Geoscience Reference
In-Depth Information
First, plots M6 to M9 are the most productive (highest yield) but have the lowest EC
a
values. In
other words, soil EC
a
and yield correlation is not necessarily positive. Generally speaking, a yield
map represents a crop response surface that integrates the effect of a host of influences including
soil, water, nutrients, pests, climate, and management. Because of that, a yield response map could
be specific to a growing season and may change over time. On the other hand, a soil EC
a
map is
strictly a soil phenomenon, a reflection of highly complex interactions of soil physical and chemical
properties of texture (for instance, clay content), cation exchange capacity, organic matter, and soil
water. The main distinction between a soil EC
a
and a yield map is that the former is known to be
temporally stable (Farahani and Buchleiter, 2004), providing a useful base map for multiple years.
Second, Figure 20.3c shows that within-plot variability was as pronounced as within-field and
within-farmland variability. Figure 20.3 is an attempt to illustrate an example of the usefulness of
baseline EC
a
and yield information. This information can aid researchers in placing their particular
study across a desirable level of soil and productivity variance. As shown in Figure 20.3c, variabil-
ity ranged from less than 20 percent CV to about 60 percent in Montana plots. Choice of plots with
least soil variance is offered by plots M6 to M9. For small plot research, the baseline information
may be further refined to infer variability within the subplots.
20.4 ConClUdInG ReMARkS
Precision agriculture technology is providing a unique opportunity to create soil maps that are suf-
ficiently detailed to direct research planning at SAREC. In addition to the example given in this
article, a few other opportunities to apply the baseline data to practical field problems have already
occurred. For instance, the nature of soil variability maps as depicted by EC
a
was found useful to
(1) the planners with the selection and placement of two newly installed sprinkler irrigation systems
for field research (Claypool et al., 2004b), and (2) Belden et al. (2005) who explored the causes
of apparent Fe chlorosis exhibited by grain sorghum (
Sorghum bicolor
L. Moench). Areas of the
field were symptom free, but there were several patches that exhibited both extreme symptoms and
elevated EC
a
values. Soil EC
a
results are also being correlated with important soil properties such as
soil texture, which directly affects water-holding capacity—an important property in both irrigated
and dryland soils. The EC
a
map should help guide direct sampling and sensor placement.
RefeRenCeS
Belden, R.P.K., Claypool, D.A., and Farahani, H.J., Spatial variability of soil properties at the University of
Wyoming Sustainable Agricultural Research and Extension Center, In
Proc. Western Nutrient Manage-
ment Conference,
Vol. 6, Salt Lake City, UT, 2005.
Claypool, D. et al., Precision agriculture technology to plan and manage a new research and extension center,
In
Proc. Seventh International Conference on Precision Agriculture and Other Precision Resources
Management
, July 25-28, Minneapolis, MN, 2004a.
Claypool, D. et al., Modern tools help establish a new agricultural research and extension center,
Reflections,
College of Agriculture, University of Wyoming, Laramie, June 2004, 55, 2004b.
Farahani, H.J. and Buchleiter, G.W., Temporal stability of soil electrical conductivity in irrigated sandy fields
in Colorado,
Trans. ASAE
, 47, 79, 2004.
Lund, E.D., Christy, C.D., and Drummond, P.E., Practical applications of soil electrical conductivity mapping,
In
Precision Agriculture 99: Proc. 2nd European Conference on Precision Agriculture
, Stafford, J.V.,
Ed., BIOS Scientific Publishers, Oxford, U.K., 1999, 771.
