Brief Summary of Minutes of Annual Meeting

Brief summary of minutes of annual meeting

Opening

Dr. Jennifer Lachowiec began the meeting with a land acknowledgement, welcome, introduction and agenda. Montana State University Vice President, Dean, and Director of the College of Agriculture and Montana Agriculture Experimental Station reported on the state of MSU’s enrollement and the new processing and precision agriculture efforts at MSU including reviving the ag engineering program.

Two guest speakers from Montana State University presented.

Lochlinn Ermatinger

Wheat stem saw fly has estimated damage of 80 million dollars per year in Montana (350 in total range). WSS infestation leads to lodging. Utilzing drone and satellite imagery to estimate location of wheat stem sawfly. Advocated for the use of N-way partial least squares regressio since it appropriately models repeated measures and response as a proportion.

Dr. Jared Beaver: MSU Wildlife Extension: Tech and Life Applications

Applied research to solve issues human-wildlife-livestock issues. Rural working lands: Water/food sustainability, climate resiliency. Wildlife values are changing.

Wildlife-Livestock: Depredation, disease, resources. Realtime detection and monitoring in Paradise valley of Montana and contrasting game cameras for reliability and accuracty.

Drones can fairly accurately capture animal density. Size variation, shape of thermal signature, group size can identify animals. Feral pigs vs. deer separable via AI classification.

University Updates

1. Montana State University: Jennifer Lachowiec
2. Oklahoma State University: Phil Alderman (virtual)
3. University of Florida: Moses Chilenje
4. USDA-ARS, Prosser, WA: Max Feldman
5. Virginia Tech: Maria Balota
6. South Dakota State University: Maitiniyazi Maimaitijiang
7. North Carolina State University: Robert Austin
8. University of Kentucky: Michael Sama
9. Washington State University: Lav Khot
10. University of Idaho: Johnny Li
11. Texas A&M: Mahendra Bhandari
12. Mississippi State: Alex Thomasson
13. University of Arkansas: Cenzig Koparan

Lunch Break

Business Meeting

Ten early career researchers joined this year’s meeting because of S1069 was awarded $15,000 in funds as an award for achivements.

Past minutes: Minutes summarized. Motion passes to approve minutes. 

Officers

• Current officers through September 2024 and move up a position each year:
  • Chair: Jennifer Lachowiec
  • Vice-Chair: Joshua Jackson (to host/coordinate meeting 2025)
  • Secretary: Mahendra Bhandari (to host/coordinate meeting 2026)

• Nominations for secretary (host in 2027)
• Giverson Mupambi was nominated, seconded, and accepted nomination.
• Next chair was to be Josh Jackson, who is not in attendance.

Location of next S1069 meeting:

• We were contacted by NCERA180 (Precision Ag Technologies for Food Agriculture Energy Production) about the possibility of joint meeting at South Dakota State University.

• Alex Thomasson: Periodic meeting of multi-state groups brings people together. Regional Director of Southern Ag Research Stations endorses it. Unsure if multi-state groups often meet together.
• Jennifer Lachowiec: It also bridges funding issues for some groups as they are part of both organizations.
• Max Feldman moves to approve joint meeting, all in favor. Jennifer Lachowiec will pass the message along to NCERA.
• S1069 Member Maitiniya Maimaitijian is at South Dakota State University and will be liaison for the meeting with colleagues there.
• If the joint meeting does not come together, Michael Sama, possibly with Josh Jackson, will host at University of Kentucky.

