This
article sort of gets it. We will have available manpower and we will
have field robotics able to physically replicate human dexterity in
collecting product. All this and a full palette of tools will also
be available to allow successful multicropping that naturally
maximizes productivity.
It is
also painfully clear that simple improvements to the stock in hand
will allow a doubling of the global population to 15,000,000,000
without doing anything special like greening all deserts.
We
have addressed this before but it is well worth repeating just in
case some other enthusiast wants to waltz out the idea that humanity
is going to run out of food.
Precision Farming
Gains Global Foothold
Lloyd Treinish, IBM
Thomas J. Watson Research Center
Date: 12 June 2013
Our world is getting
larger … and hungrier … with every tick of the clock.
Indeed, each second
the world's population grows by two more people, and by 2050, food
production must increase by at least 70 percent to keep pace.
Unfortunately, about
half of the world's food is never consumed due to inefficiencies
in the harvesting, storage and delivery of crops. Even in
developed nations, about 30 percent of purchased food ends up going
to waste, and supply-chain inefficiencies only exacerbate the
problem.
Certainly,
weather-related events — like the current and long-lasting drought
in portions of the U.S. — add further complexity to the science of
farming, as resultant crop damage, food supply shortages and rising
commodities prices frequently illustrate.
To help reverse this
sobering trend, and to generate enough food to meet the
ever-growing demands of a growing global population, today's — and
tomorrow's — agribusinesses need to embrace smarter farming
methods.
Fortunately, the
technology to do so is available — and working — right now.
Fueling better farming
is a practice known as precision agriculture, which uses extensive
data from a farmer's field and the surrounding region to help predict
weather conditions and optimize operations. While collecting
real-time data on weather, soil, health of crops and air quality is
important, as is the availability of equipment and labor, predictive
analytics can be much a smarter approach for making better farming
decisions.
Precision agriculture
can help farmers from Brunei to Brazil pinpoint the best time for
harvesting to mitigate crop damage and loss; determine how many
workers are needed at harvest time; and show how and when to deploy
delivery trucks to ensure immediate shipment — an especially
important factor in farmlands where the lack of paved roads can
paralyze distribution.
Those and
other smarter farming methods — including techniques used
early in the growing cycle — are reducing weather-related crop
damage by as much as 25 percent in some areas, ensuring that fewer
crops are wasted and more food makes it to the dinner table.
The development and
use of those predictive, analytics based techniques and technologies
is not limited to mega-farms. Small, family-run fields and co-ops,
worldwide, are also reaping better results by maximizing production
and reducing waste.
According to the U.S.
Department of Agriculture, weather-related incidents cause 90 percent
of all crop losses. Precision agriculture helps address that problem
by improving weather forecasting and modeling, and localizing it —
even within a particular farm. Knowing that it will rain in Nairobi,
Kenya is irrelevant if skies are clear above your farm just outside
of the city.
At IBM, we developed a
precision agriculture weather-modeling service using Deep Thunder,
our Big Data analytics technology, for local, customized,
high-resolution and rapid weather predictions. It gathers data from
sensors placed throughout fields that measure the temperature and
moisture levels in soil and surrounding air. That information is
combined with multi-spectral images of fields taken by advanced
camera systems from satellites and airplanes.
The system then
combines the field data with a diversity of public data from the
National Oceanic and Atmospheric Administration, the National
Aeronautics and Space Administration and the U.S .Geological Survey,
and private data from companies like Earth Networks. A supercomputer
processes the combined data and generates a four-dimensional
mathematical model derived from the physics of the atmosphere.
With high accuracy,
Deep Thunder can deliver hyper-localized weather conditions up to
three days in advance, with calculations as fine as a single mile and
as granular as every 10 minutes.
In practical terms, a
farmer armed with precise weather forecasting information may choose
to hold off on fertilizing an area of a farm expecting heavy rains;
or, he may irrigate only that portion of the farm that will not
receive rainfall. With 70 percent of the world's freshwater supply
already going to agriculture, every drop counts.
Also, better
understanding — and predicting — of weather effects on
transportation networks can help farmers make better decisions about
which routes and methods will be fastest to transport harvested food.
That is especially critical in countries like Brazil, where many of
the roads are unpaved and heavy rain can cause trucks to get stuck in
mud.
Coupling predictive
analytics and modeling techniques with other sophisticated farming
methods can prove to be quite beneficial when resources — like
water — are at a premium.
For instance, many farmers are now using methods like flow-through
irrigation, drip irrigation, micro-sprinklers and more
efficient
use of groundwater to increase yields. Getting more "crop
per drop" not only improves farm productivity but
provides enough return on investment to fund additional high-tech
solutions.
While the days of
farmers using the divining rod to find water are long since passed,
many farmers — especially in developing countries — still rely
too much on guesswork in making planting, irrigation and harvesting
decisions.
By combining
supercomputing and Big Data analytics with other technological
innovations, even farmers with modest means can bolster production
and profits. And all of us who eat will be grateful.
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