOILS D5 

(seasonally wet soils with weakly developed horizons, 

with either a light-colored or thin black surface 

horizon) and Hapludalfs (medium to high in bases) 

gray to brown surface horizons with subsurface 

horizons of clay accumulation; generally moist, but 

intermittently dry for short periods in some seasons). 

The total precipitation in 1969 was about 48 inches 

( 122 em). The average temperatures for the coldest 

and warmest months were, respectively, January 

33.3°F (0.7°C) and July 83.2°F (28.4°C). 

The extent of this area closely corresponds to that of 

the southeast agricultural reporting area 9 (fig. 2). 

Production data for this area follow: 

Corn-200,000 acres (80,940 ha); yield per acre, 71.0 

bushels (4,771 kg/ha). 

Soybeans....:...1,329,000 acres (573,846 ha); yield per 

acre, 24.0 bushels (1,613 kg/ha). 

Hay, all kinds-69,000 acres (27,924 ha); yield per 

acre, 1.74 tons (3.90 tonnes/ha). 

GLACIATED PRAmiE 

The pre-settlement vegetation of this area consisted 

of a mosaic of Bluestem Prairie and Oak-hickory 

Forest (KUchler, 1964), but this mosaic has virtually 

disappeared. The prairie soils are mostly under 

cultivation, and the formerly extensive communities 

of grasses and forbs generally occur only along roads 

and fence rows. Most forests are only along streams or 

in isolated upland groves. In both this study and in the 

earlier geochemical study of native vegetation in this 

area, samples were collected at sites that were, or 

now are, typical of the Bluestem Prairie. Some of the 

sampled soils were dark prairie loam, classified by the 

U.S. Soil Conservation Service (in U.S. Geological 

Survey, 1970, p. 86) as Argiudall (black, friable, 

organic-rich surface horizon, high in bases; calcium 

carbonate or gypsum horizons are absent). A second 

soil type sampled was gray-brown podzolic, classified 

as Hapludalf (gray to brown surface horizons, medium 

to high in bases; usually moist, but during the warm 

season may be intermittently dry for short periods; 

with thin subsurface horizon of clay accumulation). A 

third soil of this area was of more limited extent and is 

classified as Albaqualf (medium to high in bases; with 

a bleached upper horizon that changes abruptly in 

texture to an underlying horizon of clay accumulation). 

The total precipitation in 1969 ranged from about 30 

inches (76 em) in the west-central part of the area to 

about 40 inches (102 em) in the eastern part. Average 

temperatures for the coldest and warmest months, 

respectively, were as follows: west-central partJanuary, 23°F (-5°C), July, 79°F (26°C); eastern part 

-January, 22°F (-5.6°C), July, 77°F (25°C). 

This vegetation-type area roughly corresponds to 

the combined areas of the northwest, north-central, 

and northeast agricultlH'al reporting areas 1, 2, and 3, 

respectively (fig. 2). Combined production data for 

these three reporting areas follow: 

Corn-1,380,000 acres (558,486 ha); yield per acre, 

63-81 bushels (4,234-5,443 kg/ha). 

Soybeans-1,390,000 acres (562,533 ha); yield per 

acre, 25-31 bushels (1,680-2,083 kg/ha). 

Hay, all kinds-1,060,000 acres (428,982 ha); yield 

per acre, 1.94-2.32 tons (4.35-5.20 t/ha). 

UNGLACIATED PRAIRIE 

The original vegetation of this area was similar to 

that of the Glaciated Prairie, in that it consisted of a 

mosaic of prairie species and forest species. At 

present most cultivated land of moderate relief 

comprises areas that were primarily vegetated with 

prairie plants, although there is evidence that some 

cultivated land was originally forested. The soils were 

derived from bedrock (largely carbonate rocks) and 

loess deposits. Dark prairie soils predominate in the 

northern third of the area. These soils were classified 

by the U.S. Soil Conservation Service (in U.S. 

Geological Survey, 1970, p. 86) as Hapludoll (nearly 

black, organic-rich surface horizon, high in bases; 

usually moist; not horizon of calcium carbonate or 

gypsum accumulation and no subsurface clay horizon) 

and Argiudoll (similar to Hapludoll, but with a 

subsurface horizon in which clay has accumulated). 

The southern two-thirds of this area is blanketed with 

a gray to brown surface horizon, and the soil is 

classified as Albaqualf (having a bleached upper 

horizon, with an abrupt change in texture to 

underlying horizons of clay accumulation). 

The total precipitation in 1969 was about 51 inches 

(130 em). Average temperatures for the coldest and 

warmest months, respectively, were January, 27°F 

(-2.8°C) and July, 78°F (25.6°C). 

This vegetation-type area approximately corresponds to the western agricultural reporting area 4 

(fig. 2). Production data for this reporting area follow: 

Corn-335,000 acres (135,574 ha); yield per acre~ 71 

bushels (4,771 kg/ha). 

Soybeans-275,000 acres (111,292 ha); yield per 

acre, 28 bushels (1,882 kg/ha). 

Hay, all kinds-305,000 acres (123,434 ha); yield per 

acre, 1.88 tons (4.21 t/ha). 

OAK-IDCKORY FOREST 

This vegetation-type area originally was forested 

with many tree species, several kinds of oaks and 

hickories being most common. Extensions of this 

forest type occur along streams in the prairies (fig. 1); 
D6 GEOCHEMICAL SURVEY OF MISSOURI 

these extensions were not .sampled because the forest 

soil there is generally of alluvial origin and therefore 

not characteristic of this forest type as a whole. Most 

land of low to moderate relief has been cleared of trees 

and is cultivated, except areas where the soil is too 

shallow for tillage. The area is drained by many 

streams that commonly are deeply entrenched, and 

the slopes along the stream banks are forested. Much 

land is devoted to pasture, either in rotation with 

cultivated crops or as permanent pasture on lands that 

are not suited to tillage. The most extensive soils in 

the western and central part of this area are 

red-yellow podzolic soils, classified by the U.S. Soil 

Conservation Service (in U.S. Geological Survey, 

1970, p. 86) as Paleudults (low in bases and organic 

matter; with short or no dry periods during the year; 

with a thick horizon of clay accumulation; and without 

appreciable weatherable minerals). Soils of the 

northeastern part of the area are gray-brown podzolic 

and are classified as Hapludalfs (medium to high in 

bases; brown surface soil, with a subsurface horizon of 

clay accumulation; usually moist during the warm 

season, but may be intermittently dry in some 

horizons for short periods). 

The total precipitation in 1969 ranged from about 35 

inches (89 em) in the western part of the area to 39 

inches (99 em) in the eastern part. Average 

temperatures for the coldest and warmest months 

were as follows: west-central part-January, 33.4°F 

(0.8°C), July, 80.6°C); (27°C) eastern part-January, 

about 30°F (-1.1 °C), July, 78.4°F (25.8°C). 

The major parts of this vegetation-type area correspond, in a very general way, with the combined areas 

of the southwest, central, and eastern agricultural 

reporting areas 7, 5, and 6, respectively (fig. 2). 

Combined production data for these areas follow: 

Corn-658,000 acres (266,293 ha); yield per acre, 

53-70 bushels (3,562-4, 704 kg/ha). 

Soybeans-396,000 acres (160,261 ha); yield per 

acre, 24-28 bushels (1,613-1,882 kg/ha). 

Hay, all kinds-1,060,000 acres (428,982 ha); yield 

per acre, 1.93-2.02 tons (4.33-4.52 5/ha). 

METHODS OF SAMPLING PLANTS AND SOILS 

SAMPLING DESIGN 

The boundaries of the vegetation-type areas that 

were described earlier outline the categories or 

mapped units at which sampling was directed. 

Sampling for the purpose of assessing possible 

differences between these areas constituted stage 1a 

of a general sampling plan for geochemical surveys of 

large regions. The general plan was described by 

Connors and others (1972) and by Miesch (1976). This 

sampling was used to estimate the magnitude of the 

variability in chemical composition of the sampled 

materials at various geographic scales. No sampling of 

the stage 1b or phase 2 types was done. 

The sampling was based on a three-level geographically nested design in which each level is associated 

with a specific range of scales. The top level of this 

design consists of the four vegetation-type areas as 

modified from Kuchler (1964). The two lower levels 

consist, respectively, of 71

/z -minute quadrangles 

within areas and sites within quadrangles. A site was 

defined as an area where separate fields of corn, 

soybeans, and pasture grasses were contiguous or in 

close proximity to each other. A plant and a soil 

sample were collected at each of the three fields at a 

site. The geographic units at the two lower levels 

(quadrangles and sites) were selected for sampling by 

formal randomization procedures, in an attempt to 

reduce sampling bias. 

The general statistical model employed was: 

(1) 

where Xikj represents the concentration of an 

element, or other constituent, reported by the analyst 

in a soil or plant sample at the kth site taken from the 

jth 71/z-minute quadrangle of the ith vegetation-type 

area; and I" is the grand mean concentration of the 

element in the material under study within all four 

areas of the State. ai represents the difference 

between the true mean concentration of an element in 

the ith vegetation-type area and the grand mean, I"; 

~ijrepresents the difference between the true mean 

concentration for the jth quadrangle and the mean of 

the ith vegetation-type area; and Y ijk represents, in 

part, the difference between the element concentration of the sample at the kth site and the mean of the 

jth quadrangle of the area. Included in the last term, 

Y ijk ., are all effects of sample preparation and 

laboratory analysis referred to as "laboratory error." 

The model in equation 1 follows a specific case of the 

analysis of variance termed the hierarchical, or 

"nested" case, discussed in mathematical detail by 

Krumbein and Slack (1956) and described as it applies 

to the Missouri studies by Miesch (1976. The terms a i, 

(3 ij, and Y ijk are assumed to be. random variables with 

means of zero and variances of s&, s $,and s :. The total 

variance of the element x, estimated s&, may be 

partitioned into three components of variance: 

2 2+ 2+ 2 sx = sa s fJ s y, (2) 
COMPOSITION OF CORN, SOYBEANS, GRASSES, AND ASSOCIATED SOILS D7 

where s ti estimates the regional or statewide 

effect- that is, variation between vegetation-type 

areas; s & estimates large-scale geographic variation 

between quadrangles within areas; and s ~ estimates 

small-scale geographic variation between sites within 

quadranges, plus the variance attributable to 

laboratory error. The goal of the sampling is to obtain 

unbiased estimates of these variances. 

With the exception of the silicon and pH data for 

soils, the variance components were estimated on 

logarithmic transforms (base 10) of the data, because 

the concentrations of most elements -particularly the 

trace elements-tended to have marked positive 

skewness in their frequency distributions. 

The sampling design included 4 vegetation-type 

areas, 5 quadrangles from each area, and 2 sites 

within each quadrangle, for a total of 40 sites. Corn, 

soybeans, pasture grasses, and soils associated with 

each of the crops were sampled in separate fields at 

each site, where possible. Quadrangles that 

overlapped two vegetation-type areas about equally 

were excluded from the population of quadrangles 

that was to be sampled. 

All samples were analyzed in a completely and 

formally randomized sequence in order to circumvent 

any effects of systematic variation in laboratory 

analysis. Included in this sequence was a small 

number of duplicate samples used to estimate the 

magnitude of laboratory error. In effect, these 

duplicate analyses constitute a fourth level of the 

sampling design (see the section on laboratory 

procedures). 

Results of the analysis of variance of the soil and 

plant data provided estimates of the three components 

of variation in equation 2: between-vegetation-type 

variance, between-quadrangle variance, and the sum 

of between-site and laboratory variances. These 

components indicate the geographic scale of element 

variation in Missouri crop plants and cultivated soils; 

they may also be used to assess the efficiency of this or 

any other sampling design directed towards 

distinguishing between the geochemical characteristics of the four vegetation-type areas. 