Review of proposal milestones and progress towards them

• 2023 Milestones
• A. Funded project for collaborative development of extension/outreach training materials from corporate, state, and/or federal resources.
• None noted
• B. Funded project for collaborative research from corporate, state, and federal sources.
• Texas A&M has potential joint projects with OK State University.
• Small seed project between Max Feldman (USDA) and Oregon State and Mississippi State.
• C. Functional and accessible website.
• NIMMS website is sufficient.
• Thomasson: This point is more relevant to the hiring of Anne Porter. More websites is a hassle.
• Lachowiec: Diversify NIMs website.
• Balota: Website would not upload videos/photos, only text.
• Conclusion: add more information to the website and inquire about linking to share out information
• 2024 Milestones:
• At least one set of extension/outreach training material to meet the needs elucidated from the needs assessment conducted in earlier years.
• Jennifer: There are many extension publications showcased in updates.
• At least three submitted multi-university research proposals to address needs elucidated from the assessment conducted in earlier years.
• Thomasson: Need to facilitate interstate grad student communication via coordinated meeting or other mechanism.
• Organize with commodity meetings or other meetings or host an additional conference
• Coconut grant from AG2PI funded S1069 grad students at the 2023 meeting at Virginia Tech.
• Feldman: 30-50k per year for potato projects. Some goes to students for training.
• Lav Khot: USDA commissions might not fund external meetings. NIFA is already connected. Can NIFA come up with the money to send the students? Write a conference proposal.
• Li: Need to make a compelling case that students will benefit from meeting. Could get 50k for conference.
• Thomasson willing to take lead on conference proposal. Lav will support.
• Lachowiec: UAS in Ag CAP
• Would NIFA fund a CAP project that isn’t part of a commodity?
• Alter the way we host S1069
• Maria: Have graduate students present as a mini-conference as part of the presentation. Move updates to the form of a report and replace time with graduate student presentations.
• Feldman: 1^st day: presentations focused on graduate student presentations. 2^nd day business meeting and updates.
• At least one customizable course curriculum (up to 3 credits) and pertinent education material/modules development to meet the needs elucidated from the assessment conducted in earlier years.
• Mahendra: Put together a small handbook on UAV operations and data collection. Allows you start a phenotyping program from scratch. Moving toward making non-DJI handbooks for different platforms to give people options. Possible source of money to train IPM extension agents.
• UAV manuals for feature collection and data processing
• On researchgate

• There is a need for refined data collection protocols across multiple states. Data analysis can also be standardized. Dataset needs to be understandable across disciplines.

• Feldman: Submitted proposal to regional commodity board for multiple positions with DJI drone and pay for student training and data analysis jam. Commodity Board did not fund. WSDA Crop is another option.
• OR, WA, ID work closely together. TA&M could also join together in data analysis.
• Lav: Can we make consistent curriculum for 1 day training? Need to communicate clearly to extension agents and students.
• Jennifer: Imagery processing through a CAP?
• Noted that we should reword future proposals to include “submission” of proposals, rather than “funding” of proposals

Presentations & Demonstrations from Local Companies

Bridger Photonics: Nathan Greenfield

Originally funded by grants and gov contracts for long- and short-range laser systems. 2019: Gas mapping lidar. Looking at efficiency of oil and gas supply chain. 2022: GML V2. Leak detection and repair. Emission analytics.

Resonon: Alexandre Lussier

Making hyperspectral imagery products commercially available.

Pika-L can be used indoors w/out radiometric calibration and outdoors with. Gimbal can be used if very high winds, but generally not needed.

Vision Aerial: Phil and Mots

US-made unmanned aerials systems. Onboard dampening systems for different frequency vibrations. All onboard controls. Full system will run ~$45k. Outdoor demonstration.

Day 2 Field Trips

Visit to Montana State University Barley Malt and Brewing Lab

Visit to Montana State University Red Bluff Research Ranch

Working together, in small or large groups, the S-1069 Team made significant progress towards discovery if new aspects of UAS applications in breeding, and agriculture production and natural resources; development of training materials for UAS applications; building platforms for UAS-based data analysis, storage and sharing; and extension and outreach for expansion of UAS-driven agriculture production.

The team is leading research using hyperspectral imagery, and machine learning in agricultural research and practice. A common theme across the discussions was the focus on precision agriculture, where tools such as remote sensing, deep learning, and AI are being leveraged to improve crop monitoring, yield prediction, and stress detection. These innovations are being applied to a wide range of crops, including wheat, corn, potatoes, and rice, and are also extending into areas like soil nutrient management, ecological sustainability, and water quality improvement.

Several projects emphasized the importance of developing standardized protocols for UAS and the need for robust data management frameworks to handle the growing influx of information from various sensors and imaging systems.

