M.A. Johnston, M.P.W. Farina and J.Y. Lawrence. Cedara Agricultural College and Research Institute,. P/Bag X9059. Pietermaritzburg 3200. South Africa.
COMMUN. IN SOIL SCI. PLANT ANAL., 18(11), 1173-1180 (1987)
ESTIMATION OF SOIL TEXTURE FROM THE SAMPLE DENSITY KEY WORDS:
Soil testing, sample density,
volume weight, soil texture M.A. Johnston, M.P.W. Farina and J.Y. Lawrence Cedara Agricultural College and Research Institute, P/Bag X9059 Pietermaritzburg 3200 South Africa ABSTRACT Soil texture often plays an important role in the interpretation
of
purposes.
A reliable and inexpensive method of clay content
estimation
is,
laboratories.
soil
analytical
therefore,
a
data
for
requirement
fertilizer of
most
advisory advisory
This note discusses the use of sample density
(i.e. the mass of a scooped volume of soil) as an index of clay content.
A strong relationship was found to exist between sample
density and clay content, and such estimates of clay content were superior to those obtained by experienced pedologists using the "finger
test" procedure.
The use of this quick and
simple
procedure is considered to be ideally suited to soil testing laboratories handling large numbers of samples. INTRODUCTION In soil testing laboratories the texture of the soil, or an estimate of this, is often required for providing sound advice on 1173 Copyright © 1987 by Marcel Dekker, Inc.
1174
JOHNSTON, FARINA, AND LAWRENCE
crop fertilization and liming.
Potassium and phosphorus recommen-
dations are commonly adjusted according to clay content, recommended nitrogen is usually higher on sands than on loams and clays, and the calculation of lime requirement is sometimes based on clay content.
Many other applications of soil texture exist.
Laboratory measurement of clay content is costly and tedious, and the most common means of obtaining information on soil texture is by "finger testing".
It is widely recognized, however, that
this procedure is subjective and it is undoubtedly tedious when handling large numbers of samples. A recent development in the soil testing laboratory at Cedara was the introduction
of the volume measurement of soil using
standard soil scoops.
The mass of soil measured in the scoop,
termed here the sample density, but referred to as volume weight 3 by Mehlich , is naturally related to soil texture. It was, therefore, decided to investigate this relationship in greater detail with a view to the possibility of using sample density to estimate soil texture in routine soil testing.
EXPERIMENTAL One hundred and thirty topsoil samples were taken to represent a wide range of soil and climatic conditions in the province of Natal.
Samples varied greatly
organic matter mineralogy
content
in texture
(4 - 72% clay),
(0.2 - 5.0% organic carbon), and clay
(sesquioxidic-kaolinitic
through
to
illitic
and
smectitic). Soil samples were air-dried and ground to pass a 1 mm sieve, according to local standard practice. by recording the mass of 10 cm soil scoop.
Sample density was measured
of soil measured in a standard
The actual technique involved taking a heaped scoop-
ful of soil, giving the shaft of the scoop three firm taps with a plastic rod to ensure uniform compaction, and then levelling off the sample with the straight edge of the rod.
ESTIMATION OF SOIL TEXTURE
1175
Clay and silt analysis was done according to the pipette 2 method of Day . Modifications of note included the use of a 20 g soil sample, and dispersion by a three-minute treatment with an ultrasonic probe at an output of approximately 300 watts. Sand fractions were measured by dry-sieving. ticle size fractions were determined: (2 - 20 ym); um);
coarse silt (20 - 50 um);
The following par-
clay (< 2 y m ) ;
fine silt
very fine sand (50 - 100
fine sand (100 - 250 u m ) ; medium sand (250 - 500 um);
and coarse sand (500 - 1 000 u m ) . Organic carbon was measured by the Walkely-Black procedure .
RESULTS AND DISCUSSION The influence of clay content on sample density is illustrated in Fig. 1.
The relationship is of a logarithmic nature and
the high correlation (R
= 84%) for sample density vs. log
clay
% substantiates the strong relationship between these parameters. It
is
particularly strong above a sample density of about _3 1.10 g cm , which corresponds to soils with loamy and sandy texture. In the low sample density range the points show a greater degree of scatter.
Major reasons for this appear to be
the greater variations that occur in organic matter content and strength of structure in the high clay content range.
It is
evident that a high organic matter level tends to lower sample density while strong structure, even in the ground sample, tends to increase sample density. It is of interest that good correlation with sample density 2 was also obtained for log organic carbon (R = 80%), log fine e e 2 2 sand (R = 75%) and log medium sand (R = 75%). Clay content was found to be fairly highly correlated with organic carbon 2 (R = 64%). The correlations between sample density on the one hand and fine silt, coarse silt, very fine sand, and coarse sand 2 on the other, were found to be much weaker with R values of less than 50%.
1176
JOHNSTON, FARINA, AND LAWRENCE
Clay % vs Sample density
Log
R2 = 84% **
70
\
T * T
60
•V * "
50 Clay content
Log (Clay % + 1)= 7.87 - 3.84 x Sample density T
T 40
30
T : This symbol distinguishes soils with strong structure from those without.
~ _ ft*
•
20
10 •
oL
.
0.8
0.9
. 1.0
1.1 1.2 1.3 1.4 Sample Density (g cm~3)
1.5
1.6
Fig. 1 : The relationship between sample density and clay content for 130 Natal soils.
In view of the strong relationship that was found to exist between sample density and clay content, the potential of using sample density to estimate soil texture was recognized.
