From: University of Illinois College of Agricultural, Consumer and Environmental Sciences
January 13, 2022 -- Synthetic nitrogen
fertilizers transformed agriculture as we know it during the Green Revolution,
catapulting crop yields and food security to new heights. Yet, despite improvements
in crop nitrogen use efficiency, fears of underperformance spur fertilizer over-application
to this day. Excess nitrogen then ends up in waterways, including groundwater,
and in the atmosphere in the form of potent greenhouse gases.
Predicting the amount of nitrogen needed
by a particular crop in a particular year is tricky. The first step is
understanding crop nitrogen status in real time, but it's neither realistic nor
scalable to measure leaf nitrogen by hand throughout the course of a season.
In a first-of-its-kind study, a
University of Illinois research team put hyperspectral sensors on planes to
quickly and accurately detect nitrogen status and photosynthetic capacity in
corn.
"Field nitrogen measurements are
very time- and labor-consuming, but the airplane hyperspectral sensing
technique allows us to scan the fields very fast, at a few seconds per acre. It
also provides much higher spectral and spatial resolution than similar studies
using satellite imagery," says Sheng Wang, research assistant professor in
the Agroecosystem Sustainability Center (ASC) and the Department of Natural
Resources and Environmental Sciences (NRES) at U of I. Wang is lead author on
the study.
"Our approach fills a gap between
field measurements and satellites and provides a cost-effective and highly
accurate approach to crop nitrogen management in sustainable precision
agriculture," he adds.
The plane, fitted with a top-of-the-line
sensor capable of detecting wavelengths in the visible and near infrared
spectrum (400-2400 nanometers), flew over an experimental field in Illinois
three times during the 2019 growing season. The researchers also took in-field
leaf and canopy measurements as ground-truth data for comparison with sensor
data.
The flights detected leaf and canopy
nitrogen characteristics, including several related to photosynthetic capacity
and grain yield, with up to 85% accuracy.
"That's close to ground-truth
quality," says Kaiyu Guan, co-author on the study, founding director of
the ASC, and associate professor in NRES. "We can even rely on the
airborne hyperspectral sensors to replace ground-truth collection without
sacrificing much accuracy. Meanwhile, airborne sensors allow us to cover much
larger areas at low cost."
Remote sensing picks up energy reflected
from surfaces on the ground. The chemical composition of leaves, including
their nitrogen and chlorophyll content, subtly changes how much energy is
reflected. Hyperspectral sensors detect differences of just 3 to 5 nanometers
across their entire range, a sensitivity unmatched by other remote sensing
technologies.
"Other airborne remote sensing
technologies pick up the visible spectrum and possibly near-infrared, just four
spectral bands. That's not even close to what we can do with this hyperspectral
sensor. It's really powerful," Guan says.
The researchers see a use for their
findings in the popular Maximum Return To Nitrogen (MRTN) corn nitrogen rate
calculator.
Wang explains, "Under our approach,
we can detect the nitrogen status of the crop and make some real-time
adjustments for the agricultural stakeholders. MRTN provides recommended
nitrogen fertilization rates based on the economic tradeoff between soil
nitrogen fertilizer rates and end-of-season yield. Our remote-sensing approach
can feed plant nutrient status into the MRTN system, enabling real-time crop
nitrogen management. It can potentially shift the current recommendations based
on pre-growing season, soil-centric fertilization to a diagnosis based on
real-time plant nutrition, improving agroecosystem nitrogen use
efficiency."
Importantly, the research team worked
out the best mathematical algorithm to detect nitrogen reflectance data from
the hyperspectral sensor. They expect it will be put to use as newer technologies
come on board.
"NASA is planning a new satellite
hyperspectral mission, as are other commercial satellite companies. Our study
can potentially provide the algorithm for those missions because we already
demonstrated its accuracy in the aircraft hyperspectral data," Wang says.
Guan says bringing this technology to
satellites is the end goal, enabling a view of every field's nitrogen status
early in the growing season. The advancement will allow farmers to make more
informed decisions about nitrogen side-dressing.
Ultimately, of course, the goal is to
improve the environmental sustainability of nitrogen fertilizers in agronomic
systems. And Guan says precision is the way to get there.
"Essentially, you can't manage what
you can't measure. That is why we put so much effort into this
technology."
https://www.sciencedaily.com/releases/2022/01/220113120736.htm
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