Moreover, there is a notable effort to bridge the gap between research and practical application, with many projects involving outreach initiatives to educate the next generation of scientists and practitioners. This collective push is leading to the creation of valuable datasets, software tools, and patents, which are expected to have lasting impacts on both academic research and real-world agricultural practices, driving towards more sustainable and efficient food production systems.

Presentations given

1. Lachowiec J, Feldman MJ, Matias FI, LeBauer D. Empowering high-throughput phenotyping using drones/UAS. AG2PI community event UAV/UAS/Drone restrictions for agricultural research and how different organizations are dealing with them. January 8, 2024.
2. Bruxellas, B., Austin, Milla-Lewis, S., UAVs, Machine Learning, and Deep Learning for Phenotypic Evaluation of Turfgrass, 2024 AI in Agriculture and Natural Resources Conference - College Station, TX - Apr. 15-17
3. Bruxellas, B., Austin, R., Woodley, A., & Heitman, J. L. (2022) UAV-Based Characterization of Micro-Topographic Features for Use in Estimating Soil Moisture and Nitrous Oxide Emissions in Agriculture Fields. ASA, CSSA, SSSA International Annual Meeting, Baltimore, MD. https://scisoc.confex.com/scisoc/2022am/meetingapp.cgi/Paper/143615
4. Howell A.W., Durham, M.W., Sperry, B.P., and Richardson, R.J., Aquatic Plant Management Society: Identifying Optimal Spray Components for Waterhyacinth Control with Unoccupied Aerial Sprayers
5. Hall, S. and D. Smith, 2024 (upcoming). Novel aquacultural applications for individual and fleets of autonomous surface vehicles. Accepted for presentation at AQUA 2024, Copenhagen Denmark (Organized by European Aquaculture Society and World Aquaculture Society, August 26-30, 2024
6. Hall, S., March 2024. Research and Extension at the Marine Aquaculture Research Center, presented at North Carolina Aquaculture Development Conference New Bern, NC. Included discussion of automated and autonomous systems being used and researched with focus on aquaculture and coastal management.
7. Chowdhury, S., 2024 (Hall on PhD committee). Assessing the impact of oyster reefs on local shallow water dynamics in a tidally controlled environment, WRRI, March 2024.  This analytical approach was matched with data from both autonomous and automated surface vehicles and aerial data collection with a focus on water quality for oysters.
8. Schrader, M. J., Amogi, B. R., and Khot, L. R. 2023. Dronesonde based temperature inversion strength monitoring and grower decision support tool for frost mitigation in perennial specialty crops. Paper no. 2301273, ASABE 2023 Annual International Meeting, Omaha, NE, July 9-12, 2023 (Oral Presentation).
9. Schrader, M. J., Bhalekar, D. G., Sahni, R., and Khot, L. R. 2023. Efficacy of drone with angled spray boom for applications in modern VSP trained vineyards. Paper no. 2301268, ASABE 2023 Annual International Meeting, Omaha, NE, July 9-12, 2023 (Oral Presentation).
10. Schrader, M. J., Molaei, B., Khot, L. R., Zhang, Q., Peters, R. T., Keller, M., and Stockle, C. 2023. Smart Farm concepts into action: Technological challenges faced to implement Smart Vineyard in WA State. Paper no. 2301274, ASABE 2023 Annual International Meeting, Omaha, NE, July 9-12, 2023 (Oral Presentation).