SAMPLING TECHNIQUES 

SOILS 

The plow zone of soils comprises the upper 6 to 8 

inches (15-20 em) of the soil that is tilled and generally 

includes part or all of the original A horizon and part of 

the B horizon. These horizons ordinarily have been so 

thoroughly mixed by successive tillage that their 

identities have been lost. Most soils are more 

compacted just below the plow zone, and at places a 

hardpan has formed that restricts root development of 

most crop plants and retards the downward 

movement of water. The plants sampled in this study 

are fibrous rooted, and their roots are largely 

restricted to the plow zone. Therefore, for the purpose 

of correlating element concentrations in soils and 

plants, only the plow zone soil was sampled. 

Most of the soil samples were collected by digging to 

the bottom of the plow zone, using a hand trowel, and 

taking about 300 to 400 g of soil from points 

throughout the profile. If the soil at the site was dry 

and hard, a clamshell digger was used for sampling. 

Rock fragments larger than about 5 mm, if present, 

were hand culled from the sample, and the soil was put 

in a manila paper envelope and allowed to dry. If 

samples were still moist when received at the 

laboratory, they were dried in a low temperature 

(45°-50°C) oven. The soils were sampled at the same 

sites where the crop and pasture plants were sampled. 

PLANTS 

The randomly selected sampling sites in each of the 

sampled quadrangles were examined for the presence 

of separate fields of corn, soybeans, and pasture 

grasses that were contiguous or in close proximity. 

Where such fields could not be found, other randomly 

selected sites in alternative quadrangles (also 

randomly selected) were examined. In a few 

quadrangles, sites containing all three kinds of plants 

could not be found. At sites where two kinds were 

present, the third was omitted in sampling. 

The selection of the part of a soybean field to sample 

was limited by the characteristic of mature soybean 

seeds to fall from the pods if the plants are disturbed; 

to prevent damage to the crop we did not walk 

through the fields, but sampled only at or near the 

edges of the fields. We chose the side of a field for 

sampling by drawing lots, and the distance from a 

corner of a field at which to sample was likewise 

selected. Sampling corn fields and pastures was not 

restricted by this constraint; therefore all parts of a 

field had an equal chance of being sampled. Sampling 

points within these fields were chosen by a 

randomization procedure based on a coordinate 

system. 

Corn was collected by breaking two ears from the 

stalk, removing the husk (shuck) from the ears, and 

placing the ears in a cloth bag. Soybean pods 

containing the seeds were pulled from the stalks in a 

quantity sufficient to fill a cloth bag that measured 

6x12 inches ( 15x30 em). Enough pasture grass leaves 

and stems to fill a one-quart (about one-litre) f~eezer 

carton were clipped from the plants with steel shears. 

All samples of corn were of yellow-grain hybrid 

varieties, except one sample of a white-grain variety, 

and all soybean samples consisted of yellow-seed 
DB GEOCHEMICAL SURVEY OF MISSOURI 

varieties. No attempt was made to ascertain varietal 

names. Pasture grass samples included either one 

species or a mixture of several species, according to 

the composition of the pasture that was selected for 

sampling. 

A list of the plant species that were sampled 

follows: 

Corn (Zea mays L.) 

Soybean (Glycine max (L.) Merr). 

Pasture grasses: 

Big bluestem (Andropogon gerardi Vitman) 

Bluegrass (Poa pratensis L.) 

Fescue (Festuca elatior L.) 

Foxtail (Setaria viridis (L.) Beauv .) 

Johnson grass (Sorghum kalepense (L.) Pers.) 

Paspalum (Paspalum setaceum Michx.) 

Timothy (Pkleum pratense L.) 

LABORATORYPROCEDURESUSED 

The corn grains were removed from the cobs, the 

soybean seeds were shelled from the pods, and the 

cobs and pods were discarded. The samples of grain, 

seed, . and pasture grasses were air dried, then 

pulverized in a Wiley mill. A part of the pulverized 

material was weighed, then burned to ash in an 

electric oven in which the heat was increased 50°C per 

hour to a temperature of 450°C and held at this 

temperature for 14 hours. The resulting ash was then 

weighed to determine the ash yield of the dry plant 

material. Analytical methods for most elements 

employ a weighed aliquot of the ash. For determining 

concentrations of a few elements that would be 

volatilized and lost by burning the sample, weighed 

aliquots of the dry plant material were used for 

analysis. 

The soil samples were dried in an oven with 

circulating air held at 50°C before the samples were 

pulverized in a ceramic mill to about minus-100-mesh 

particle size. Before being pulverized, the samples 

were not sifted through a 200-mesh sieve, as is done in 

some soil studies; therefore, rock particles larger than 

this mesh size, if present, were retained and 

pulverized. 

TABLE !.-Analytical methods used in this study 

Method Elements commonly reported, and plant ash 

Six -step emission 

spectrographic ........................ In soils and plant ash: B, Ba, Be, 

Cr, Cu, Ga, La, Mn, Mo, Nb, Ni, 

Ph, Sc, Sr, Ti, V, Y, Yb, and Zr. 

In soils only: Co. In plant ash 

only: AI, Fe, and Mg. 

Atomic absorption, flame .................. In soils and plant ash: Cd, Li, Na, 

Atomic absorption, 

and Zn. In soils only: Mg. In 

plant ash only: Ca and Co. 

flameless ............................. In soils and dry plant material: Hg. 

X-ray fluorescence ...................... In soils: AI, Ca, Fe, K, P, Se, 

and Si. 

Colorimetric ............................ In plant ash only: P. 

Catalytic ............................... In dry plant material only: I. 

Specific ion electrode .................... In dry plant material and soils: F. 

Gasometric ............................. In soils only: Carbonate carbon. 

Calculated .............................. In soils only: Organic carbon. 

2-3 diaminonaphthalene 

fluorimetric ........................... In dry plant material only: Se. 

Arsine-spectrophotometricisotope dilution ........................ In soils and dry plant materials: As. 

Gravimetric ............................ Ash. 

Principal references 

Myers, Havens, and Dutton, 1961; 

Neiman, 1976. 

Ward and others 1969; 

Shacklette and others, 1973; 

Harms, 1976. 

Vaughn (1967); Harms, 1976; 

Huffman and Dinnin, 1976. 

Wahlberg, 1976. 

Harms, 1976. 

Cuthbert and Ward, 1964; Harms, 

1976. 

Harms; 1976; Huffman and 

Dinnin, 1976. 

Scott, 1962; Tourtelot, Huffman, 

and Rader, 1964; Huffman and 

Dinnin, 1976. 

Huffman and Dinnin, 1976. 

Harms, 1976. 

Harms, 1976; Huffman and 

Dinnin, 1976. 

Ward, Lakin, Canney, and others, 1963; 

Harms, 1976. 
COMPOSITION OF CORN, SOYBEANS, GRASSES, AND ASSOCIATED SOILS D9 

Before submitting the plant samples to the 

laboratories for chemical analysis, we selected 26 

samples of the 3 kinds of plants at random from the 

total of 115 collected. Each of these selected samples 

was divided into 2 approximately equal parts in order 

to obtain duplicate analyses to use as a basis for 

estimating the error in laboratory procedures; these 

divided samples were then merged in randomized 

sequence with the 89 samples that had not been 

divided. After numbering the entire set of 141 samples 

in a sequence that was random with respect to both 

geographical location and kind of plant and that was 

unknown to the analysts, the samples were submitted 

to the analytical laboratories. 

Following the same procedures used for dividing 

and randomizing plant samples, we divided 23 samples 

of soil to provide duplicates. The 46 resulting 

duplicates were merged with the 92 samples that were 

not divided, and the total of 138 samples was 

submitted to the laboratories in a randomized order. 

The methods of analysis used for all samples of the 

Missouri geochemical studies were described in detail 

in a previous report (Miesch, 1976). An outline of the 

methods used for analysis of plant and soil samples is 

given in table 1. 

The approximate lower limits of detection for 

materials analyzed are given in table 2. 

TABLE 2.-Approximate lower limits of determination for 

elements in soils a:nd plant materials 

[Dry soil was used for analyses of all elements. Dry plant material was used for arsenic, 

fluorine, iodine, mercury, and selenium analyses; plant ash was used for analyses of 

all other elements. Limits are give·n in parts per million. Leaders( ... ) indicate no data 

available] 

Element Lower limit of detection 

Soils Plant materials 

AI ....... 10,000 

As....... .2 

B........ 20 

Ba ..... ·.. 2 

Be....... 1.5 

C, in C03 . 100 

C, organic 1,000 

Ca ....... 1,000 

Cd....... 1 

Ce....... 150 

Co....... 5 

Cr....... 1 

Cu....... 1 

F......... 40 

Fe ....... 11,000 

Ga....... 5 

Hg....... .01 

I ....... .. K ........ 1,000 

La....... 50 

1Total Fe as Fe203. 

2Fe. 

50 

.25 

50 

5 

3 

100 

.2 

300 

1 

2 

2 

.5 

220 

5 

.025 

1 

100 

70 

Lower limit of detection 

Element 

Soils Plant materials 

Li ........ 5 

Mg ....... 300 

Mn ....... 1 

Mo ....... 3 

Na ....... 100 

Nb ....... 10 

Nd ....... 70 

Ni....... 5 

P ........ 300 

Pb ....... 10 

Sc....... 5 

Se....... .1 

Si. .... 10,000 

Sr....... 5 

Ti. ....... 2 

v ........ 7 

y ........ 10 

Yb....... 1 

Zn ....... 10 

Zr ....... 10 

4 

50 

2 

5 

25 

150 

5 

40 

20 

7 

.01 

10 

5 

10 

20 

2 

25 

20 

TABLE 3.-Elements commonly looked for, but rarely or never 

detected, by semiquantitative spectrographic analysis, and th.eir 

approximate lower Umits of determination, in parts per miUion, 

for samples in this report 

[Leaders ( .... ) in a figure column indicate that the element is commonly detected in the 

sample material listed in the column heading] 

Material analyzed Material analyzed 

Element Soils Plant ash Element Soils Plant ash 

Arsenic ...... 1,000 2,000 Palladium .... 2 5 

Antimony .... 200 500 Platinum .... 2 50 100 

Bismuth ..... 10 20 Praseodymium 100 200 

Cadmium .... 50 100 Rhenium .

2 .. 50 100 

Cerium ...... 200 500 Samarium .. 100 200 

Dysprosium1. 50 100 Silver ....... .5 1 

Erbium1.

2 

... 50 100 Scandium ..... 7 

Eurofiium 1 .. 100 200 Tantalum .... 200 500 

Gadoinium . 50 100 Telluriu~ .... 2,000 5,000 

Germanium .. 10 20 Terbium .... 300 700 

Gold ........ 20 50 Thallium ..... 50 100 

Hafnium ..... 100 200 Thorium ..... 200 500 

Holmium1 ... 20 50 Thulium1 .... 20 50 

Indium ...... 10 20 Tin ......... 10 15 

Lithium .

1 ... 100 200 Tungsten . : .. 100 300 

Lutetium . 2

. 30 70 Uranium ..... 500 1,000 

Neodymium . 70 150 Zinc ......... 300 

Niobium ..... 10 20 

1Looked for if yttrium is greater than 50 ppm. 

2Looked for if lanthanum or cerium is found. 

TABLE 4.-Error variance attributed to laboratory procedures 

based on duplicate analyses of cultivated soils and crop plants 

from Missouri 

[Error variances were estimated from Jog 1o concentrations, except where noted. 

n = total number of samples analyzed for estimation of error variances. Leaders 

( .... ) in figure columns indicate no data available] 

Soils 

Element, 

Error 

ash, or variance 

n=46 

pH (23 pairs) 

AI. ...... 0.00018 

As ........ 00183 

B ......... 03210 

Ba ........ 00304 

C, organic .01468 

Ca....... .00017 

Cd ...... . 

Co ........ 00608 

Cr ........ 00284 

Cu ........ 00304 

F ......... 07253 

Fe ........ 00018 

Ga ........ 00558 

Hg ........ 02213 

I ........ . 

