December 2020 - 13

water, optimize the time and effort
spent by crop specialists, and help
decrease some of the costs in the
food-production chain.
Current measuring techniques
involve collecting leaf samples and
transporting all of them to an off-site
location, where testers can use very
accurate, expensive pressure chambers;
and sampling and analyzing leaf
samples in the field using hand-held
pressure chambers, Karydis explained.
In the first category, leaf samples
can get mixed up, making it
impossible to track them back to the
specific areas of the field they came
from, Karydis said.
" In addition, the properties of the
leaf might vary given the time elapsed
between being sampled and being
analyzed, which in turn may yield
misleading results, " he said.
Hand-held instruments in the field
can be less accurate, but testing can
be done multiple times with different
leaves from the same plants, but this
method is time- and labor-intensive,
and must be undertaken by specially
trained personnel, he said.
" If we're going to
use precision
agriculture, we need
the most accurate
information-gathering
systems we can make. "
- Stefano Carpin, UC Riverside
" If we're going to use precision
agriculture, we need the most accurate
information-gathering systems we can
make, " Carpin said.
He has already worked with
colleagues at UC's Davis and Berkeley
campuses to create the robotassisted
precision irrigation delivery
(RAPID) system, which travels along
rows of crops adjusting irrigation
flows according
to sensor data
that tells the
robot precisely
what's needed for
each plant.
They'll use
STEPHANO
CARPIN
the same base
robot as RAPID,
but equip it
with GPS and
a pressure
chamber being
designed by the researchers at
Riverside, and pair it with drones that
can survey the fields and direct the
robot to areas of interest.
" Using this process, farmers could
survey plants all day long, even in
large fields, " Carpin said.
The four-year project will
support graduate students as well as
summer research opportunities for
undergraduates. The project has four
phases: development of the chamber;
developing machine-vision so the
robot can " see " the water coming from
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the leaf stems; coordinating multiple
robots - in the air and on the ground;
and evaluation.
The researchers plan to have
the first set of automated pressure
chamber prototypes fabricated by
Spring 2021, and to evaluate their
performance and refine designs in
controlled settings over spring and
summer 2021. They expect to have
a completed setup by winter 2022 so
they can begin controlled field testing.
" We have to be quick about it because
if we miss a peak growing season, we
have to wait another nine months for
the next one, " Carpin said. " We'd like to
be able to start testing next summer and
test every summer, and we need to be
able to maximize the tests. "
When all of the components have
been designed, the designs and code
will be open source, and all the data
collected during the project will
be made available to the scientific
community, the researchers wrote in
their proposal.
The project came about after Carpin
and Viers, director of the Center for
Information Technology Research in
the Interest of Society (CITRIS) at UC
Merced, had been talking with area
farmers about the challenges of growing
almonds and grapes. Professors Karydis
and Amit K. Roy-Chowdhury had been
hearing the same challenges from citrus
and avocado growers in the Riverside
area, so the four partnered up.
" This research partnership with
UC Riverside
will advance
our capabilities
in precision
food systems
broadly, and
most importantly
contribute to
the presence of
UC Merced and
CITRIS in the
emerging San Joaquin Valley ag-foodtech
sector, " Viers said.
" California agriculture presents
a challenge in terms of scalability, "
Carpin said, " but this is an exciting
collaboration because we'll get to
develop a system that will work on
different kinds of crops. " FGN
JOSHUA VIERS
FGN | DECEMBER 2020 | 13

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December 2020

Table of Contents for the Digital Edition of December 2020