Will Farmers Choose
Precision Farming or Convenience Agriculture?
Jess Lowenberg-DeBoer
Management time is a scarce
and expensive resource in all industries. A 2001 U.S. Department of Labor
survey shows that the average compensation for managers is around $60,000
annually. Experienced managers earn much more.
Average farm worker wages are around $20,000 annually. A recent article
in the USDA monthly publication Agricultural
Outlook suggested that adoption of precision agriculture technology was
relatively slow because of the management time require to implement this
technology. Katherine Smith, author of the USDA article, labeled farming
practices that economize on management time as “convenience agriculture”.
The Smith article considers
all types of “smart farming”, not just precision agriculture in her analysis.
By “smart farming” she means agricultural management that collects data,
analyzes that data, and implements farming practices based on that analysis, instead
of relying on rules of thumb, fixed application schedules or general
recommendations. She includes integrated pest management (IPM) as another
example of smart farming.
The Glyphosate Paradox - The management time hypothesis could help explain
some disparities in adoption of technology in agriculture. In particular it
could help explain the difference between adoption of biotechnology products,
which typically require little management effort, and information technology,
which often requires substantial analysis and decision-making. The difference in adoption between glyphosate
(i.e. Roundup Ultra, Touchdown, Rattler, or Rodeo) resistant soybeans and
precision farming technologies such as yield monitoring or intensive soil
sampling is a good example. Glyphosate resistant soybeans are planted on
over 70% of U.S. soybean area in spite of the fact that there have been
marketing problems and they often do not show production benefits when compared
to conventional soybeans. In some cases glyphosate resistant soybeans
suffer from lower yields (i.e. yield drag) and may have higher weed control
costs than conventional soybeans if glyphosate must be applied more than
once. Many farmers say that they use glyphosate resistant soybeans
because they are “so easy to grow”. In other words, glyphosate resistant
soybeans do not require as much management time as conventional soybeans. While
the per unit area returns may be lower, they allow a producer to manage more
area. In contrast, precision agriculture adoption has been relatively low, in
spite of good evidence of profitability for some aspects.
One issue is that none of the economic studies of precision agriculture have explicitly accounted for the management time needed to implement these technologies. In fact very few of them have accounted for any additional time requirement (see review of these studies by Lambert and Lowenberg-DeBoer under publication). The most common practice has been to treat farm labor as a fixed resource that would not change with the technology and omit it from partial budget calculations. One of the key problems in trying to introduce charges for management time is that there is no good data on the amount of management time that various precision farming tools require. Some practices that are primarily outsourced (e.g. grid soil sampling, variable rate fertilizer) probably require very little management time. Practices that primarily affect logistics or operations efficiency, but do not require data analysis or decision-making (e.g. DGPS guidance, "lightbars"), also do not require much management time.
How much extra time does precision farming take? - Practices that must be
implemented by the producer and those which require analysis and decisions
probably require much more management time. In the U.S. Midwest, where it is
common for farmers to own combine harvesters, someone on the farm must usually
invest time if yield monitoring is to show any benefit. They must learn how to
operate and calibrate the equipment. They must learn how to make yield maps and
how to use yield map data to diagnose problems or interpret on-farm trial
information. It is not uncommon to hear first time yield monitor users explain
that, “I spent all winter going through those yield maps.”
The charge for management
time is difficult to determine in traditional U.S. farming operations in which
producers provide both labor and management. It is common, even for producers
with relatively large operations (> 5,000 acres of row crops), to spend some
time operating equipment. The value of time in bottleneck planting and
harvesting periods can be estimated by the opportunity cost (e.g. shadow prices
in linear programming models or the cost of hiring additional labor), but what
is the value of the flexible time in the winter months used to study yield
maps. Is it the $10/hr that might be earned in part time seasonal work? Or is
it the $30/hour or more for management time?
The relatively low returns
of most stand-alone precision farming practices (e.g. variable rate P & K,
variable rate seeding of maize and soybeans) means that they could not support
much management time. But what about the more profitable integrated precision
agriculture practices? On the 526 ha Sauder corn and soybean farm, the GPS
treatment would earn about US$18,000/year more than the conventional whole
field management. This would pay for almost three full months of the average
American managers time. Three months is probably more than enough to analyze
the soil test data, to implement and interpret the on-farm trials that Sauder
used to develop his farm specific soil fertility management plan, and to make
the necessary decisions. This suggests that while including the cost of
management time may mean that returns to precision farming technologies are somewhat
lower than previously thought, it does not seem to entirely exclude adoption of
the technology.
A related issue is the
availability of management time. Most U.S. producers did not become farmers in
order to spend time in front of the computer analyzing spatial data. They
became producers in part because they like the active, out door life that
farming offered. This may mean that they are relatively unwilling to put time
into management or equivalently that they must be compensated at a higher than
average rate to make it worth their while. Risk may also be an issue.
Alternative uses of time for U.S. producers (e.g. seasonal off-farm work,
livestock raising) have more certain compensation than the relatively new,
immature precision agriculture technology. Management time is another reason to
expect higher adoption of precision agriculture on larger farming operations.
There are economies of scale in data analysis and decision-making. Larger
operations can spread the management time cost over more area.
The apparent reluctance of
US producers to commit management time to precision agriculture and other types
of smart farming may create an opportunity for crop consultants. If these
consultants are willing to learn precision agriculture skills and to spend time
in front of the computer, they may be able to provide cost effective crop
management advice. This has benefits for all concerned. Crop consulting could
create relatively high paying jobs in rural areas and those services could
allow producers to benefit from smart farming without becoming “nerds”.
Conclusions - Both
availability and cost of management time appear to be issues for adoption of
precision farming technology. Some precision farming technologies appear to use
very little on-farm management time under U.S. conditions, either because they
are usually out-sourced, or because they mainly affect logistics and do not
require data analysis. Some stand-alone precision farming technologies yield
low returns even without charging for management time and they would look even
worse if management time were deducted. For the most profitable of precision
farming practices returns seem to be high enough to pay average management
costs. The willingness of traditional U.S. producers to retrofit and undergo
extensive training (e.g. computer analysis and decision-making) may be a
greater constraint than the opportunity cost of the time because many producers
have chosen agriculture for the active outdoor lifestyle and are reluctant to
spend time in front of a computer. The apparent unwillingness of U.S. producers to
commit management time to precision agriculture may signal an opportunity for
out-sourcing the data analysis and recommendation development.
References:
Lambert, D. and J.
Lowenberg-DeBoer. 2000. Precision Farming Profitability Review, Site-Specific
Management Center, Purdue
University, West Lafayette, IN, USA, www.purdue.edu/ssmc.
Smith,
Katherine. 2002. “Does Off-Farm Work Hinder ‘Smart’ Farming? USDA Agricultural Outlook, Sept., p.
28-30,
(www.ers.usda.gov/publications/agoutlook/sep2002/ao294i.pdf).