K ......... 00003 

Li. ........ 00016 

Mg ........ 00133 

Plants 

Error 

variance 

n=52 

(26 pairs) 

0.05892 

.01480 

.01022 

.00144 

.02287 

.00966 

. 00824 

. 00246 

. 00039 

.00606 

Soils 

Element, Error 

ash, or variance 

n=46 

pH (23 pairs) 

Mn ....... 0.01133 

Mo ....... 

Na ....... . 00010 

Ni ....... . 00790 

P ........ . 04446 

Ph ....... .00964 

Sc ....... .00151 

Se ....... .00967 

Si1 ....... 2.1011 

Sr ....... .00316 

Ti. ....... .01786 

v ........ .00410 

Y ........ . 00997 

Yb ....... .00839 

Zn ....... .00076 

Zr ....... .01471 

Ash ...... pH2 ...... . 02913 

Plants 

Error 

variance 

n=52 

(26 pairs) 

0.00428 

.01719 

.00818 

.03288 

.00240 

.00149 

.00737 

.00223 

.00133 

~Error variance estimated from percent concentration rather than logarithms. Error variance estimated from standard units. 

All samples of both soils and plants were analyzed 

first by semiquantitative emission spectrophotometry, and the concentrations reported for many 

elements of primary interest were within the limits of 

determination of the method, as is indicated in table 1. 

Many other elements were commonly looked for by 
D10 GEOCHEMICAL SURVEY OF MISSOURI 

TABLE 5.-Components of logarithmic variance estimated for samples of plow zone soils from cornfields in four vegetation-type areas in 

Missouri 

[All variances are on the basis of Jog10 concentration, except where noted. *, significantly greater than zero at the 0.05 probability level) 

Between areas 

Element 

Totallog10 Variance Percent 

variance component of total 

AI ............. 0.01251 0.00203 16 

As ............. .03714 .01231* 33 

B .............. .04219 .01146* 27 

Ba ............. .01465 .00190 13 

C, organic ...... .03073 .01075* 35 

Ca ............. .08738 0 <t 

Co ............. .04261 .00849* 20 

Cr ............. .01983 .00664* 33 

Cu ............. .03971 .00675* 17 

F .............. .07916 .02161* 27 

Fe ............. .02875 .00717* 25 

Ga ............. .01574 .00211 13 

Hg ............ .05922 0 <1 

K .............. .01668 .00181 11 

Li ............. .01284 .00436* 34 

Mg ............ .04042 .00484 12 

Mn ............ .07157 0 <t 

Na ............. .04062 .00461 11 

Ni ............. .08835 0 <1 

P .............. .08175 .00464 6 

Pb ............. .03070 .00187 6 

Sc ............. .01840 .00458* 25 

Se ............. .05813 .02262* 39 

Sil ............ 33.014 6.7320 20 

Sr ............. .02774 .00105 4 

Ti ............. .02940 .00413 14 

v .............. .02711 .00511 19 

Y .............. .02352 .00553* 23 

Yb .. 00 0 0 0 0 0 0 00 0 .01744 .00511* 29 

Zn ............. .02818 .00365 13 

Zr ............. .03074 .00272 9 

pH2 ........... .74910 0 <1 

lvariance components based on percent Si. 

2variance components based on standard units. 

this analytical method, but were rarely or never 

detected. These elements are listed in table 3. 

The estimated variances associated with laboratory 

procedures are given in table 4. By subtracting these 

components from the between-sites variance 

components in the nested analysis of variance (tables 

5, 6, 7, 12, 13, and 14), one can estimate the natural 

local variability. Because both components are 

estimates, the analytical variance component may 

exceed the variance component at the site level, as, 

for example, occurred for boron and fluorine in all crop 

soils of this study. Such a result indicates the most, if 

not all, of the apparent local variability (s~) is more 

correctly attributed to laboratory procedures than to 

natural causes. In these circumstances, a measure of 

Between 71/z' Between sites quadrangles 

Variance Percent Variance Percent 

component of total component of total 

0.00584* 47 0.00464 37 

0 <t .02483 67 

0 <1 .03073 73 

.00371 25 .00904 62 

.00346 11 .01652 54 

.04857* 56 .03880 44 

.00638 15 .02774 65 

.00418 21 .00901 45 

.00495 12 .02801 71 

0 <1 .05755 73 

.00406 14 .01752 61 

.00527* 33 .00836 53 

.00933 16 .04989 84 

.00996* 60 .00491 29 

.00161 13 .00637 54 

.01554* 38 .02004 50 

.01179 16 .05978 84 

.02378* 59 .01223 30 

.04320* 49 .04515 51 

0 <t .07711 94 

.00630 21 .02253 73 

.00352 19 .01030 56 

.01323 23 .02228 38 

11.138* 34 15.144 46 

.01641* 60 .00998 36 

0 <t .02527 86 

.00862* 32 .01338 49 

.00444 19 .01357 58 

.00236 14 .00997 57 

.00773 27 .01680 60 

.00550 18 .02252 73 

.30831* 41 .44079 59 

the natural variability between sites will require more 

precise laboratory procedures. 

RESULTS 

GEOCHEMICAL CHARACTERISTICS OF CULTIVATED SOILS 

Most randomly selected sampling sites, as explained 

earlier, were sufficiently large to contain separate 

fields of corn, soybeans, and ·pasture grasses. A 

sample of soil was collected at one location in each of 

these fields, and components of chemical variance 

were calculated separately for soils supporting corn, 

soybeans, and pasture grasses. These components, as 

related to geographic scale, are given in tables 5, 6, 

and 7. 

Only about one-half of the 32 soil constituents 
COMPOSITION OF CORN, SOYBEANS, GRASSES, AND ASSOCIATED SOILS Dll 

TABLE 6. -Components of logarithmic variance estimated for samples of plow zone soils from soybean fields in four vepetation-type areas 

in Missouri 

[All variances are on the basis of log10 conc-entration, except where noted. •, significantly greater than zero at the 0.05 probability level) 

Between areas 

Elemem 

Totallog10 Variance Percent 

variance component of total 

AI ............. 0.01100 0.00297 27 

As ............. .04991 .01913* 38 

B .............. .03283 .00154 5 

Ba ............. .01630 0 <1 

C, organic .04084 .00993* 24 

Ca ............. .05398 0 <1 

Co ............. .05860 .01043 18 

Cr ............. .02891 .00741 26 

Cu ............. ,.02326 .00537* 23 

F .............. .06716 .01351* 20 

Fe ............. .04497 .01337* 30 

Ga ............. .01634 .00537* 33 

Hg ............ .09186 0 <1 

K .............. . 01161 .00229 20 

Li ............. .01623 .00647* 40 

Mg ............ .03948 .00640 16 

Mn ............ .11369 0 <1 

Na ............. .01860 .00256 14 

Ni ............. .06900 .00236 3 

P .............. .08533 .01513* 18 

Ph ............. .03397 .00492 14 

Sc ............. .01779 .00767* 43 

Se ............. .07657 .03565* 47 

Sit ............ 30.5204 6.6957* 22 

Sr ............. .01895 .00073 4 

Ti ............. .04135 .02069* 50 

v .............. .04161 .01874* 45 

Y .............. .03620 .01720* 48 

Yb ............. .04920 .03384* 69 

Zn ............. .05029 .00288 5 

Zr ............. .04926 .02932* 60 

pH2 ........... .68226 .00521 1 

lvariance components based on percent Si. 

2variance components based on standard units. 

examined exhibit statistically significant variation at 

the 95-percent confidence level between the four 

vegetation-type areas, and the amount of variation, 

expressed as percent of the total, is relatively minor at 

this scale. For example, only titanium, ytterbium, and 

zirconium in soils from soybean and pasture fields 

exhibit 50 percent or more of their variation between 

vegetation-type areas. In contrast, calcium, strontium, and nickel in all fields, mercury, manganese, and 

pH in corn and soybean fields, and barium in soybean 

and pasture fields exhibit virtually no variation 

between areas. Tables 5, 6, and 7 indicate that most of 

the chemical variation in these soils is within 

vegetation-type areas or, even more important, 

between sites. 

Between 7'12' Between sites quadrangles 

Variance Percent Variance Percent 

component of total component of total 

0.00542* 49 0.00260 24 

.00861 17 .02217 44 

0 <1 .03129 95 

.00513 31 .01107 69 

.00195 5 .02896 71 

.00940 17 .04458 83 

.01918* 33 .02899 49 

.01411* 49 .00739 26 

.00549 24 .01240 53 

.01750 26 .03615 54 

.01736* 39 .01424 32 

.00169* 38 .00478 29 

.02824 31 .06362 69 

-.00618* 53 .00314 . 27 

.00383 24 .00593 37 

.02087* 53 .01221 31 

.03983 35 .07836 65 

.00843* 45 .00771 41 

.03678* 53 .02986 43 

0 <1 .07020 82 

.00418 12 .02487 73 

.00353 20 .00659 37 

:01063 14 .03029 40 

6.1877 20 17.637 58 

.00942* 50 .00880 46 

0 <1 .02066 50 

.01094* 26 .01193 29 

.00721 20 .01179 32 

.00415 8 .01121 23 

.01641 33 .03160 63 

.00689 14 .01305 26 

.19316 28 .48389 71 

Part of the between-site variance is due to 

laboratory procedures (sample preparation and 

analysis), but, because these effects tend to be small 

for most elements (table 4), most of the variance can 

be attributed to natural causes-that is, to actual 

small-scale variation within the soil. Boron and 

fluorine are notable exceptions to this generalization, 

in that all of the variance between sites, as given on 

tables 5, 6, and 7, may be attributed to laboratory 

procedures rather than to natural causes. 

Results of the chemical analyses of the cultivated 

soils from the four vegetation-type areas that were 

sampled in Missouri are summarized in tables 8, 9, and 

10. The geometric mean (GM) for each element in each 

area is an estimate of the most typical concentrations 
D12 GEOCHEMICAL SURVEY OF MISSOURI 

TABLE 7 .-Components of logarithmic variance estimated for samples of plow-zone soils from pasture fields in four vegetation-type areas in Missouri 

[All variances are based on log10 concentration, except where noted. •, significantly greater than zero at the 0.05 probability level] 

Between areas 

Element 

Totallog10 Variance Percent variance component of total 

AI ............. 0.00951 0.00008 < 1 

As ............. .05665 .00556 10 

B .............. .03541 .00459 13 

Ba ............. .02287 0 < 1 

C, organic .04468 .01482* 33 

Ca ............. .05583 0 < 1 

Co ............. .03199 .00221 7 

Cr ............. .02538 .01051* 41 

Cu ............. .01897 .00400 21 

F .............. .08298 .00256 3 

Fe ............. .03042 .00155 5 

Ga ............. .01077 .00215* 20 

Hg ............ .05793 .00618 11 

K .............. .01214 .00074 6 

Li ............. .01227 .00129 11 

Mg ............ .04359 0 < 1 

Mn ............ .07903 .00798* 10 

Na ............. .02819 .00386 14 

Ni ............. .05402 0 < 1 

P .............. .06518 .01062* 16 

Pb ............. .02433 .00235 10 

Sc ............. .01254 .00327* 26 

Se ............. .05410 .01547* 29 

SP ............ 31.9051 1.7578 6 

Sr ............. .02377 0 < 1 

Ti ............. .03263 .01700* 52 

V .............. .02205 .00609* 28 

Y .............. .04598 .01454* 32 

Yb .. 0 ••• 0 0. 0 0. 0 .03424 .01728* 50 

Zn ............. .05122 .00585 11 

Zr ............. .03132 .01728* 55 

pH2 ........... .51212 .03362 7 

lvariance components based on percent Si. 

