Growers know which parts of their property give the best yields.
Technology helps refine that knowledge, write Peter Fisher and Mohammad
Paddock zoning is a process that growers should approach without trepidation;
after all, many are already practising it, though they might just call
it common sense.
Farmers are constantly tailoring management operations according to the
properties of different paddocks, what the current and future conditions
might hold, and what risks might be involved. Most growers would already
know that they need to manage particular areas of some paddocks differently.
This is the basis of precision agriculture.
So what is new about PA? By integrating agronomy knowledge with recent
advances in technology, PA provides a more scientific process for identifying
and managing areas on the farm that might perform differently.
Managing individual paddocks differently might be considered the coarsest
form of zone management. The other extreme is where constantly variable
technology (CVT) is used to manage every location to match its conditions
as they vary throughout the paddock.
This is also not a new concept to growers. Tractor draft control, which
is probably the first example of CVT, was developed by harry Ferguson
back in 1926. This mechanism senses the force on ground-engaging implements
and adjusts the working depth "on-the-fly". Today, other CVTs are available
such as variable-rate spray nozzles and fertiliser applicators.
In general, CVT is not limited by the application technology, but rather
by our ability to accurately sense and locate the variability. In most
cases, our agronomic knowledge of the crop responses to spatial variability
is also not accurate enough to merit CVT More usually, a paddock is divided
into a small number of sub-paddock zones in which different management
can be confidently applied.
There are three main approaches to how sub-paddock zones can be delineated.
The first is based on a single factor of interest, such as soil sodicity
or weed prevalence. For such factors there are clear remedial actions,
such as applying gypsum or herbicide.
The second approach is to zone the paddock according to the yield produced
- high-, medium- and low-yielding areas. Providing these zones are stable
over time, growers know with confidence that each zone has a different
return, so they can explore ways of maximising the gross margin for each
zone. The criteria to identify each zone can be modified to account for
the economic threshold of different management options, including making
the area of each of these zones big enough for practical use.
The third approach is a combination of the first two, and uses a mixture
of yield and other site properties, such as elevation and electromagnetic
measurement (EM) maps. The approach uses a statistical methodology known
as "cluster analysis" to identify areas within the paddock that are similar
to each other in terms of a range of site properties included in the analysis.
However, the thresholds for different zones cannot be easily manipulated
using cluster analysis techniques. Once the zones have been identified,
further site investigation is usually required to understand why the zones
are different and what changes in management practice might be required.
The impact of selecting these different zoning techniques is being studied
by the Victorian Department of Primary industries (DPI) on a paddock in
the southern Mallee region of the state, as part of the GRDC"s national
PA Initiative. The first two images in Figure 1 show the individual site
characteristics of (a) elevation and (b) EM induction readings, a measure
of soil conductivity.
DPI has also been mapping the gammaradiometric emission profile of the
paddock, because we are interested in whether this can provide a rapid
estimate of the soil"s plant available water capacity (PAWC).
The third image is the average yield from three recent wheat crops (including
the drought season of 2004), zoned into high, medium, and low yield. The
fourth image is the paddock zoned using cluster analysis in which the
same three seasons of yield data plus the elevation and EM (38-vertical
mode) data have been used.
Figure 1: a) elevation map, b) electromagnetic induction readings,
c) zoning using three seasons of yield maps, and d) zoning using cluster
analysis with three seasons of yield map plus elevation and EM map.
[Note: Elevation in m; yield in t/ha; and EM shows electrical conductivity
Although there are many similarities between the different zoning methods
(after all, they both use the same three years of yield data), there are
also some marked differences. A big difference in this example is that
in the yield-only analysis each zone has a distinctly different mean yield,
whereas in the cluster analysis it can be seen that the red and green
zones have similar average yields.
The three zoning techniques described earlier require the grower to already
have collected various amounts of information about their paddocks. This
information can cost growers a significant amount of time and money in
buying a yield monitor and for consultants to carry out site mapping,
as well as in cleaning, storing and analysing the data sets.
It can also take several years for growers to build up a significant
set of yield maps for each crop across different seasons.
An increasing number of growers are happy to make this investment, having
confidence that the variability in their paddocks is sufficiently large
that they need to be actively learning how to manage it. However, many
other growers would like to know more about the yield variability of their
paddocks before making any capital investment. DPI has been investigating
the best way of providing this information to growers.
The methodology it has developed is based on estimating the variability
in crop yield from historical satellite digital images. These are not
a direct measure of yield but are used to estimate the crop biomass near
anthesis (flowering), which in turn is used to estimate yield variability.
The advantage of this system is that these images are relatively cheap,
especially if a group of growers in an area can share the cost. The prototype
system being tested requires the grower to provide the rotation history
for each paddock and the average paddock yields.
Analysis of the satellite data provides the grower with a map of the
estimated differences in yield found within each paddock. However, paddock
areas may perform differently in different seasons, so the analysis also
tells the grower if the zones tend to be consistently high or low yielding,
or tend to vary between high and low yields in different seasons, known
The main advantage of the proposed system is that it not only provides
growers with high, medium, and low-yielding zones, but enables these zones
to be quantified in terms of tonnes per hectare.
Growers can use this information to compare whether the high or low-yielding
areas in one paddock are higher or lower yielding than zones in another
paddock. Not only can growers then prioritise areas for treatment within
each paddock, but they can also develop a whole-farm planning approach
to sub-paddock zoning.
For example, in a season with a late break growers can quickly prioritise
which areas within specific paddocks are likely to make the greatest profit
and concentrate their sowing in those areas. Growers can therefore estimate
the economic benefits of making greater investment in precision agriculture
by evaluating the yield variability across their complete farm.
GRDC Precision Agriculture Initiative (SIP09)
GRDC Research Code: DAV00030
For more information: Dr Peter Fisher, 03 5833 5222, Peter.firstname.lastname@example.org