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By Fred MillerU of A System Division of Agriculture@AgNews479
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Download related PHOTOS from Flickr: https://flic.kr/s/aHsmGRDHuT
FAYETTEVILLE, Ark. – A team of researchers from the University of Arkansas System
Division of Agriculture and the University of Arkansas College of Engineering are
designing tiny sensors that can be placed in corn stalks to monitor water, nitrogen
and potassium needs in real time.
The data collected from those sensors — matched with geographic, weather and other
environmental data — will feed machine learning software to develop models that will
be able to predict when a crop will need those inputs before the conditions exist.
Those predictive models can help corn growers give their crops exactly the water and
nutrients they need, before they experience stress, to achieve the best possible yields
without wasting resources.
The collaborative research by the division’s Arkansas Agricultural Experiment Station
and the university’s College of Engineering is supported by the Chancellor’s Discovery,
Creativity, Innovation and Collaboration Fund.
Dealing With Stress
“By the time you see drought stress or nutrient deficiency, you’ve already lost some
yield,” said Trent Roberts, associate professor of crop, soil and environmental sciences
for the Arkansas Agricultural Experiment Station.
Farmers deal with these issues now in one of two ways, Roberts said. “A high-inputter
is proactive, over-applying water and nutrients in order to avoid stress or deficiencies.”
That approach maintains optimal yields, he said, but it comes with high costs for
fertilizers, fuel to run equipment and pump water.
“A low-inputter waits until he sees stress or nutrient deficiency,” Roberts said.
“He may save money on the front end, but may lose yield at harvest.”
A model that can predict a crop’s water and nutrient needs before they occur can cut
the costs of over-applying without losing yield, Roberts said.
To develop such a system, Roberts joined a team of researchers that includes Jia Di,
professor and 21stCentury Research Leadership Chair in the department of computer science and computer
engineering; Alan Mantooth, Distinguished Professor and 21stCentury Research Leadership Chair, and professor Simon Ang, both from the department
of electrical engineering; and Jie Xiao, associate professor of chemistry and Arkansas
Research Alliance Scholar.
They developed a tiny sensor that is inserted into a cornstalk near its base. Di said
they began with dummy sensors to test materials and dimensions that could accommodate
the electronics without impeding the growth and development of the plant.
“The electronics can be very small,” Di said, “but the limit on miniaturization is
the antenna. It must be large enough to send a signal to a base station.”
The resulting sensor looks like a slightly oversized thumbtack. The current prototype
was manufactured by the University of Arkansas High Density Electronics Center and
it relies on an external power source. Di said they have developed a microbattery
that will be integrated into the sensor and the electronics in the next prototype
to be produced in October.
The sensor is able to measure specific parameters in real time, Roberts said. “We’re
focusing on drought stress, nitrogen content and potassium content.”
To measure that information now, Roberts said, requires researchers to take tissue
samples, send them to a lab and wait for test results. “It’s time consuming and expensive,”
“So far, we’ve been testing proof of concept,” Roberts said. “And we have a viable
To develop predictive models, Di said, the data from the sensors will be fed into
a machine learning program along with environmental data, including soil texture,
planting date, weather data, geographic location and other information that affects
plant growth and productivity.
The more information is gathered over time, Di said, the more accurate the predictive
“Now that we have a working sensor,” Roberts said, “the next step is to see how many
we need in a field to get useful data. We’re right in the middle of the process.”
Di said the research team will also be determining the best means of collecting the
data. The sensors are designed to transmit to a base station, but Di said he doesn’t
think putting that station permanently in the field is the best option. “I think we’ll
probably attach the base station to a tractor or truck and drive around the field
to collect the data.”
Each sensor has an ID code so they’ll know where in a field each data set came from.
“Next, we want to develop a sensor that dissolves in the field after harvest,” Roberts
said. That saves the time and labor of finding and removing each one year after year.
Right now, the sensors are limited to use in corn. Di said the sensors are too large
to insert into crops with smaller stalks or stems. “But advances in electronics could
lead to smaller sensors that could be applied to smaller plants,” he said.
To learn more about Division of Agriculture research, visit the Arkansas Agricultural
Experiment Station website: https://aaes.uark.edu. Follow us on Twitter at @ArkAgResearchand Instagram at ArkAgResearch.
About the Division of Agriculture
The University of Arkansas System Division of Agriculture’s mission is to strengthen
agriculture, communities, and families by connecting trusted research to the adoption
of best practices. Through the Agricultural Experiment Station and the Cooperative
Extension Service, the Division of Agriculture conducts research and extension work
within the nation’s historic land grant education system.
The Division of Agriculture is one of 20 entities within the University of Arkansas
System. It has offices in all 75 counties in Arkansas and faculty on five system campuses.
The University of Arkansas System Division of Agriculture offers all its Extension
and Research programs to all eligible persons without regard to race, color, sex,
gender identity, sexual orientation, national origin, religion, age, disability, marital
or veteran status, genetic information, or any other legally protected status, and
is an Affirmative Action/Equal Opportunity Employer.
Media Contact: Fred MillerU of A Division of AgricultureArkansas Agricultural Experiment Station(479) firstname.lastname@example.org