2variance components based on standard units. 

of the element in a randomly selected sample from 

each kind of field in each vegetation-type area. In 

those cases where the detection ratio does not equal 

unity, the mean logarithms were computed using 

procedures developed by Cohen (1959) and described 

as they were applied to the Missouri geochemical 

studies by Miesch (1976). The geometric deviation 

(GD) is a factor used to estimate the degree of scatter 

of the data around this typical concentration. For 

example, a GD of 1.0 indicates no variation in 

concentration of the element in the soil material that 

was analyzed; a GD of 2.0 indicates that about 

two-thirds of the concentrations range from GM+2.0 

to GMx2.0. 

Geometric mean concentrations that differ by as 

Between 7 112' quadrangle!> Between sites 

Variance Percent Variance Percent 

component of total component of total 

0.00518* 54 0.00425 45 

.01114 20 .03995 70 

.OOi94 5 .02888 82 

.00896* 39 .01391 61 

0 < 1 .02986 69 

.00924 17 .04659 83 

.01352* 42 .01626 51 

.00730* 29 .00757 30 

.00609* 32 .00888 47 

.02145 26 .05898 71 

.00960 32 .01927 63 

.00220 20 .00642 60 

0 < 1 .05175 89 

.00732* 60 .00409 34 

.00069 6 .01029 84 

.02790* 64 .01569 36 

0 < 1 .07105 90 

.01665* 59 .00768 27 

.03989* 74 .01412 26 

0 < 1 .05456 84 

.00360 15 .01838 75 

.00348* 28 .00580 46 

.02556* 47 .01307 24 

8.6493 27 21.498 67 

.01783* 75 .00594 25 

.00175 5 .01389 43 

.00290 13 .01306 59 

0 < 1 .03145 68 

.00284 8 .01412 41 

.00007 < 1 .04532 88 

.00058 2 .01346 43 

.05500 11 .42350 83 

much as a factor of two between the vegetation-type 

areas are apparent in tables 8, 9, and 10. For about 

one-half of the constituents tested, at least the highest 

and lowest means are significantly different at the 

0.05 probability level (tables 5, 6, and 7). Most of the 

higher concentrations occur in soils from the 

Floodplain Forest area. However, the highest mean 

values in the pasture fields are evenly distributed 

between the Glaciated Prairie and the Unglaciated 

Prairie areas. 

Basically, the analysis of variance (tables 5, 6, and 7) 

assures us only that significant differences in 

concentrations of many of the elements occur at least 

between the two vegetation-type areas that have the 

extreme mean values. This analysis does not indicate 
COMPOSITION OF CORN, SOYBEANS, GRASSES, AND ASSOCIATED SOILS .Dl3 

TABLE B.-Mean chemical composition and chemical variation of cultivated soils from cornfields in four vegetation-type areas in Missouri 

[Mean concentrations given in parts per million except where percent is indicated. Dry soil used for chemical analysis; soil slurry used for pH determinations. GM, geometric means, 

except where indicated; GD, geometric deviation, except where indicated; ratio, number of samples in which element was detected to total number of samples analyzed; 

leaders ( ... ) in figure column, no data available. Tests using analysis of variance techniques indicated that differences were significant at the 0.05 probability level for 

concentrations of certain elements in soils from the vegetation-type areas that had the highest and lowest concentrations of these elements, as indicated by boldface and italic, 

respectively. Significant differences were not indicated by analysis of variance tests for the concentrations of AI, Ba, Ca, Ga, Hg, K, Mg, Mn, Na, Ni, P, Pb, Si, Sr, Ti, V, 

Zn, Zr, and pH. Because of insufficient data, differences in concentrations of Be, carbonate C, Cd, La, Nb, and Sn were not tested for statistical significance) 

Element or pH Floodplain Forest Glaciated Prairie 

GM GD Ratio GM GD 

AI, percent . 4.0 1.21 8:8 4.8 1.16 

As. 5.5 1.68 8:8 10 1.32 

B . . . . . . . . . . -~20 7:8 25 1.53 

Ba . .. .. . .. .. 800 1.20 8:8 810 1.28 

Be . .. . .. -< 1.5 0:8 1.2 1.26 

C, organic, 

percent .. .91 1.32 8:8 1.7 1.26 

C, carbonate, 

percent .. . < .01 2:8 .0075 4.28 

Ca, percent . .48 1.38 8:8 .57 1.30 

Cd . . . -.. <1 0:8 <1 

Co. 5.2 1.51 6:8 8.1 1.28 

Cr. 43 1.56 8:8 70 1.18 

Cu. 11 1.82 8:8 18 1.41 

F, percent. .021 1.82 8:8 .044 1.95 

Fe, percent . 1.4 1.80 8:8 2.4 1.28 

Ga. 12 1.23 8:8 15 1.21 

Hg .. .037 1.93 8:8 .051 1.81 

K, percent. 1.7 1.15 8:8 1.7 1.12 

La. ..<50 0:8 49 1.09 

Li.. .. 15 1.32 8:8 22 1.22 

Mg, percent .. .27 1.82 8:8 .36 1.36 

Mn .... . .. .. 460 2.32 8:8 590 1.73 

Na, percent. .79 1.11 8:8 .69 1.13 

Nb. 7.9 1.24 3:8 8.0 1.23 

Ni .. 8.4 2.36 6:8 14 1.51 

P, percent. .074 1.64 8:8 .063 1.66 

Pb .... 18 1.16 8:8 20 1.29 

Sc .......... 5.2 1.24 7:8 8.1 1.20 

Se ....... 1 .. .31 1.51 8:8 .67 1.67 

Si, percent . . 38 6.61 8:8 35 3.50 

Sn. . ... <tO 0:8 < 10 

Sr ......... . 150 1.21 8:8 150 1.21 

Ti, percent .. .22 1.49 8:8 .27 1.35 

V. 52 1.74 8:8 84 1.21 

Y ..... 16 1.46 8:8 22 1.26 

Yb .. 2.0 1.56 8:8 2.7 1.22 

Zn ... 37 1.69 8:8 55 1.29 

Zr ...... . . . . 190 1.77 8:8 180 1.16 

pH2 .... 6.4 .80 8:8 6.5 .93 

1 Arithmetic means and standard deviations. 

2standard units and standard deviations. 

whether the two mean values that lie between the 

extremes are significantly different from each other or 

from the extremes. To determine if these differences 

exist, we applied a multiple range test (Duncan, 1955) 

to the data. The application of this test to geochemical 

problems was described by Miesch ( 1976). The results 

demonstrated that, as a group, the cultivated soils 

from the Floodplain Forest area tend to be 

distinctively low in concentrations of certain elements 

as follows: cornfield soils-lowest in arsenic, organic 

carbon, cobalt, chromium, iron, and ytterbium; 

soybean field soils-lowest in titanium and ytterbium; 

and pasture field soils-lowest in chromium, titanium, 

ytterbium, and zinc. 

The multiple range test also revealed that 

cultivated soils from the two prairie areas were 

Vegetation-type areas 

Unglaciated Prairie Oak-hickory Forest 

Ratio GM GD Ratio GM GD Ratio 

10:10 3.4 1.32 10:10 3.9 1.30 10:10 

10:10 10 1.47 10:10 8.8 1.23 10:10 

9:10 29 1.52 10:10 41 1.39 10:10 

10:10 600 1.39 10:10 700 1.26 10:10 

4:10 1.1 1.31 3:10 .94 1.37 2:10 

10:10 1.4 1.33 10:10 1.4 1.56 10:10 

4:10 <.01 4:10 < .01 4:10 

10:10 .39 2.43 10:10 .44 2.30 10:10 

0:10 <1 0:10 <1 1:10 

10:10 9.7 1.81 10:10 8.7 1.41 10:10 

10:10 63 1.18 10:10 66 1.24 10:10 

10:10 14 1.33 10:10 19 1.51 10:10 

10:10 .022 1.57 10:10 .020 1.56 10:10 

10:10 2.3 1.32 10:10 2.1 1.14 10:10 

10:10 11 1.35 10:10 12 1.37 10:10 

10:10 .042 1.70 10:10 .038 1.56 10:10 

10:10 1.2 1.41 10:10 1.5 1.43 10:10 

9:10 45 1.18 7:10 45 1.18 7:10 

10:10 18 1.22 10:10 19 1.17 10:10 

10:10 .21 1.38 10:10 .26 1.56 10:10 

10:10 530 1.94 10:10 530 1.41 10:10 

10:10 .45 1.84 10:10 .55 1.68 10:10 

4:10 9.5 1.10 8:10 10 1.00 10:10 

10:10 10 1.96 9:10 11 2.16 9:10 

9:10 .041 2.04 8:10 .058 1.87 10:10 

10:10 23 1.28 10:10 27 1.91 10:10 

10:10 6.3 1.25 9:10 6.3 1.33 9:10 

10:10 .52 1.48 10:10 .91 1.43 10:10 

10:10 37 5.02 10:10 38 4.78 10:10 

1:10 <10 0:10 <10 1:10 

10:10 110 1.64 10:10 120 1.53 10:10 

10:10 .31 1.49 10:10 .34 1.35 10:10 

10:10 63 1.26 10:10 78 1.35 10:10 

10:10 25 1.37 10:10 27 1.35 10:10 

10:10 3.0 1.24 10:10 3.0 1.00 10:10 

10:10 41 1.29 10:10 53 1.43 10:10 

10:10 240 1.23 10:10 260 1.61 10:10 

10:10 6.5 .82 10:10 6.5 .81 10:10 

similar in having distinctively high concentrations of 

selenium in cornfield soils and selenium and arsenic in 

soybean field soils. High selenium values in 

uncultivated prairie soils were reported earlier 

(Erdman and others, 1976). Cultivated soils from the 

Glaciated Prairie area differ from soils of the other 

three areas in having high fluorine concentrations in 

cornfield soils and high gallium concentrations in 

soybean field soils. The only other result of this test 

was the grouping of Floodplain Forest and Glaciated 

Prairie area soils as distinctive in having low 

zirconium. 

In view of the possible effects of cultivation on 

native soils that were discussed earlier, the question 

arises whether the postulated effects on element 

concentrations can, in fact, be substantiated by results 
D14 GEOCHEMICAL SURVEY OF MISSOURI 

TABLE 9.-Mean chemical composition and chemical variation of cultivated soils from soybean fields in four vegetation-type areas in 

Missouri 

[Mean concentrations given in parts per million except where percent is indicated. Dry soil used for chemical analyses; soil slurry used for pH determinations. GM, geometric mean, 

except where indicated; GD, geometric deviation, except where indicated; ratio, number of samples in which element was detected to total number of samples analyzed; leaders 

( ... ) in figure column, no data available. Tests using analysis of variance techniques indicated that differences were significant at the 0.05 probability level for concentrations of 

certain elements in soils from the vegetation-type areas that had the highest and lowest concentrations of these elements, as indicated by boldface and italic, respectively. 

