AeroVironment & California State University, Fresno Begin Field Research to Identify Water Stress in Almond Production Using ...
December 07 2016 - 9:10AM
Business Wire
- AeroVironment and Fresno State to study
the correlation between aerial multispectral data and hydration
data related to water stress
- Results should identify varying levels
of water stress in almond trees and which types of imagery might
enable almond producers to make more effective water management
decisions
- Project running Dec. 2016 – Aug. 2017;
final results to be announced in September 2017
AeroVironment, Inc. (NASDAQ: AVAV), a global leader in unmanned
aircraft systems for both military and commercial applications,
today announced it has begun a year-long study with California
State University, Fresno to research how unmanned aerial vehicle
(UAV) imagery and analytics could potentially detect varying levels
of water stress in almond trees and give producers smarter insights
to make more effective in-season decisions regarding water
management.
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AeroVironment and Fresno State begin
field research using advanced drone imagery and data analysis to
identify water stress in almond production (Photo: Business
Wire)
“Improved crop management is a major goal for all growers,
including almond producers,” said Jon Self, vice president,
AeroVironment Commercial Information Solutions. “Working closely
with the plant science experts at Fresno State’s globally
recognized Jordan College of Agricultural Sciences and Technology,
we look forward to developing a reliable and effective means of
correlating multispectral data with almond tree hydration data to
provide growers with better insight so they can proceed with
certainty.”
Almonds represent the state’s second largest agricultural
commodity, valued at $5.33 billion in 2015 according to the
California Department of Food and Agriculture. The Almond Board of
California (ABC) reports that almonds account for approximately 14
percent of California’s total irrigated farmland. To assure
long-term sustainability, almond producers are increasingly turning
to advanced technologies to push the envelope of water use
efficiency while serving as good stewards of this limited
resource.
AeroVironment will deploy its Puma™ UAV configured with a 24
megapixels photogrammetric camera and 6-channel multispectral
sensor to capture data and aerial imagery of the Fresno State
University Agricultural Laboratory (UAL) orchards. AeroVironment’s
DSS™, a cloud-based analytics platform, will then process and
analyze the data for correlation with ground measurements. The team
will test several linear and non-linear geospatial data algorithms
for statistical correlation and predictability validated by
ground-level hydration data. Fresno State researchers and UAL
campus farm staff will closely monitor the hydration levels of
almond trees as well as environmental and crop conditions using a
variety of soil and plant sensors.
Together, the team aims to gain a greater understanding of what
types of imagery and data output will allow almond producers to
make better decisions regarding the fine balance between water
management and the needs of the crop to obtain optimal yield.
Results of the year-long study are expected to be available in
September 2017.
Please visit www.avinc.com/cis for more information on
AeroVironment Commercial Information Solutions, including its
Quantix drone and Decision Support System.
About AeroVironment, Inc. (AV)
AeroVironment (NASDAQ: AVAV) provides customers with more
actionable intelligence so they can proceed with certainty. Based
in California, AeroVironment is a global leader in unmanned
aircraft systems, tactical missile systems and electric vehicle
charging and test systems, and serves militaries, government
agencies, businesses and consumers. For more information visit
www.avinc.com.
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version on businesswire.com: http://www.businesswire.com/news/home/20161207005468/en/
AeroVironment, Inc.Steven Gitlin,
+1-626-357-9983pr@avinc.comorFor AeroVironment, Inc.Ron Piskula,
+1-919-870-5718rpiskula@gscommunications.com
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