In order
to investigate the practical value of this, the following exercise was carried out on twenty soil samples which ranged widely in texture.
Clay content and sample density were measured, and
clay content was estimated
from sample density using the re-
gression equation given in Fig. 1. In addition, five experienced
ESTIMATION OF SOIL TEXTURE
1177
field pedologists were asked to estimate the clay content of these samples by the finger test.
The results of this exercise
are given in Table 1. 2 It is clear from the R
value and the slope of the relation-
ships between actual and estimated clay % that sample density provided a more reliable estimate of clay content than that produced by the finger test.
The low slope values for the finger
test estimates reflect a general tendency for this test to overestimate the clay content at levels above about 25%. It is noteworthy in Table 1 that the variation in estimated clay % between the different operators is sometimes quite alarming (e.g. samples 2, 5, 8 and 9 ) . In our experience this table represents a fair reflection of the unreliability of finger test estimates.
This problem appears to be particularly evident on
certain "difficult" soils where the content of organic carbon and/or silt plus fine sand (20-250 urn fraction) is relatively high. The poor estimate of clay content produced by sample density for sample number 16 deserves comment. the
only
strongly-structured
soil
This soil is a vertisol,
amongst
this group of 20 _3 samples. If a sample density of 1.16 g cm (that of sample number 16) is related to Fig. 1, it can be seen that there were other soils in the original collection that showed a similar relationship between sample density and clay content.
That is,
the scooped sample is relatively more dense for these soils than for most others.
Closer examination showed that the strongly-
structured
clay
densities.
These soils, as a group, therefore could be given
soils
have
characteristically
higher
special treatment in terms of a separate regression.
sample
In the
analytical system used at Cedara the effective cation exchange capacity
(ECEC) is routinely
reported, and this conveniently
allows the identification of strongly-structured
clays, since
these soils have characteristically high ECEC values.
1178
JOHNSTON, FARINA, AND LAWRENCE
TABLE 1 Estimates of Clay Content for 20 Soil Density and the Finger Test Method
Sample number
Measured clay
(%)
1 2 3
4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
Sample density (g cm
)
Estimated clay (5°) From sample density
15 29 8 22 52 19 33 17 19
1.27 1.27 1.42 1.26 1.01 1.21 1.06 1.29 1.27
19 19 10 20 53 24 44 17 19
4
1.45 1.38 1.14 1.05 1.46 1.22 1.16 1.35 1.35 1.18 1.17
12 32 45 9 23 29 14 14 27 28
11 41 40 6 33 57 16 17 24 27
Samples using Sample
9
Finger test by 5 observers
1
2
3
4
5
23 35
23 58 5 27 32 40 60 55 60
20 45 8 22 30 35 50 35 40 3 12 55 25 8 50 55 18
22 23
20 29
20 50 5 40 15 38 50 45 48 8 13 60 18 5 45 60 10 12 15 29
50
26
64
6 30 12 15 42 32 26 5 10 40 12
4
4 11 70 28 7
28 82 10 6 8 19
46
41
70 18 20 26 49
14
7 28 55 34 38 22 28 5 12 60 10 7 38
55 20 22 28 32
R2 %
66
39
Slope
0.97
0.51
0 .45 0.64
0.41
0.74
S.E. of slope
0.16
0.14
0 .12 0.14
0.15
0.13
Measured
vs. estimatec1 clay %
—
ESTIMATION OF SOIL TEXTURE
1179
The above findings have significant implications for soil testing laboratories. standard
The recording of the mass of soil in the
scoop is very quick, especially where an electronic
balance with printer is used.
Provided that laboratory staff are
properly trained, the sample density measurement is very reproducible.
It must be pointed out that the use of sample density
in the analytical system facilitates the interpolation of the fertilizer requirements for textural classes on which specific calibration data is unavailable.
The sample density therefore
provides a sliding scale for the calculation of texture-related fertility
requirements.
However, if a particular
laboratory
wishes to distinguish only between textural groups (e.g. clays, loams, and sands), then these groups can simply be associated with sample density ranges. Opportunity lationship
also exists for improving on the single re-
between
clay
content
and
sample density which is
reported here for a wide range of soil types.
Better prediction
of clay content will undoubtedly be possible if soils are grouped according to, for instance, basic soil types such as vertisols, oxisols, etc., and
a
relationship
Another
possibility
is the
soils.
As
out
pointed
highly-structured
use of
developed
for each group.
analytical
earlier, it is
data to group
possible to identify
soils in an advisory laboratory according to
their high ECEC values, so that a more appropriate relationship can be applied to these particular soils.
Nevertheless, the
available evidence suggests that estimation of soil texture using the equation established in Fig. 1, without any of the refinements suggested above, is more reliable than texture estimated from finger tests.
ACKNOWLEDGMENTS The authors are indebted to Mrs M. Smith for her valuable assistance with the statistical work.
1180
JOHNSTON, FARINA, AND LAWRENCE REFERENCES
1.
2.
3.
Allison, L.E., 1965. Organic carbon. In C.A. Black (ed.). Methods of soil analysis, Am. Soc. of Agron., Madison, Wis., U.S.A. Day, P.R., 1965. Particle fractionation and particle size analysis. In C.A. Black (ed.). Methods of soil analysis, Am. Soc. of Agron., Madison, Wis., U.S.A. Mehlich, A., 1973. Uniformity of soil test results as influenced by volume weight. Commun. Soil Sci. Plant Anal. 4:475-486.