11. Yumnam, K., Gorthi, S., Amogi, B. R., Hoheisel, G.-A. and Khot, L. R. 2023. Drone-sonde and ground sensing-based evaluation of wind machines effectiveness in Sweet Cherry spring frost mitigation. Paper no. 2301395, ASABE 2023 Annual International Meeting, Omaha, NE, July 9-12, 2023 (Oral Presentation).
12. Yumnam, K., Kothawade, G. S., Blanco, V., Chandel, A. K., Kalcsits, L. and Khot, L. R. 2023. Developing understanding on suitability of aerial multispectral and thermal imagery in mapping crop water status of apple trees. Paper no. 2301342, ASABE 2023 Annual International Meeting, Omaha, NE, July 9-12, 2023 (Oral Presentation).
13. Li, L. Invited guest lecture, University of Idaho, November 7, 2023, ‘Precision Agriculture Research in Idaho: Assessing Crop Health and Evapotranspiration with Time-series High-resolution UAV Remote Sensing Imagery. Idaho Water Resource seminar.
14. Li, L. Invited guest lecturer, University of Idaho, Feb 7, 2023, ‘Advance Robotics Sensing, Control and ​Computing For Sustainable Agriculture and ​Infrastructural and Manufacturing Management’, Mechanical Engineering Department Graduate Seminar Series.
15. Li, L. Invited Talk “Advance Robotics Sensing, Control and Computing for Smart Agriculture" by 2023 School of Mechanical and Materials Engineering Seminar Series at Washington State University, September 21, 2023
16. Ladino, K.S., Sama, M.P. 2024. Automating Ground Control Point Detection in UAS Imagery Using Matrix Barcodes. SPIE Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping IX. National Harbor, MD.
17. Wesche, J.A., Pampolini, L.F., Sama, M.P. 2023. Validating Drone-Based 3D Models Using a LiDAR 3D Scanner. ASABE Annual International Meeting. Omaha, NE.
18. Ladino, K.S., Sama, M.P. 2023. Evaluating Static and Dynamic Position Measurement Accuracy on an Unmanned Aircraft System (UAS). ASABE Annual International Meeting. Omaha, NE.
19. Maimaitijiang M., Millett, B., Paheding S., Khan SN., Dilmurat K., Reyes A., Kovács P. (2023). Estimating crop grain yield and seed composition using deep learning from UAV multispectral data. 2023 IEEE International Geoscience and Remote Sensing Symposium IGARSS, July 16 – 21st, Pasadena, CA, USA.
20. Khan SN., Maimaitijiang M., Millett, B., Paheding S., Li DP., Caffé M., Kovács P. (2023). Simultaneously estimating crop yield and seed composition using multitask learning from UAV multispectral data. 2023 IEEE International Geoscience and Remote Sensing Symposium IGARSS, July 16 – 21, Pasadena, CA, USA.
21. Maimaitijiang M., Early forecasting of crop production and quality using UAV remote sensing and machine learning. 2023 AAG GPRM conference, October 6 – 7th, Sioux Falls, SD, USA.
22. Billah, MM., Maimaitijiang, M., Millett, B., Kaushal, S., Kovacs, P., Sehgal, SK. (2023) Crop Yield and Seed Composition Estimation Using UAV Remote Sensing and Deep Transfer Learning. 2023 AAG-GPRM conference, October 6-7th, Sioux Falls, SD, USA
23. Janjua, U., Maimaitijiang, M., Millett, B., Khan. S., Billah. M., Kaushal. S., Shires. M., Yabwalo. D., Sehgal. S., Ali. S. (2023) Wheat Fusarium Head Blight (FHB) Disease Detection using UAV Multispectral Imagery and Machine Learning. 2023 AAG-GPRM conference, October 6-7th, Sioux Falls, SD, USA
