Agriculture Reference
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the soil water pH. This means either a procedure for sensing pH buffer in a similar
way as in conventional laboratories must be developed or - instead of this - soil prop-
erties that can act as suitable substitutes must be used. The first procedure - sensing
pH buffer directly in the field - has been studied, but not yet realized in an on-the-go
mode (Viscarra Rossel and McBratney 2003 ). As for substitute soil properties, the
cation-exchange-capacity (CEC) is a prime candidate. It predominantly depends on
the clay and organic matter in soils. Both clay and organic matter particles have a net
negative electric charge. Hence the higher the clay and organic matter content is, the
more cations can be absorbed and thus also be exchanged with the soil water.
The cation-exchange-capacity and the clay content have rather high correlations
to the electrical conductivities of soils (see Sect. 5.2.2.1 ) . And the organic matter
content can quite precisely be sensed via infrared reflectance (Sect. 5.3 ) . Hence,
substituting the traditional buffer pH measurements by techniques that can be
recorded on-the-go and thus provide site-specific information is feasible. It proba-
bly is reasonable to concentrate on the cation-exchange-capacity alone as a substi-
tute property for the buffer pH. Because this soil property includes already effects
of the clay and of the organic matter.
Concerning the spatial resolution, the advantages of on-the-go sensing of soil
water pH are obvious. Yet measurement errors might occur. Assuming that the soil
water pH indications from conventional laboratories are precise, the question is,
how well the on-the-go sensed records of ion-selective electrodes compare to these.
The comparison in Fig. 9.5 is based on the commercialized sensing technique of
Fig. 9.4 and furthermore to georeferenced points in fields where exactly samples for
analysing in laboratories were taken. This means that the advantages of on-the-go
sensing in the spatial resolution are not considered. The on-the-go recorded data
that were used without any further processing (Fig. 9.5 , top) were only fairly cor-
related to the soil water pH from the laboratories. The correlation was considerably
improved by field-specific data shifts in such a way that a regression slope of 1 was
obtained (Fig. 9.5 , bottom). This post-calibration removed field specific biases.
However, for the time being, these data shifts still require a few georeferenced labo-
ratory measurements from each field. So calibration is an important point.
Simultaneous sensing and mapping of several ions that are essential for crop
nutrition in the same field operation would be an interesting and challenging objec-
tive. Experiments in this direction by using different ion-selective electrodes in natu-
rally moist soil samples at the same time were simulated in a laboratory by Adamchuk
et al. ( 2005 ). The ion-selective electrodes corresponded to those listed in Sect. 9.2.1 .
After converting the voltage output of the electrodes to the respective ion activities,
the results were compared to those from methods of conventional soil laboratories.
The average correlations of 15 soils from sandy, loamy and clayey fields were:
for soil water pH r 2
=−
093096
.
.
for available potassium r 2
=−
061062
.
.
r 2
for nitrate nitrogen
=−
041051
.
.
Since all experiments were conducted in naturally moist soils, it was assumed
that primarily the low water content resulting from this caused the less successful
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