Significant differences were not indicated by analysis of variance tests for the concentrations of AI, B, Ba, Ca, Co, Cr, Hg, K, Mg, Mn, Na, Ni, Pb, Sr, Zn, and pH. Because 

of insufficient data, differences in concentrations of Be, carbonate C, Cd, La, Nb, and Sn were not tested for statistical significance) 

Vegetation-type areas 

Element or pH Floodplain Forest Glaciated Prairie Unglaciated Prairie Oak-hickory Forest 

GM GD Ratio GM GD Ratio GM GD Ratio GM GD Ratio 

AI, percent . 4.0 1.25 10:10 5.2 1.08 10:10 

As. 5.9 1.70 10:10 12 1.31 10:10 

B ......... 21 1.46 8:10 29 1.52 10:10 

Ba .... . 630 1.26 10:10 700 1.26 10:10 

Be .... . .. < 1.5 1:10 1.2 1.26 4:10 

C, organic, 

percent .... .93 1.57 10:10 1.6 1.32 10:10 

C, carbonate, 

percent .. .. < .01 2:10 <.01 2:10 

Ca, percent . .47 1.49 10:10 .58 1.33 10:10 

Cd ... .<1 0:10 <1 1:10 

Co. 5.6 1.44 8:10 10 1.42 10:10 

Cr ......... 40 1.77 10:10 63 1.18 10:10 

Cu. 12 1.53 10:10 19 1.13 10:10 

F, percent .. .016 1.89 10:10 .036 1.43 10:10 

Fe, percent . 1.4 1.96 10:10 2.8 1.13 10:10 

Ga ........ 12 1.36 10:10 16 1.15 10:10 

Hg ......... .042 2.00 10:10 .051 1.89 10:10 

K, percent. 1.7 1.09 10:10 1.6 1.08 10:10 

La. 33 1.39 3:10 40 1.28 5:10 

Li. .. .. . 15 1.42 10:10 24 1.12 10:10 

Mg, percent .. .26 1.81 10:10 .38 1.18 10:10 

Mn. .. 350 2.31 10:10 500 2.20 10:10 

Na, percent . .76 1.15 10:10 .68 1.09 10:10 

Nb .... 6.6 1.33 2:10 7.4 1.27 3:10 

Ni .......... 9.8 1.67 9:10 16 1.40 10:10 

P, percent ... .078 1.57 10:10 .066 1.60 10:10 

Pb .. ... 18 1.15 10:10 25 1.41 10:10 

Sc .. 5.1 1.31 8:10 8.4 1.21 10:10 

Se ......... .33 1.67 10:10 .74 1.71 10:10 

Si, percent1 37 6.29 10:10 35 1.77 10:10 

Sn. <tO 0:10 <10 1 :10 

Sr. . .. 140 1.19 10:10 140 1.14 10:10 

Ti, percent .. .18 1.34 10:10 .26 1.36 10:10 

V. 42 1.65 10:10 93 1.16 10:10 

Y. 15 1.43 10:10 21 1.30 10:10 

Yb. 1.5 1.48 10:10 2.9 1.14 10:10 

Zn. 42 1.74 10:10 61 1.26 10:10 

Zr 

2 

.... . .. 150 1.39 10:10 180 1.34 10:10 

pH .. 5.8 .77 10:10 6.4 .84 10:10 

1 Arithmetic means and standard deviations. 

2standard units and standard deviations. 

of the present study. Our earlier study of uncultivated 

plants and soils in Missouri (Erdman and others, 1976) 

provided estimates of mean concentrations of 

elements in soils from six vegetation-type areas, 

including the four areas of the present study. The 

results of the two studies are not directly comparable 

because somewhat different sampling media were 

used. Plow zone soils were sampled in the present 

study, whereas only the lower soil zones were sampled 

in the earlier study. For this reason, the best 

comparison that can be made is of the two kinds of 

soils from the Floodplain Forest area, because these 

soils are relatively homogeneous with depth. A 

comparison of the chemical properties of the 

cultivated and uncultivated soils from this area follows 

(table 11). 

Examination of this table suggests that mean 

concentrations of some elements (particularly those 

3.8 1.29 8:8 3.8 1.23 9:9 

11 1.52 8:8 7.1 1.38 9:9 

31 1.53 8:8 27 1.54 8:9 

640 1.28 8:8 640 1.51 9:9 

1.0 1.34 2:8 < 1.5 1:9 

1.6 1.48 8:8 1.1 1.60 9:9 

< .01 3:8 <.01 4:9 

.38 1.76 8:8 .51 2.18 9:9 

<1 1:8 <1 0:9 

10 2.31 7:8 7.7 1.42 9:9 

67 1.13 8:8 65 1.16 9:9 

14 1.34 8:8 16 1.33 9:9 

.022 1.63 8:8 .025 1.76 9:9 

2.5 1.42 8:8 1.9 1.12 9:9 

11 1.28 8:8 11 1.22 9:9 

.046 1.72 8:8 .030 2.29 9:9 

1.2 1.41 8:8 1.5 1.30 9:9 

50 1.00 8:8 44 1.20 6:9 

20 1.20 8:8 18 1.17 9:9 

.22 1.37 8:8 .23 1.47 9:9 

590 1.89 8:8 650 2.09 9:9 

.56 1.50 8:8 .53 1.49 9:9 

9.4 1.11 6:8 9.8 1.07 8:9 

8.4 2.44 6:8 11 1.80 9:9 

.048 1.59 7:8 .041 1.80 7:9 

31 1.82 8:8 25 1.48 9:9 

6.7 1.25 8:8 6.5 1.16 9:9 

.67 1.56 8:8 .31 1.31 9:9 

37 4.90 8:8 38 5.11 9:9 

<to 1:8 <tO 0:9 

120 1.55 8:8 110 1.48 9:9 

.31 1.42 8:8 .40 1.31 9:9 

71 1.47 8:8 60 1.19 9:9 

32 1.35 8:8 27 1.37 9:9 

3.6 1.30 8:8 3.8 1.31 9:9 

63 2.11 8:8 41 1.41 9:9 

270 1.37 "8:8 360 1.40 9:9 

6.1 .93 8:8 6;5 .70 9:9 

essential for plant growth) are consistently lower in 

cultivated soils. Yet these apparent differences in 

mean element concentration between the two kinds of 

soil, with the exception of nickel, were not significant 

at the 95-percent confidence level when tested by the 

conventional t statistic. The t test, however, does not 

take into account the consistency of differences from 

one chemical element to the next. For example, 

cultivated soils from the three kinds of fields are at 

least 25 percent lower in concentrations of boron, 

cobalt, iron, manganese, and zinc, as well as the 

nonessential elements arsenic, flourine, lithium, 

nickel, scandium, vanadium, and ytterbium. Because 

of this, an intuitive judgment was made that the 

differences, for the most part, are real and may 

indicate that depletion in elements has occurred as a 

result of cultivation. The exact factory responsible for 

the lower concentrations cannot be stated with 
COMPOSITION OF CORN, SOYBEANS, GRASSES, AND ASSOCIATED SOILS D15 

TABLE 10.-Mean chemical composition and chemical variation of cultivated soils from pasture fields in four vegetation-type areas in 

Missouri 

[Mean concentrations given in parts per million except where percent is indicated. Dry soil used for chemical analyses; soil slurry used for pH determinations. GM, geometric mean, except where 

indicated; GD, geometric deviation, except where indicated; ratio, number of samples in which element was detected to total number of samples analyzed; leaders( ... ) in figure column, no data 

available. Tests using analysis of variance techniques indicated that differences were significant at the 0.05 probability level for concentrations of certain elements in soils from the vegetationtype areas that had the highest and lowest concentrations of these elements, as indicated by boldface and italic, respectively. Significant differences were not indicated by analysis of variance tests 

for the concentrations of AI, As, B, Ba, Ca, Co, Cu, F, Fe, Hg, K, Li, Mg, Na, Ni, Pb, Si, Sr, Zn, and pH. Because of insufficient data, differences in concentrations of Be, carbonate C, Cd, La, Nb, and Sn were not tested for statistical significance] 

Vegetation-type areas 

Element or pH ___ F_I_ood__.:..p_Ia_in_F_o_re_s_t __ Glaciated Prairie Unglaciated Prairie Oak-hickory Forest 

GM GD Ratio GM GD Ratio GM GD Ratio GM GD Ratio 

AI, percent 4.2 As 6.4 

B. 2I Ba. . .. 700 Be. . . <1.5 

C, organic, 

1.25 

2.25 

1.56 

1.18 

lO:IO 

lO:IO 

7:IO 

lO:IO 

O:IO 

4.6 

I2 

28 

780 

1.1 

1.11 

1.63 

1.60 

1.33 

1.31 

10:10 

IO:IO 

9:10 

10:10 

3:10 

3.8 

9.3 

36 

670 

<1.5 

1.24 

1.41 

1.47 

1.46 

10:10 

10:10 

10:10 

10:10 

1:10 

3.9 

8.5 

26 

590 

< 1.5 

1.33 

1.22 

1.46 

1.58 

10:10 

10:10 

10:10 

10:10 

1:10 

percent. . 1.1 

C, carbonate, 

percent. < .OI 

Ca, percent . .48 

1.69 

1.46 

1.42 

1.54 

1.54 

1.93 

1.96 

IO:IO 

O:IO 

IO:IO 

2.2 

< .OI 

.66 

1.22 

1.38 

1.46 

1.18 

1.16 

1.60 

1.20 

10:10 

4:10 

10:10 

1.7 

< .01 

.47 

<I 

1.29 

2.34 

1.53 

1.19 

1.23 

2.32 

1.28 

10:10 

3:10 

10:10 

1.5 

<.01 

.44 

<I 

1.60 

1.55 

i:4s 

1.26 

1.25 

1.73 

1.23 

10:10 

3:10 

10:10 

Cd. . <I Co. 6.0 Cr. 99 

Cu. 12 

F, percent. .017 

Fe, percent . 1.6 

Ga I2 

Hg.. .053 

K, percent. 1.7 La. 28 

Li.. I6 

Mg. percent.. .25 Mn ......... . 950 

Na, percent. .74 

Nb. 

Ni. 

P, percent. 

Pb .. 

Sc .. 

Se ... 1 Si, percent 

Sn .. 

8.0 

IO 

.067 I8 

5.1 

.28 

37 <10 

Sr .......... 140 

Ti, percent. . .17 

v. 48 

y 15 

Yb. 1. 7 

Zn. 45 Zr 2 ........ 140 

pH . . 5.9 

1.23 

2.16 

1.10 

1.48 

1.49 

1.91 

2.02 

1.22 

1.23 

1.53 

1.52 

1.16 

1.3I 

1.65 

7.74 

1.14 

1.34 

1.49 

1.43 

1.47 

1.70 

1.36 

.56 

l:IO 

IO:IO 

10:10 

IO:IO 

IO:IO 

IO:IO 

10:10 

IO:IO 

10:10 

2:10 

10:10 

IO:IO 

IO:IO 

IO:IO 

4:IO 

IO:IO 

IO:IO 

IO:lO 

8:10 

IO:lO 

IO:IO 

0:10 

IO:lO 

IO:IO 

IO:lO 

IO:lO 

IO:IO 

lO:IO 

lO:IO 

IO:lO 

~Arithmetic means and standard deviations. 

Standard units and standard deviations. 

<I 

8.7 

63 

I8 

.029 

2.3 

15 

.069 

1.6 

43 

21 .35 

580 

.70 

f~.(i 

.067 

25 

7.3 

.62 35 

<to 

150 

.27 

78 

22 

2.7 

68 

190 

6.6 

1.I8 

1.5I 

1.13 

1.23 

1.12 

1.36 

1.89 

1.11 

1.19 

1.23 

1.53 

1.63 

1.12 

1.68 

2.96 

1.21 

1.39 

1.33 

1.58 

1.35 

1.74 

1.30 

.58 

certainty. It is possible that a loss in essential 

elements resulted from removal in crops. Moreover, 

both essential and nonessential elements may have 

been depleted by erosion and leaching, which often are 

accelerated by cultivation. On the other hand, 

concentrations of some elements in the cultivated soils 

from this area appear to be the same as in uncultivated 

soils, or even slightly higher. These elements include 

the major nutrients calcium, magnesium, potassium, 

and phosphorus, which are the elements most likely to 

have been added to the soil in fertilizers. 