24. Maimaitijiang M., When AI meets UAV Remote Sensing: Crop Monitoring in Support of Precision Agriculture and Plant Phenotyping. 2023 South Dakota Geospatial Conference, October 18 – 19th, Chamberlain, SD, USA
25. Billah, MM., Maimaitijiang, M., Millett, B., Kaushal, S., Kovacs, P., Sehgal, SK. (2023) Estimating Crop Yield and Protein Content using UAV Remote Sensing and Advanced Transfer Learning. 2023 South Dakota Geospatial Conference, October 18-19th, Chamberlain, South Dakota, USA
26. Janjua, U., Maimaitijiang, M., Millett, B., Billah. M., Shires. M., Yabwalo. D., Sehgal. S., Ali. S. (2023) Wheat Fusarium Head Blight (FHB) Disease Detection using UAV Multispectral Imagery and Machine Learning. 2023 USGS EROS Poster Symposium, November 15th, Sioux Falls, South Dakota, USA
27. Kaushal, S., Gill, H., Halder, J., Billah, MM., Shahid, N., Maimaitijiang, M., Bernardo, A., St Amand, P., Bai, G., Sehgal, SK. AI-driven Winter Wheat Phenomics Prediction utilizing UAV Multispectral Data, 2024 Annual WheatCAP Meeting, January 11th, San Diego, CA, USA
28. Kaushal, S., Gill, H., Halder, J., Billah, MM., Shahid, N., Maimaitijiang, M., Bernardo, A., St Amand, P., Bai, G., Sehgal, SK.  Improving Grain Yield Prediction with Multi-Modal Deep Learning, integrating Genomics and Phenomics, 2024 NAPPN Annual Conference, February 13-15th, West Lafayette, IN, USA
29. Janjua U., Maimaitijiang, M., Millett, B., Billah. M, Shires. M., Yabwalo. D., Sehgal. S., Ali. S. (2024). Wheat Fusarium Head Blight (FHB) Disease Severity Estimation using UAV Multispectral Imagery and Machine Learning. 2024 NAPPN Annual Conference, February 13-15th, West Lafayette, IN, USA
30. Janjua U., Maimaitijiang, M., Millett, B., Kovacs, P. (2024). Assimilation of UAS remote sensing and machine learning-based biomass with a crop simulation model for maize yield prediction. 2024 AI in Agriculture and Natural Resources Conference, April 15-17th, College Station, TX, USA
31. Irshad, MA., Maimaitijiang, M., Millett, B., Kovacs, P. (2024). Large Scale Crop Canopy Cover Estimation Using Satellite-UAS Synergy and Machine Learning. 2024 AI in Agriculture and Natural Resources Conference, April 15-17th, College Station, TX, USA
32. Billah, MM., Maimaitijiang, M., Millett, B., Kaushal, S., Kovacs, P., Sehgal, SK. (2024). Multiyear crop yield and quality estimation using UAS remote sensing and deep transfer learning. 2024 AI in Agriculture and Natural Resources Conference, April 15-17th, College Station, TX, USA
33. Irshad, MA., Maimaitijiang, M., Millett, B., Kovacs, P. (2024). Crop Canopy Cover Estimation Using Satellite-UAS Synergy and Deep Learning. 2024 AAG Annual Conference, April 16 – 18th, Honolulu, HI, USA.
34. Billah, MM., Maimaitijiang, M., Millett, B., Kaushal, S., Kovacs, P., Sehgal, SK. (2024). Crop yield and seed composition estimation using UAV remote sensing and deep transfer learning. 2024 AAG Annual Conference, April 16 – 18th, Honolulu, HI, USA.
35. Janjua U., Maimaitijiang, M., Millett, B., Kovacs, P. (2024). Crop yield estimation using crop growth model, machine learning and remote sensing data assimilation. 2024 AAG Annual Conference, April 16 – 18th, Honolulu, HI, USA.

