Successful Farming – August 2019

competitive? As agriculture’s
existing players work on
a resolution, outsiders like
IBM are emerging with their
own approach.
Launched in 2018, the
Watson Decision Platform
for Agriculture leverages
the power of artificial intel-
ligence (AI) to analyze silos
of data and then generate
evidence-based insights.
Watson begins by creating
a digital representation of a
field. This electronic field
record (EFR) includes soil,
equipment, farm practice
and workflow, and imag-
ery data. It can also accept
weather data from The
Weather Company.
Applying AI, machine
learning, and advanced
analytics to the EFR, the
platform highlights key
factors that might affect crop yields like soil temperature,
moisture levels, crop stress, pests, and diseases. Ultimately,
each EFR becomes a digital twin of everything that happens
on Paulman’s 113 fields. A unified dashboard lets him easily
see and monitor data as well as receive alerts when critical ele-
ments like weather could affect a crop.
The difficulty with many of the decisions Paulman tries
to make is that they are biologically based. “They are almost
always influenced by weather we don’t yet know. Having the
ability to forecast conditions has to be an integral part of any
decision platform,” says Kenneth Sudduth, research agricul-
tural engineer at USDA-ARS.
In addition, the process has to be automated from start to
finish. Technologies like automatic guidance, shutoffs, and
boom height control – systems that had little or no direct hu-
man control – saw fairly swift adoption because they improved

the workflow without re-

quiring operator interaction.

Today, too many ap-

plications require farmers

to input information over

and over again. “Every time

farmers make an entry, there

is a chance they’ll get it right,

but there is also a chance

they’ll get it wrong,” says

Michael Gomes, VP business

development IoT, Topcon

Agriculture.

More often than not, the

most common variety plant-

ed is labeled “one” because

the window to get

that seed in the

ground is continu-

ally shrinking.

It’s a painful

process, and farm-

ers are tired of it.

If farmers can

select from a pick

list, Gomes says,

their risk of get-

ting it wrong is a

WHAT IS DIGITAL AGRICULTURE?

DIGITAL AGRICULTURE COMBINES MULTIPLE

DATA SOURCES WITH ADVANCED CROP AND

ENVIRONMENTAL ANALYSES TO PROVIDE

SUPPORT FOR ON-FARM DECISION MAKING.

Source: Ohio State University

whole lot lower than having

to punch it in letter by letter

or ensuring they call it the

same exact thing every time.

“Only about 8% of the

data being collected is

actually usable,” says John

Fulton, associate professor at

Ohio State University.

the power of ai

T

o make the analytics

better, a much cleaner

data set is needed, and many

believe AI can take produc-

ers there. Applying it to

data provides Paulman with

myriad new abilities.

From the air, he can deploy

a drone to capture a field of

corn and use AI visual recog-

nition to identify crop disease

or a pest infestation. From the

ground, plants can be photo-

graphed up close, so Paulman

can react in real time.

“Simplifying the process

also enables agronomists

Paulman Farms

in Sutherland,

Nebraska, has

been testing

IBM’s Watson

Decision

Platform for

Agriculture on

its irrigation

system. The

technology helps

Roric Paulman

identify the best

practices for

the operation’s

irrigated acres

to maximize the

limited supply of

water.

42 Successful Farming at Agriculture.com |August 2019