CHEMICAL COMPOSITION OF SELECTED CROP PLANTS 

Estimated variance components for elemental 

concentrations in corn grains, soybean seeds, and 

pasture grasses for the three geographic levels of the 

sampling design are listed in tables 12, 13, and 14. The 

significance of differences between the four 

1:10 

10:10 

10:10 

10:10 

10:10 

10:10 

IO:IO 

IO:IO 

10:10 

6:10 

10:10 

I0:10 

I0:10 

10:10 

5:10 

10:10 

10:10 

10:10 

10:10 

10:10 

10:10 

0:10 

10:10 

10:10 

10:10 

10:10 

10:10 

10:10 

10:10 

10:10 

8.5 

59 

16 

.029 

2.0 

11 

.038 

1.3 

47 

20 

.25 600 

.50 

9.5 

9.7 

.098 

22 

6.3 

.47 

37 

<to 

110 

.37 68 

31 

3.7 

41 

290 

6.4 

1.28 

1.21 

1.34 

1.14 

1.16 

1.43 

1.33 

1.50 

1.10 

1.77 

1.52 

1.33 

1.18 

1.39 

5.07 

1.58 

1.30 

1.29 

1.36 

1.30 

1.29 

1.29 

.66 

0:10 

10:10 

10:10 

10:10 

10:10 

10:10 

10:10 

10:10 

10:10 

8:10 

10:10 

10:10 

10:10 

10:10 

8:10 

9.10 

9:10 

10:10 

10:10 

10:10 

10:10 

1:10 

10:10 

10:10 

10:10 

10:10 

10:10 

10:10 

10:10 

10:10 

8.8 

70 

16 

.024 

2.2 

12 

.057 

1.5 

40 

20 

.27 

490 

.51 

8.9 

13 

.050 

25 

6.3 

.38 

37 

<IO 

120 

.29 

63 

25 

3.0 

58 

240 

6.5 

1.24 

1.68 

1.40 

1.42 

1.21 

1.60 

1.50 

1.67 

1.16 

2.01 

1.98 

1.41 

1.26 

1.43 

4.73 

1.57 

1.29 

1.18 

1.51 

1.24 

1.74 

1.30 

.89 

1:10 

10:10 

10:10 

10:10 

10:10 

10:10 

10:10 

10:10 

10:10 

5:10 

10:10 

10:10 

10:10 

10:10 

6:10 

9:10 

8:10 

10:10 

10:10 

10:10 

10:10 

0:10 

10:10 

10:10 

10:10 

10:10 

10:10 

10:10 

10:10 

10:10 

vegetation-type areas was tested by analysis of 

variance techniques. Of the approximately 20 

elements tested for each crop plant sample, 

differences significant at the 95-percent confidence 

level were found as follows: corn grains, potassium 

and nickel; soybean seeds, calcium, cadmium, copper, 

strontium, and zinc; and pasture grasses, barium, 

calcium, fluorine, sodium, lead, zinc, and ash. 

However, in general, the amount of variation at this 

scale, expressed as percent of the total, is relatively 

small. For example, aluminum, boron, iron, 

manganese, phosphorus, and selenium concentrations 

in all three kinds of crop samples exhibit 10 percent or 

less of their total variance among vegetation-type 

areas. The greatest amount of variation by far is found 

between sites within areas, expecially in the 

composition of seeds and grains. Exceptions to this 

result are nickel and phosphorus in soybean seeds and 

aluminum in pasture grasses. 
D16 GEOCHEMICAL SURVEY OF MISSOURI 

TARLE H.-Comparison of mean chemical properties of means (GM) for each element in each vegetation-type 

uncultivated soils and cultivated soils from the Floodplain Forest area are estimates of the most typical concentrations 

vegetation-type area in Missouri of the elements in a randomly selected sample from 

[Means are geometric and are expressed in parts per million, except where noted. n in 

column heading indicates number of samples analyzed] 

Element Uncultivated Cultivated soil 

or pH soil1, n=50 C~rnfield soil, Soybean field soil, Pasture field soil, 

n=8 n=10 n=10 

AI, percent 4.4 4.0 4.0 4.2 

As. 7.5 5.5 5.9 6.4 B 29 20 21 21 

Ba. 660 800 630 700 Be .99 < 1.5 < 1.5 < 1.5 

C, carbonate, 

percent. .046 < .01 <.01 < .01 

C, organic, 

percent .. .89 .91 .93 1.1 

Ca. percent . .42 .48 .47 .48 

Co 8.3 5.2 5.6 6.0 

Cr. 39 43 40 39 

Cu. 15 11 12 12 

F. 250 210 . 160 170 

Fe, percent . 2.1 1.4 1.4 1.6 

Ga. 12 12 12 12 

Hg. .057 .037 .042 .053 

K, percent. 1.8 1.7 1.7 1.7 

La 32 <50 33 28 

Li ... 20 15 15 16 

Mg. .31 .27 .26 .25 

Mn. 710 460 350 350 

Na, percent. .62 .79 .76 .74 

Nb. 5.8 7.9 6.6 8.0 

Ni 19 8.4 9.8 10 

P, percent. .068 .067 .074 .078 

Ph 19 18 18 18 

Sc. 7.1 5.1 5.2 5.1 

Se .. .31 .28 .31 .33 

Si2, percent . 36 37 38 37 

Ti, percent. .26 .17 .22 .18 

v 64 48 52 42 

y 23 15 16 15 

Yb 2.1 1.7 2.0 1.5 Zn 54 45 37 42 Zr 160 140 190 150 

pH3 5.8 5.9 6.4 5.8 

1Erdman and others, 1976. 

2Arithmetic means. 

3standard units. 

Error attributed to laboratory procedures (sample 

preparation and analysis, table 4) contributes to the 

observed between-site variance, but for most 

elements in the plant material these effects are small 

(tables 12, 13, and 14). Therefore, most of the variance 

at this level of the sampling design can be attributed 

to natural causes. For example, the analytical error 

for selenium in corn grains contributes less than one 

percent to the variance observed between sites. In 

contrast, virtually all the variance in boron between 

sites for the crop plants, as with soils, is due to 

laboratory procedures. Moreover, at least 80 percent 

of the site variance for magnesium and phosphorus in 

corn grains and for copper, nickel, and zinc in soybean 

seeds is due to laboratory error. 

Results of the analyses of crop plant samples are 

summarized in tables 15, 16, and 17. The geometric 

that area. 

Visual inspection of the data summarized in these 

tables did not reveal obvious patterns in crop-plant 

element concentrations that are consistent between 

the vegetation-type areas and kinds of plants that 

were analyzed. Areas having significantly different 

mean concentrations in each crop plant were grouped 

by Duncan's (1955) multiple range test. Again, no 

general patterns in crop plant chemistry were found, 

but the following distinctive associations were 

revealed: corn grains-nickel low in samples from the 

Floodplain Forest area; soybean seeds-cadmium high 

in samples from the Floodplain Forest area, strontium 

high in samples from the Oak-hickory Forest area, and 

zinc high in samples from the Oak-hickory Forest and 

Unglaciated Prairie areas; pasture grass stems and 

leaves-barium low in samples from the Unglaciated 

Prairie area, and sodium high in samples from the 

Floodplain Forest and U nglaciated Prairie areas. 

Although significant differences between areas 

were found for 12 chemical constituents in the 3 kinds 

of crop samples (tables 15, 16, and 17), the variations 

appear to be almost completely erratic. The marked 

differences in mean compositions between the three 

crops, regardless of origins, support the conclusion by 

Shacklette, Sauer, and Miesch (1970) that plant 

chemistry reflects a species (genetic) control much 

more than a geographic control. 

CORRESPONDENCE BETWEEN THE ELEMENTAL 

COMPOSITION OF CULTIVATED PLANTS AND 

THAT OF ASSOCIATED SOILS 

The correspondence between the elemental 

composition of corn grains, soybean seeds, and stems 

and leaves of pasture grasses and that of associated 

soils was examined by means of correlation 

coefficients (table 18 and fig. 3). The data in this table 

and figure show no consistently strong correlations 

between total concentrations of elements in cultivated 

soils and in crop plants. Similar results were obtained 

for uncultivated soils and native plant tissues from 

Missouri (Erdman and others, 1976) and from Georgia 

(Shacklette and others, 1970). 

Soils utilized in agriculture generally have levels of 

elements that are well within the range of utilization 

by, or tolerance of, crop plants; otherwise the soil 
COMPOSITION OF CORN, SOYBEANS, GRASSES, AND ASSOCIATED SOILS D17 

TABLE 12.-Components of logarithmic variance estimated for corn grains from four vegetation-type areas in Missouri 

!All variances are on the basis of log10 conrentration, except where noted. •. significantly greater than zero at the 0.05 probability level] 

Between areas 

Element 

Totallog10 Variance Percent 

variance component of total 

AI ...... 0.19053 0.00181 1 

B .............. .01672 .00030 2 

Ba ............. .13111 0 <1 

Ca ............. .01293 0 <1 

Cd ............. .25534 0 <1 

Cu ............. .02286 .00105 5 

Fe ............. .01928 .00184 10 

I .............. .00810 .00114 14 

K .............. .00112 .00023* 21 

Mg ............ .00507 0 <1 

Mn ............. .01071 .00036 3 

Mo ............ .09947 .00260 3 

Na ............. .03555 .00411 12 

Ni ............. .10936 .02440* 22 

P .............. .00434 0 <1 

Se ............. .15631 0 <1 

Sr ............. .07561 0 <1 

Zn ............. .00746 0 <1 

Ash ............ .00611 0 <1 

would be unproductive. Within this range the 

manifold factors that influence element availability 

tend to override the differences in total element 

content of the soil in terms of influence on the 

concentration of elements in the crop plants. 

SUMMARY 

1. Corn grains, soybean seeds, pasture grasses, and 

associated soils were sampled in four of the six 

vegetation-type areas of Missouri, using a three-level 

geographically nested sampling design. 

2. Components of variance were estimated in order 

to partition the total variance between the three 

geographic levels of the design. Only about one-half of 

the 32 soils constituents that were examined exhibited 

statistically significant variation between the areas. 

Most of the variation occurred within vegetation-type 

areas and, predominantly, between sites within 

quadrangles. 

3. Relatively high concentrations of most elements 

occurred in soils from cultivated fields in the Glaciated 

Prairie area, and the lowest concentrations were in 

soil samples from the Floodplain Forest area. Area 

means were grouped by Duncan's (1955) multiple 

Between quadrangles Between sites 

Variance Percent Variance Percent 

component of total component of total 

0 <1 0.18872 99 

0 <1 .01642 98 

.01830 14 .11281 86 

0 <1 .01293 100 

.04304 17 .21230 83 

.00531 23 .01650 72 

.00090 5 .01653 85 

0 <1 .00696 86 

0 <1 .00088 79 

.00002 <1 .00506 100 

0 <1 .01035 97 

.02155 22 .07531 75 

0 <1 .03145 88 

0 <1 .08496 78 

.00146 34 .00288 66 

.01243 8 .14388 92 

.00067 1 .07494 99 

.00357* 48 .00389 52 

.00006 1 .00605 99 

range test, which revealed that soils of the Floodplain 

Forest area are distinct from soils of the other areas. 

4. An assessment of the possible effects of 

cultivation and cropping on the element content of 

soils suggests that many elements have been depleted 

in cultivated soils compared to uncultivated soils. 

5. The variation in element composition of corn 

grains, soybean seeds, and pasture grasses was (as 

with soils) largely between sites within quadrangles. 

The variation between quadrangles and between 

vegetation-type areas was even less pronounced than 

that in the soils. 

6. No consistent differences in crop-plant element 

concentrations were found between either the 

vegetation-type areas or the plants that were 

sampled-that is, variation between elements and 

areas appear to be almost completely erratic. 

