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Developing the workforce for next-generation agriculture

 * REEU Application
 * REEU Home
 * Contact
 * Application


AGTECH REEU: OFFERING UNDERGRADUATE RESEARCH AND EXTENSION EXPERIENCES IN
INNOVATIVE TECHNOLOGIES TO SUPPORT SUSTAINABLE AGRICULTURE AND DEVELOPMENT

AgTech REEU is a Research and Extension Experience for Undergraduates (REEU)
Program funded by the USDA for undergraduate students interested in smart
farming and innovative agricultural technologies. The program provides financial
support, educational opportunities, and research experiences to undergraduate
students, primarily those from underrepresented groups or from institutions with
limited undergraduate research opportunities.

Collaboratively hosted by Texas A&M University-Corpus Christi and Texas A&M
AgriLife Research & Extension Center at Corpus Christi (AgriLife), the program
aims to enhance the region's future workforce in next-generation agriculture.


APPLICATION DEADLINE: FEBRUARY 15, 2024


Request Info
Apply Now

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ABOUT THE AGTECH REEU PROGRAM


PROGRAM OBJECTIVES

 * Develop undergraduates’ knowledge of and skills in using IoTs, UAS, and
   geospatial data analytics in agriculture.

 * Train students with extension experience and professional development through
   government agencies and industry partners.

 * Inspire curiosity and confidence in STEM students to continue their education
   and enter the agricultural workforce.





PROGRAM BENEFITS

 * Hands-on, team-based, project-focused immersive research experience

 * An 8-week in-person summer internship that includes:
   
   * $500 weekly stipend
   
   * Travel to TAMU-CC
   
   * On-campus housing
   
   * Meal allowances up to $140/week
   
   * Pre- and post-program webinars during spring and fall semesters

 * Conference opportunities and travel support.

 * Training with extension experience & professional development through
   government entities and industry partners; field trips, workshops, guest
   speakers, and hands-on activities.

 * Research topics focused on Internet of Things (IoTs), Unmanned Aircraft
   Systems (UAS), and Geospatial data analytics for sustainable agriculture and
   development.
   
   
   


REEU RESEARCH PROJECTS


 * PROJECT #1: SUSTAINABLE SENSING, PROCESSING, AND COMMUNICATION ON EMBEDDED
   IOT DEVICES FOR INTELLIGENT AGRICULTURE
   
   
   Lead Mentor: Dr. Mehdi Sookhak
   
   Project Background: The emerging IoT brings new opportunities to empower
   next-generation agriculture. IoT can significantly extend the agricultural
   workforce with minimum cost and human involvement while maintaining excellent
   performance.
   
   Project Description: We will implement a small-scale embedded IoT network
   consisting of multiple low-power embedded IoT devices. Each embedded IoT
   device will be equipped with multiple environmental sensors (temperature,
   humidity, etc.), a microcontroller unit, and a transceiver to enable sensing,
   processing, and communication. Due to long-term cost, sustainability, and
   environmental concerns, we will power the devices with energy harvesters that
   scavenge ambient energy from solar, wind, and heat.
   
   Student Research Activities:
   
   1) Build up an energy harvesting powered IoT embedded system with
   off-the-shelf electronic components.
   
   2) Design smart sensing algorithms for the equipped sensors.
   
   3) Design and deploy data preprocessing algorithms for sensor data on the
   microcontroller.
   
   4) Enable wireless delivery of preprocessed data to the IoT edge server for
   further analysis.
   
   


 * PROJECT #2: UTILIZING UAS AND ASSOCIATED DATA ANALYTICS TO UNDERSTAND CROP
   GROWTH AND DEVELOPMENT
   
   
   Lead Mentor: Dr. Bhandari
   
   Background: Advances in analyzing UAS remote sensing images have contributed
   to improving our understanding of crop growth and development and yield
   predictions by the ability to collect high spatial-temporal data on plant
   morphological traits. However, ground-truth data collection, a key component
   in UAS applications, is tedious, laborious, and expensive. Automated systems
   equipped with IoT technology have shown the potential to gather high quality
   real-time data related to field conditions continuously. We envision that the
   integration of UAS with a ground-based IoT system will enhance our capability
   on understanding crop growth and developing management practices.
   
   Project Description: We will investigate challenges and their solutions in
   the combination of IoT and UAS for predicting crop yield. The IoT sensors
   will collect site-specific field conditions (for example soil moisture,
   canopy temperature, air temperature, and relative humidity). The UAS will
   gather data on canopy height, canopy cover, and vegetation indices. We will
   feed data from both platforms into mechanistic crop growth models to assess
   site-specific crop management practices and predict crop yield. This will
   help students learn the data integration approach from multiple devices, and
   we can demonstrate how advanced tools and techniques can be used to better
   understand crop growth and manage them efficiently and effectively.
   
   Student Research Activities:
   
   1) Develop a workflow combining IoT and UAS data for predicting crop yield.
   
   2) Process continuous and real-time field condition data from IoT sensors.
   
   3) Link the IoT and UAS data to crop growth models for crop growth and yield
   simulations.
   