Patents

1. NDVI and NDRE Models to Determine Tiller Density in Winter Wheat; Authors: Oakes J; Balota M; Cazenave A-B; Thomason W
2. Disclosure-24-00054. Khot, L. R., Dadallage, K. and Amogi, B. Weathersonde with integrated mobile/web application for real time mapping of lower atmospheric attributes
3. Li, L. Unmanned vehicle having flight configuration and surface transverse configuration. US Provisional Patent 63/409,522 (Filed)

Dataset/software published

1. ArcGIS UAV Toolbox: GUI-based processing tools developed that facilitate UAV image processing and analysis in ArcGIS Pro, https://github.com/reaustin/arcgis-uav-toolbox

Outreach events

1. Chandel, A. Drone data analytics workshop, April 19, 2024
2. Chandel, A. Virginia peanut production with state-of-art technology, March 8, 2024
3. Chandel, A. Drone applications in strawberry production. Mid-Atlantic strawberry field day. February 26, 2024. Chesapeake, VA.
4. Chandel, A. Drones and AI for peanut maturity mapping, Virginia peanut grower annual meeting, Franklin, VA. Feb 22, 2024.
5. Chandel, A. Drone applications in agriculture. Private applicator recertification training. December 14, 2023. Rapidan, VA (Virtual)
6. Lachowiec J. Research for early detection of herbicide resistant wild oat: send us your photos! Montana Grain Growers Association Annual Meeting, Great Falls, MT, November 29, 2023.
7. Lav Khot. Co-organized “Smart Orchard + AgAID Field day” at Wenatchee, WA, September 15, 2023. This event featured the Smart Orchard project and the WSU AgAID AI Institute project developed technologies. Attendees: 40 tree fruit growers, agri-business industry, NIFA & NSF national program leaders, and media.
8. Lav Khot. Co-organized “Smart Vineyard Field Day”, at Prosser, WA, July 21, 2023. This event showcased research to improve irrigation scheduling, grapevine plant models and heat stress mitigation techniques. Attendees: 40 grapevine growers, agri-business industry representatives, and media.
9. Lav Khot. Co-organized “Smart Orchard Field Day”, Washington Fruit Smart Orchard Block, Grandview, WA. August 2, 2023. (Attendees: ~60+ from agri-business industry, growers, commodity group representatives, researchers, and media).
10. Lav Khot. Co-organized “Spring Drone Day” at Pasco, WA; May 19, 2023. This event was co-organized with WSU Tree Fruit Extension team member, Bernardita Sallato and focused on educating stakeholders about current landscape of drone-based aerial imaging and crop management, offerings from service providers, and associated regulations. Attendees: 25+ Tree fruit growers, agri-business industry, and media.
11. Lav Khot. 2023. (Invited) Virtual Talk on “Crop protection technologies for modern orchard systems”, 8^th Annual Materials Innovation for Sustainable Agriculture Symposium, Orlando, FL, November 30, 2023. Time: ~30 min. Participants: ~50.
12. Lav Khot. 2023. (Invited) Virtual Talk on “Aerial crop protection technologies for modern orchard systems”, 2023 Remotely Piloted Aerial Application Systems Workshop, University of California, Davis, CA; October 04, 2023. Participants: 104 (69 virtual, 35 in person).
13. Lav Khot. 2023. (Invited) Talk on “Digital agriculture and drones”, Spokane Ag Expo and Pacific NW Farm Forum, Spokane, WA. February 7, 2023. Time: 60 min. Participants: ~40.