7. No strong correlations were found between 

concentrations of elements in cultivated soils and crop 

plant tissues, suggesting that within the normal range 

of element concentrations in cultivated soils, chemical 

analyses of corn grains, soybean seeds, and pasture 

grass stems and leaves do not generally reflect the 

total elemental composition of the associated soils. 
D18 

Floodplain 

U nglaciated 

Prairie 

ALUMINUM 

IRON 

SODIUM 

GEOCHEMICAL SURVEY OF MISSOURI 

BARIUM BORON CALCIUM 

LEAD MAGNESIUM MANGANESE 

STRONTIUM TITANIUM VANADIUM 

FIGURE 3.-Correlations between the log concentrations of selected elements in crops and cultivated soils within four vegetation-type 
CHROMIUM 

NICKEL 

ZINC 

COMPOSITION OF CORN, SOYBEANS, GRASSES, AND ASSOCIATED SOILS 

COBALT 

PHOSPHORUS 

ZIRCONIUM 

COPPER 

POTASSIUM 

EXPLANATION 

0 Corn grains 

0 Soybean seeds 

6 Pasture-grass leaves 

and stems 

D19 

FLUORINE 

SELENIUM 

areas of Missouri. The locations of the symbols on the radii indicate the correlations by their distances from the center of the circle. 
D20 GEOCHEMICAL SURVEY OF MISSOURI 

TABLE 13.-Components of logarithmic variance estimated for soybean seeds from four vegetation-type areas in Missouri 

[All variances based on log10 concentration. • , significantly greater than zero at the 0.05 probability level) 

Between areas RetwePn quadrangles Between sites 

Element 

Totallog10 Variance Perceni Variance Percent Variance Percent 

variance component of total component of total component of total 

AI ............. 0.07860 0.00041 1 0 . <1 0.07820 99 

B .............. .01906 .00184 10 .00328 17 .01395 73 

Ba ............. .12618 .00612 5 .01897 15 .10109 80 

Ca ............. .00468 .00154* 33 .00048 10 .00265 57 

Cd ............. .15884 .06800* 43 0 <1 .09085 57 

Cu ............. .01149 .00305* 21 .00080 6 .01065 73 

Fe ............. .04206 .00305 7 .00096 2 .03805 91 

I .............. .00443 0 <1 0 <1 .00443 100 

K .............. .00073 .00005 6 0 <1 .00068 94 

Mg ............ .02083 .00264 13 .00192 9 .01628 78 

Mn ............ .02297 0 <1 .00744 32 .01553 68 

Mo ............ .21275 0 <1 .06762 32 .14513 68 

Na ............. .03618 0 <1 .00154 4 .03465 96 

Ni ............. .08169 0 <1 .04800* 59 .03369 41 

P .............. .01324 .00110 8 .01214 92 0 <1 

Se ............. .12631 .00634 5 .03248 26 .08750 69 

Sr ............. .06988 .02084* 30 .00575 8 .04329 62 

Zn ............. .00574 .00259* 45 .00068 12 .00248 43 

Ash ............ .00102 .00002 2 .00038 37 .00062 61 

TABLE 14.-Components of logarithmic variance estimated for pasture grasses from four vegetation-type areas in Missouri 

(All variances based on log10 concentration. •, significantly greater than zero at the 0.05 probability level.] 

Between areas Ret WPPn quadrangles Between sites 

Element 

Totallog10 Variance Percent Variance Percent Variance Percent 

variance component of total component of total component of total 

AI ............. 0.21553 0 <1 0.11248* 57 0.09306 43 

B .............. .01446 .00092 6 0 <1 .01354 94 

Ba ............. .06296 .01772* 28 0 <1 .04524 72 

Ca ............. .02098 .00411* 20 0 <1 .01686 80 

Cd ............. .11249 .01153 10 .03347 30 .06749 60 

Cr ............. .12752 0 <1 .05114* 40 .07637 60 

Cu ............. .02152 .00096 4 .00301 14 .01755 82 

F .............. .10369 .02375* 23 .00911 9 .07083 68 

Fe ............. .11322 0 <1 .04767* 42 .06556 58 

I .............. .01083 .00138 13 .00221 20 .00724 67 

K .............. .02634 .00098 4 .00421 16 .02116 80 

Mg ............ .02594 .00316 12 .01137* 44 .01141 44 

Mn ............ .04195 .00228 5 .00406 10 .03562 85 

Na ............. .39304 .12948* 33 .09106 23 .17250 44 

P .............. .01501 .00046 3 .00231 15 .01223 82 

Pb ............. .05072 .01068* 21 .00853 17 .03151 62 

Se ............. .09043 .00947 10 .00907 10 .07189 79 

Sr ............. .04420 0 <1 .00160 4 .04260 96 

Ti ............. .18642 0 <1 .05523 30 .13119 70 

Zn ............. .05517 .00753* 14 .00990 18 .03774 68 

Zr ............. .12962 0 <1 .04126 32 .08836 68 

Ash ............ .01623 .00369* 23 0 <1 .01254 77 
COMPOSITION OF CORN, SOYBEANS, GRASSES, AND ASSOCIATED SOILS D21 

TABLE 15.-Mean chemical composition and chemical variation in the ash of corn grains from four vegetation-type areas in Missouri 

[Mean concentrations given in parts per million, except where percent is indicated. GM, geometric mean; GD, geometric deviation; ratio, number of samples in which element was 

detected to total number of samples analyzed; leaders ( ... ) in figure column, no data available. Tests using analysis of variance techniques indicated that differences were 

significant at the 0.05 probability level for concentrations of K and Ni in samples from the vegetation-type areas that had the highest and lowest concentrations of these 

elements, as indicated by boldface and italic, respectively. Significant differences were not indicated by analysis of variance tests for the concentrations of AI, B, Ba, Ca, Cd, 

Cu, Fe, I, Mg, Mn, Mo, Na, P, Se, Sr, Ti, Zn, and ash. Because of insufficient data, differences in concentrations of Co, Cr, F, Pb, and Zr were not tested for statistical 

significance I 

Element or ash Floodplain Forest Glaciated Prairie 

VeB!tation-t,rEe areas 

U nglaciated Prairie Oak-hickory Forest 

GM GD Ratio GM GD Ratio GM GD Ratio GM GD Ratio 

AI, percent .. 0.034 5.87 7:8 0.020 1.99 10:10 0.023 1.99 10:10 0.017 1.98 10:10 

B .. 62 1.29 8:8 68 1.29 10:10 59 1.19 10:10 68 1.35 10:10 

Ba .......... 21 2.55 8:8 15 1.88 10:10 16 1.92 10:10 21 2.82 10:10 

Ca. percent .. .30 1.33 8:8 .31 1.27 10:10 .29 1.29 10:10 .32 1.22 10:10 

Cd. .37 1.72 6:8 .62 2.34 9:10 .40 1.49 9:10 .64 3.55 9:10 

Co. . .. < 1 3:8 1.0 5:10 .5 4.06 3:10 <1 2:10 

Cr .... <2 2:8 <2 0:10 <2 0:10 <2 0:10 

cy 70 1.30 8:8 69 1.49 10:10 94 1.35 10:10 81 1.42 10:10 

F. <.5 1:8 <.5 1:10 <.5 1:10 .43 1.12 2:10 

Fe, percent . .17 1.67 8:8 .13 1.28 10:10 .16 1.13 10:10 .13 1.30 10:10 

11 ......... 5.4 1.16 8:8 5.7 1.17 10:10 5.3 1.22 10:10 4.6 1.24 10:10 

K, percent. 29 1.09 8:8 30 1.07 10:10 31 1.05 10:10 31 1.06 10:10 

Mg. percent. 6.2 1.19 8:8 6.3 1.18 10:10 6.5 1.15 10:10 5.9 1.19 10:10 

Mn . . . . . . . . . . 300 1.00 8:8 260 1.40 10:10 320 1.31 10:10 290 1.14 10:10 

Mo. 18 1.66 8:8 11 1.83 9:10 7.9 2.72 7:10 11 2.19 8:10 

Na ... 39 1.67 8:8 32 1.51 10:10 25 7:10 25 8:10 

Ni. 12 1.95 7:8 23 2.04 10:10 32 1.73 10:10 28 2.03 10:10 

P, percent. 22 1.16 8:8 21 1.16 10:10 20 1.16 10:10 21 1.16 10:10 

Pb .. . <20 1:8 <20 1:10 <20 0:10 <20 0:10 Sel .062 2.41 8:8 .072 2.61 10:10 .047 1.88 10:10 .040 2.96 10:10 

Sr. 14 2.73 6:8 17 1.72 9:10 15 1.55 10:10 17 2.04 9:10 

Ti. ... <5 3:8 <5 2:10 <5 3:10 <5 0:10 

V. . ... <10 1:8 <10 0:10 <10 0:10 <10 0:10 

Zn . . . . . . . . . . 1,700 1.14 8:8 1,800 1.29 10:10 1,900 1.11 10:10 1,900 1.25 10:10 

Zr .......... <20 1:8 < 20 0:10 <20 0:10 <20 0:10 

Ash, percent. 1.8 1.17 8:8 1.6 1.23 10:10 1.5 1.19 10:10 1.6 1.19 10:10 

1Parts per million in dry material, not in ash. 

TABLE 16.-Mean chemical composition and chemical variation in the ash of soybean seeds from f0'1..tr vegetation-type areas in Missouri 

[Mean concentrations given in parts per million, except where percent is indicated. GM, geometric mean; GD, geometric deviation; ratio, number of samples in which element was 

detected to total number of samples analyzed; leaders ( ... )in figure column, no data available. Tests using analysis of variance techniques indicated that differences were 

significant at the 0.05 probability level for concentrations of Ca, Cd, Cu, Sr, and Zn in samples from the vegetation-type areas that had the highest and lowest concentrations of 

these elements, as indicated by bolclfaee and italic, respectively. Significant differences were not indicated by analysis of variance tests for the concentrations of AI, B, Ba, Co, 

Fe, I, K, Mg, Mn, Mo, Na, Ni, P, Se, and ash. Because of insufficient data, differences in concentrations ofF and Ti were not tested for statistical significance) 

Vegetation-type areas 

Element or ash Floodplain Forest Glaciated Prairie Unglaciated Prairie Oak-hickory Forest 

GM GD Ratio GM GD Ratio GM GD Ratio GM GD Ratio 

AI, percent .. 0.042 2.20 10:10 0.053 1.29 10:10 0.038 1.51 8:8 0.055 2.00 9:9 

B ........... 170 1.34 10:10 220 1.26 10:10 210 1.44 8:8 240 1.36 9:9 

Ba .......... 440 2.33 10:10 220 2.43 10:10 290 2.18 8:8 230 1.82 9:9 

Ca. percent .. 5.0 1.14 10:10 5.0 1.16 10:10 6.2 1.12 8:8 5.6 1.11 9:9 

Cd. 2.3 2.33 10:10 .60 2.04 10:10 .80 1.53 8:8 .68 1.93 9:9 

Co .. •. 1.0 7:10 2.0 2.97 8:10 2.1 3.75 6:8 2.1 2.39 8:9 

cy ..... ... . 170 1.26 10:10 180 1.26 10:10 210 1.30 8:8 230 1.30 9:9 

F ..... .46 1.85 5:10 .47 1.07 5:10 .49 1.04 6:8 <.5 3:9 

Fe, percent .. .10 1.14 10:10 .12 1.24 10:10 .13 1.23 8:8 .13 1.28 9:9 

11 ........... 13 1.14 10:10 13 1.14 10:10 12 1.15 8:8 13 1.15 9:9 

K, percent ... 41 1.06 10:10 40 1.06 10:10 39 1.03 8:8 41 1.06 9:9 

Mg, percent .. 2.5 1.43 10:10 3.0 1.24 10:10 3.2 1.35 8:8 3.6 1.40 9:9 

Mn .......... 400 1.57 10:10 320 1.31 10:10 310 1.42 8:8 360 1.29 9:9 

Mo .......... 10 3.77 7:10 17 3.95 8:10 9.4 3.16 6:8 20 2.04 9:9 

Na .......... 33 1.43 10:10 ~25 8:10 37 1.56 8:8 33 1.77 8:9 

Ni ...... . 130 2.62 10:10 94 1.50 10:10 110 1.50 8:8 87 1.71 9:9 

P,percent. .. 12 1.00 10:10 9.1 1.43 10:10 10 1.38 8:8 12 1.00 9:9 

Se ......... .17 2.68 10:10 .098 1.83 10:10 .097 2.28 8:8 .077 1.94 9:9 

Sr .......... 330 1.72 10:10 290 1.63 10:10 430 1.38 8:8 170 1.83 9:9 

Ti. .......... <5 2:10 ~5 6:10 4.7 2.33 5:8 11 3.67 8:9 

Zn .......... 890 1.17 10:10 870 1.09 10:10 1,100 1.19 8:8 1,100 1.08 9:9 

Ash, percent. 5.1 1.10 10:10 5.5 1.06 10:10 5.3 1.06 8:8 5.2 1.07 9:9 

1Parts per million in dry material, not in ash. 
D22 GEOCHEMICAL SURVEY OF MISSOURI 

TABLE 17 .-Mean chemical composition and chemical variation t"n the ash of pasture grass stems and leaves from four vegetation-type areas in Missouri 

[Samples included one or more of the following species: Bluegrass (Poa pratensis), big bluestem (Andropogon gerardi), fescue (Festuca elatior), foxtail (Setaria viridis), Johnson 

grass (Sorghum halepense), paspalum (Paspalum setaceum), and timothy (Phleum pratense). Mean concentrations given in parts per million, except where percent is 

indicated. GM, geometric mean; GD, geometric deviation; ratio, number of samples in which element was detected to total number of samples analyzed; leaders ( ... ) in figure 

column, no data available. Tests using analysis of variance techniques indicated that differences were significant at the 0.05 probability level for. concentrations of Ba, Ca, Na, 

Ph, Zn, and ash in samples from the vegetation-type areas that had the highest and lowest concentrations of these elements, as indicated by boldfaee and italic, respectively. 