   


 * PROJECT #3: A REAL-TIME GEO-VISUALIZATION AND ANALYTICS PLATFORM FOR SMART
   FARMING
   
   
   Lead Mentor: Dr. Huang
   
   Background: A real-time geo-visualization and analytics platform incorporates
   data collection, modeling, and visualization. This platform is critical for
   applying the IoT in agriculture but has not received much attention.
   
   Project Description: We will use ArcGIS Enterprise to build a platform on the
   ArcGIS GeoEvent Server to process the continuous real-time data collected
   from IoT sensors from Project #1. Further, we will design and build a spatial
   database to store and manage both sensors and UAS data and develop geospatial
   analytical tools to analyze and visualize the results from Project #2. In
   addition, we will leverage ArcGIS Dashboards to create geospatial dashboards
   to monitor and track farm field conditions as well as crop growth by
   integrating sensors and UAS from project #2.
   
   Student Research Activities:
   
   1) Connect IoT systems to the GeoEvent Server for ingesting sensor data.
   
   2) Create GeoEvent Services to analyze the sensor data in real-time.
   
   3) Implement a geospatial database to store and manage sensor and UAS data.
   
   4) Build an analytics dashboard that visualizes, monitors, and tracks farm
   field conditions and crop growth.
   
   


 * PROJECT #4: USING AGRICULTURAL EXTENSION TO IMPROVE THE SUSTAINABILITY AND
   PROFITABILITY OF ROW CROP PRODUCERS
   
   
   Lead Mentor: Dr. Mcginty
   
   Background: A key goal of the land grant university system is to provide
   educational outreach to stakeholders. Texas A&M AgriLife Extension Service is
   tasked with bringing science-based information and solutions to landowners
   and managers across the state through its network of 250 county offices.
   
   Project Description: During the spring and summer, county extension agents
   (CEA’s) provide educational programs and conduct result demonstrations in
   various row crops in south Texas. Topics of these programs and demonstrations
   are crop variety selection, pest management, and general crop management.
   
   Student Research Activities: Students will spend time with local CEA’s as
   they conduct onfarm result demonstrations in cotton, corn, and grain sorghum
   and learn how these demonstrations help to improve the sustainability and
   profitability of local producers. Students will also participate in
   educational programs where they will have the opportunity to present data
   from Projects 1-3 to local producers.
   
   


ELIGIBILITY REQUIREMENTS

We are seeking undergraduate students who are interested in research and
extension experiences focused on sustainable agriculture and development.
Applicants must meet the following qualifications to be eligible:

 * Must be a U.S. citizen or permanent resident.

 * Must be enrolled in an undergraduate degree program at a four-year university
   or community college.

 * Must be pursuing a degree in STEM, Agriculture, or related field of study.

 * Must have a cumulative grade point average of 2.8 or higher.

To be considered, applicants must submit:

 * A completed application form.

 * A 300-500 word research essay discussing why they are interested in the
   program.

 * An unofficial copy of their current transcript.

 * One recommendation letter from a professor, academic mentor, or an academic
   advisor.

Apply Now

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OUR PROJECT TEAM

Dr. Lucy Huang (PI): Dr. Huang is an associate professor of geospatial science
at the Computer Science Department at Texas A&M University – Corpus Christi

Learn more

Dr. Mehdi Sookhak (Co-PI): Dr. Sookhak is an assistant professor at the Computer
Science Department at Texas A&M University – Corpus Christi.

Learn more

Dr. Mahendra Bhandari (Co-PI): Dr. Bhandari is an assistant professor at Texas
A&M AgriLife Research.

Learn more

Dr. Joshua McGinty (Co-PI): Dr. McGinty is an associate professor and extension
agronomist at Texas A&M AgriLife Research.

Learn more

Jose L. Landivar (Senior Research Associate): Jose L. Landivar is a Senior
Research Associate at Texas A&M AgriLife Research & Extension Center. He holds a
M.S. in Geospatial Systems Engineering from Texas A&M University-Corpus Christi.
He provides workshops on the use of UAS in digital agriculture and develops
website tools for UAS data processing and sharing.

Learn more

Gina Concannon, CRA (Program Coordinator): Gina Concannon has been a research
administrator for over 20 years with several years dedicated exclusively to
projects devoted to providing students with meaningful, life-changing research
experiences.

Learn more

DeAnna Crites, CRA (Program Coordinator): DeAnna Crites has worked within the
TAMU System for almost 20 years with a career focused in pre- and post-award
administration.  This is her first experience in helping to administer a student
research experience and looks forward to learning and engaging with the students
and project personnel.

Learn more

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Click below to download a PDF copy of our AgTech REEU promotional flyer!

Program Flyer

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CONTACT US

Have questions about the AgTech REEU Program? Visit our Contact Us page to
inquire.

Contact

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This work is supported by the ARFI Education and Workforce Development Program,
Grant no: 2023-67037-40308, from the U.S. Department of Agriculture, National
Institute of Food and Agriculture. Any opinions, findings, conclusions, or
recommendations expressed in this publication are those of the author(s) and
should not be construed to represent any official USDA or U.S. Government
determination or policy.


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