14. Lav Khot. 2023. Talk and discussion on “Smart orchard learnings from 3 years”, Columbia Basic Tree Fruit Club Meeting, Kennewick, WA. January 24, 2023. Time: 30 min. Participants: ~15.
15. Lav Khot. 2023. Talk on “Smart orchard: Tools to monitor crop water use”, 76th Annual Lake Chelan Horticultural Meeting, Chelan WA. January 21, 2023. Time: 30 min. Participants: ~95.
16. NC Aquaculture Industry Growth Visioning Workshop, March 21, 2024. Hall, moderator with Paige O’Neill, Focus: Recirculating Aquaculture Systems group.
17. Hall, S., 2024. NC Aquaculture State Update and Economic impact NCSU-NCCE. Presented at NC Aquaculture Development Conference March 22, 2024.
18. Hall, S., 2024. MARC Tour, with R. Kelly, M. Frinsko (35 participants), March 21, 2024.  Included discussion of automated and autonomous vehicles for aquacultural applications.
19. Avi Goldsmith, Andrew Howell, Ramon Leon, NC Drone Extension Workshop (Talk and Field Demonstration), Intro to Unmanned Aerial Systems [Designed for NC Extension Personnel]
20. Andrew W Howell and Robert J Richardson, Midwest Aquatic Plant Management Society Talk, Evaluation of Unoccupied Aerial Systems (UAS) for Aquatic Weed Management
21. Andrew W Howell, North American Lake Management Society Talk, Unoccupied Aerial Systems (UAS) for Aquatic Weed Management
22. Andrew W Howell, NC Crop Protection School Talk: Utilizing Unoccupied Aerial Spray Systems for Aquatic and Noncropland Weed Management
23. Andrew W Howell, Michael W Durham, Benjamin P Sperry, and Robert J Richardson, South Carolina Aquatic Plant Management Society Talk, Identifying Optimal Spray Components for Floating Plant Control with Unoccupied Aerial Sprayers.
24. Austin, R.E., State of Soybean Research in North Carolina. Evaluating drone and satellite imagery for on-farm decision support in North Carolina Soybeans, March 2024
25. Austin, R.E., Ermish, S., Evaluating Image-based drone Stand Counts for Guiding Replant Decisions in Soybeans in North Carolina, 33nd Annual North Carolina Commodities Conference, January 11-13, 2023. Durham, NC. (~300 in attendance)
26. Austin, R.E., Unmanned Aircraft in Sediment and Erosion Control Design, December 6th, 2023, Lake Wheeler Field lab, Raleigh, North Carolina, Raleigh, North Carolina (100 in attendance).
27. Austin, R.E., Ermish, S UAV use for within season management decisions in North Carolina soybean production, Extension State Conference, Koury Convention Center, Greensboro, NC Oct 3-5th, 2023
28. Austin, R.E., Ermish, S 32nd Annual North Carolina Commodities Conference, January 12-14, 2023. Durham, NC.
29. ASABE Arkansas Section - Broadening Smart Technologies in Agricultural Systems Towards Autonomous Farming
30. Arkansas Water Resources Conference - Unmanned Aerial Vehicles as Autonomous Water Quality Monitoring Platforms
31. FAA high school visits over 80 students
32. Li, L. Invited Talk “Drone remote sensing and AI for Precision Agriculture” by 2023 Hermiston Farm Fair on Nov 29-20, 2023, Oregon State University
33. Maimaitijiang, M. UAS hands-on flight training and UAS remote sensing application workshop at Oglala Lakota Tribal college and Lower Brule High school (July 2023) https://lakotauas.wordpress.com/
34. Maimaitijiang, M. 2024 South Dakota State University Drone Day (April 2024) https://www.sdstate.edu/news/2024/05/sky-limit-possible-uses-drone-technology