Significant differences were not indicated by analysis of variance tests for the concentrations of AI, B, Cd, Co, Cr. Cu, Fe, I, K, Mg, Mn, P, Se, Sr, Ti, and Zr. Because of 

insufficient data, differences in concentrations of As, Hg, Li, Mo, Ni, V, and Yb were not tested for statistical significance] 

Element or ash Floodplain Forest G~M~----~G~D~------Ra--tl-.o 

Al'lpercent . . 0.63 

As ......... < .25 

B.. 52 Ba .......... 570 

Ca. percent . 3. 7 

Cd .. Co. 

Cr .. Cu ... Fe, percent . 

1.4 

1.5 

7.3 

48 

.25 

tlgl ......... < .025 I . . . . . . . . . . . 5.1 

K, percent. . . 19 

Li. .......... < 4 Mg, percent. 2.0 

Mn .......... 600 Mo........ 1.0 

Na, percent. .12 

Ni....... 8.8 

P, percent . 2.3 

Ph.. 26 

Sel. .11 

Sr. . 260 Ti. .......... 240 

v... 11 

Yb. .. < 2 Zn .......... 260 

Zr..... 34 

Ash, percent . II 

3.23 

1.11 

2.02 

1.54 

1.86 

1.47 

2.53 

1.47 

2.44 

1.16 

1.45 

1.18 

1.39 

4.93 

6.72 

2.13 

1.31 

1.58 

1.71 

1.76 

4.46 

2.03 

2.09 

2.96 

1.25 

10:10 

4:10 

10:10 

10:10 

10:10 

10:10 

9:10 

9:10 

10:10 

10:10 

2:8 

10:10 

10:10 

4:10 

10:10 

10:10 

2:10 

10:10 

8:10 

10:10 

8:10 

10:10 

10:10 

10:10 

6:10 

0:10 

10:10 

7:10 

10:10 

1Parts per million in dry material, not in ash. 

Glaciated Prairie 

GM GD 

0.57 

< .25 

63 

620 

5.0 

1.0 

1.2 

7.9 

46 

.24 

< .025 

6.3 

16 

<4 

1.5 

380 

3.2 

.024 

4.2 

2.1 

47 

.084 

280 

240 

4.8 

<2 

290 

29 

8.9 

2.09 

1.18 

1.44 

1.27 

1.99 

2.05 

1.65 

1.44 

1.62 

1.21 

1.49 

1.26 

1.46 

3.01 

1.76 

3.08 

1.34 

1.42 

2.17 

1.32 

1.80 

3.13 

1.49 

2.30 

1.24 

Vegetation-type areas 

Unglaciated Prairie 

Ratio GM GD Ratio 

10:10 

1:10 

10:10 

10:10 

10:10 

10:10 

6:10 

10:10 

10:10 

10:10 

0:10 

10:10 

10:10 

1:10 

10:10 

10:10 

4:10 

10:10 

5:10 

10:10 

10:10 

10:10 

10:10 

10:10 

3:10 

0:10 

10:10 

7:10 

10:10 

0.32 

< .25 

52 

310 4.5 

.68 

=1.0 

5.8 

41 .20 

<.025 

6.4 

23 

<4 

2.0 

470 

4.2 

.15 

3.1 

1.8 

40 .063 

250 

220 3.4 

<2 

190 

25 

11 

3.15 

1.21 

1.46 

1.19 

2.11 

2.35 

1.30 

2.43 

1.32 

1.32 

1.35 

1.60 

1.90 

3.10 

2.98 

1.35 

1.57 

1.53 

1.53 

2.16 

3.07 

1.38 

3.04 

1.24 

10:10 

1:10 

9.10 

10:10 

10:10 

10:10 

8:10 

9:10 

10:10 

10:10 

1:8 

10:10 

10:10 

0:10 

10:10 

10:10 

5:10 

10:10 

4:10 

10:10 

10:10 

10:10 

10:10 

10:10 

2:10 

0:10 

10:10 

6:10 

10:10 

Oak-hickory Forest 

GM GD Ratio 

0.38 

<.25 

60 

620 

5.4 

1.5 

1.6 

5.0 

56 

.23 

<.025 

6.4 

18 

<4 

2.3 

510 

<5 

.032 

5.2 

2.1 

50 

.054 

220 

260 

<10 

<2 

370 

32 

8.5 

2.78 

1.51 

1.44 

1.26 

2.24 

2.25 

2.67 

1.32 

1.98 

1.28 

1.48 

1.71 

1.82 

1.48 

2.67 

1.26 

1.75 

2.21 

1.81 

2.24 

1.53 

2.90 

1.29 

10:10 

1:10 

8:10 

10:10 

10:10 

10:10 

7:10 

9:10 

10:10 

10:10 

0:8 

10:10 

10:10 

0:10 

10:10 

10:10 

1:10 

10:10 

6:10 

10:10 

10:10 

10:10 

10:10 

10:10 

1:10 

1:10 

10:10 

7:10 

10:10 

TABLE lB.-Correlations between the concentrations of elements in corn grains, soybean seeds, and pasture grasses and in the 

associated cultivated soils from four vegetation-type areas in Missouri 

[r, product-moment correlation coefficient between logarithms of concentrations, n, number of pairs used in computation of r; leaders ( ... ) in figure column, data insufficient for 

computing correlations] 

Element 

AI. 

B. 

Ba. 

Ca. 

Co .. 

Cr .. Cu. 

F ... 

Fe. 

K. 

Mg. 

Mn. 

Na ... Ni. 

P ... 

Pb .. 

Se. 

Sr. 

Ti. .. V .. 

Zn. 

Zr .... 

Corn 

Floodplain 

Forest 

Glaciated 

Prairie 

r n r n 

-0.47 

-.41 

.27 

-.15 

-.81 

-.15 

.38 

.53 

-.80 

-.16 

.04 

.47 

-.21 

.72 

-.52 

7 -0.18 10 

7 .60 9 

8 .29 10 

8 -.37 10 

0 0 

2 

8 

0 

8 

8 

8 

0 

8 

6 

8 

0 

-.60 

.24 

.68 

.13 

.24 

-.04 

-.18 

.70 

8 .33 

6 -.44 

3 

0 

8 .17 

0 

0 

10 

0 

10 

10 

10 

10 

10 

10 

9 

0 

10 

9 

2 

0 

10 

0 

Ungl~~ted Oak-hickory Prwrte Forest 

r n 

-0.39 10 

-.23 10 

-.07 10 -.22 10 

.10 

-.19 

-.30 

.41 

-.06 

-.42 

-.29 

.00 

.04 

.61 

-.81 

.59 

0 

0 

10 

0 

10 

10 

10 

10 

7 

9 

8 

0 

10 

10 

3 

0 

10 

0 

r n 

0.38 10 

.27 10 

-.32 10 

-.33 10 

0 

0 -.11 10 

0 

.10 10 

-.32 10 

.23 10 

-.28 10 

-.34 8 

-.14 9 

.29 10 

-.17 

-.68 

.13 

0 

10 

9 

0 

0 

10 

0 

Floodplain 

Forest 

r n 

-0.48 10 

-.54 8 

.21 10 

.77 10 

-.35 5 

-.35 

-.23 

-.15 

-.12 

.23 

.03 

.07 

-.46 

-.05 

-.57 

-.49 

0 

10 

5 

10 

10 

10 

10 

10 

9 

0 

0 

10 

10 

2 

0 

10 

0 

Soybeans 

Glaciated 

Prairie Ungla~i~ted Oak-hickory Pratne Forest -r--n- r 

0.48 10 0.19 

.23 10 -.13 

-.06 10 -.22 

.48 10 .38 

-.13 8 -.22 

.04 

.28 

-.43 

.07 

.15 

-.14 

-.41 

.17 

.80 

.48 

.09 

.70 

0 

10 -.21 0 

10 .08 

10 -.01 

10 .03 

10 .40 

8 -.52 

10 -.26 

10 -.63 

0 

10 

10 

6 

0 

10 

0 

.47 

.03 

.51 

.58 

n 

8 

8 

8 

8 

5 

0 

8 

0 

8 

8 

8 

8 

8 

6 

7 

0 

8 

8 

5 

0 

8 

0 

r 

-0.03 

-.11 

.27 

.52 

-.05 

.31 

.09 

.18 

.07 

.36 

-.10 

.54 

-.24 

.30 

.12 

-.18 

.11 

n 

9 

8 

9 

9 

8 

0 

9 

3 

9 

9 

9 

9 

8 

9 

0 

0 

9 

8 

8 

0 

9 

0 

Floodplain 

Forest 

r n 

-0.60 10 

0 

.41 10 

-.20 10 

.10 9 

.43 

.12 

-.49 

-.21 

-.11 

-.11 

-.30 

.09 

.37 

.33 

-.02 

-.05 

-.08 

-.12 

.00 

.49 

.66 

9 

10 

10 

10 

10 

10 

10 

10 

8 

10 

8 

10 

10 

10 

6 

10 

7 

Pasture grasses 

Glaciated 

Prairie 

Unglaciated Oak-hickory 

Prairie Forest 

r n r 

0.46 

-.38 

-.31 

.12 

.48 

.47 

.00 

.02 

.21 

-.26 

-.66 

.43 

-.33 

.52 

-.43 

.45 

.51 

-.22 

-.08 

.50 

.45 

10 -0.22 

9 -.31 

10 -.32 

10 .45 

6 .30 

10 

10 

10 

10 

10 

10 

10 

10 

5 

10 

10 

10 

10 

10 

3 

10 

0 

.09 

-.11 

-.31 

-.11 

.01 

.30 

-.04 

-.10 

-.50 

.10 

-.33 

.13 

.72 

.27 

-.73 

.23 

n 

10 

9 

10 

10 

8 

9 

10 

8 

10 

10 

10 

10 

10 

3 

9 

10 

10 

10 

10 

2 

10 

6 

r n 

0.48 10 ·42 8 .52 10 

-.12 10 

.26 7 

-.26 9 

-.23 10 

.67 7 

-.36 10 

.25 10 

-.46 10 

.17 10 

-.30 10 

-.14 5 

-.38 8 

.65 10 

-.08 10 

.08 10 

.82 10 

0 

.53 10 

.36 7 
COMPOSITION OF CORN, SOYBEANS, GRASSES, AND ASSOCIATED SOILS D23 

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~U.S. GOVERNMENT PRINTING OFFICE: 1976-677·340/81