Number of students supported/trained: 63

Grants funded

1. 2023-2025. USDA-NIFA– ODF: Through University of Nebraska: National Agricultural Producers Data Cooperative: Strategic Development for USDA. ($920,000; PIs: Clarke, Chandel et al.).
2. 2022-2024. USDA-NIFA– ODF: Through University of Nebraska: National Agricultural Producers Data Cooperative: Building a Strategic Framework for Increasing Production and Driving Innovation. ($960,000; PIs: Clarke, Chandel et al.).
3. 2023-2024. NSF Convergence Accelerator– Precision agriculture for a resilient vegetable supply amidst climate change. ($313,032; PIs: Xia, Chandel, McNair, Mayer, Lyon-Hill, Herndon, Coggin, Higgins).
4. 2023-2023. Center for Advanced Innovation in Agriculture (VT-CAIA)– Supporting American Chestnut Hybridization for Restoration with State-of-the-Art Remote Sensing and Machine learning. ($10,000; PIs: Chandel, Hession).
5. 2022-2023. USDA-NIFA–ODF: Through University of Nebraska: Building synergistic data framework for cropping, livestock, and aquaculture producer network in Virginia. ($500,000; PIs: Clarke, Chandel et al.).
6. 2024-2025. Virginia Peanut Growers Association– Effect of Prohexadione calcium on peanut grown for seed production. ($28,500. PIs: Balota, Chandel, Langston).
7. 2023-2025. Southern Region Small Fruit Consortium– Latent detection of anthracnose on strawberry crop using multi-spectral imaging. ($10,000. PIs: Samtani, Chandel)
8. 2023-2024. Virginia Peanut Growers Association– Towards a grower-oriented decision tool for peanut maturity prediction and digging. ($17,760. PIs: Chandel and Balota).
9. 2023-2024. Impact of Planting Date on Wheat Development, Freeze Susceptibility, and Yield. $4,000. Joseph Oakes, Robbie Longest. Virginia Small Grains Board.
10. Automated Satellite Detection & Drone Tasking Automation Service for Precision Agriculture. $10,000. Joseph Oakes. Pixelar, LLC., Virginia Innovation Partnership Corporation
11. 2023-2026. USDA-NIFA: Peanut Variety and Quality Evaluation - Harnessing Multiscale Data for Trait Prediction to Support Cultivar Release Decisions. Balota, Chandel et al. ($500,000).
12. 2023-2026. USDA-SCRI: Enhanced Mid-Atlantic System Sustainability Through Development Of High-Protein And Stress Tolerant Faba Bean For Winter Production. $2.7 million. Balota, Chandel, Oakes, et al.
13. 2023-2027: USAID-Peanut Innovation Lab: Adoption of High Throughput Phenotyping (HTP) in Varietal Development Throughout the Groundnut Improvement Network for Africa (GINA). Balota, Chandel et al. ($522,266)
14. NSF/USDA, 1/1/21-12/31/24. NRI-INT: Developing a Customizable Fleet of Autonomous Co-Robots for Advancing Aquaculture Production. NSF/USDA $1.08M, Role: co-PI, $1.08M
15. Evaluating UAV (drone) Use for within Season Management Decisions in NC Soybeans, NC Soybean Producers Association, Inc., $83,331
16. Enabling the Research Farm of the Future, NC Plant Sciences Initiative, $315,077
17. Unmanned Aerial Vehicle (UAV)-based turfgrass evaluation for selection and development of adapted cultivars, Center for Environmental Research and Education, $32,560
18. Unmanned Aerial Vehicle for Pesticide Applications in the US, Mississippi State University - USDA NIFA, $69,955
19. WaterSmartTurf: Bridging genome-to-phenome and release-to-adoption gaps for breeding and deployment of drought-tolerant warm-season turf grasses, USDA NIFA via University of Georgia, $1.9M
20. Detection and management of multiple herbicide resistant weeds, USDA NIFA, Montana State University, $189,000.

Other

1. Khot, L. Teaching a graduate level course BYSE551: UAS in Agriculture (2 credits, Spring 2024)
2. Li, L. Coordinating courses ME 201 Robotics Team Projects, ME401 Robotics Team projects

Scientific/Research Publications

1. Jjagwe, P., Chandel, A.K., Langston, D., 2023. Pre-harvest corn grain moisture estimation using aerial multispectral imagery and machine learning techniques. Land, 12(12), p.2188. https://doi.org/10.3390/land12122188
2. Jjagwe, P., Chandel, A.K., Langston, D., 2023. Soybean yield and vigor assessment against nematode infestation using SUAS-based aerial multispectral imagery and machine learning. Remote Sensing, Under Review.
3. Prior, E.M., N. Michaelson, J.A. Czuba, T.J. Pingel, V.A. Thomas, and W.C. Hession (in review), Lidar DEM and computational mesh grid resolutions modify roughness in 2D hydrodynamic models, Water Resource Research.
4. Resop, J.P., C. Hendrix, T. Wynn-Thompson, and W.C. Hession (Accepted, in press), Channel morphology change after restoration: Drone laser scanning versus traditional surveying techniques, Hydrology.
5. Christensen, N.D., E.M. Prior, J.A. Czuba, and W.C. Hession (2024), Stream restoration that allows for self-adjustment can increase channel-floodplain connectivity, Journal of Ecological Engineering Design, 1 (1). https://doi.org/10.21428/f69f093e.e8ffa1a3.
6. Sumnall, M.J., T.J. Albaugh, D.R. Carter, R.L. Cook, W.C. Hession, O.C. Campoe, R.A. Rubilar, R.H. Wynne, and V.A. Thomas (2023), Estimation of individual stem volume and diameter from segmented UAV laser scanning datasets in Pinus taeda L.plantations, International Journal of Remote Sensing, 44:1, 217-247. doi/10.1080/01431161.2022.2161853
7. Oakes J, Balota M, Cazenave A-B, Thomason W. Using Aerial Spectral Indices to Determine Fertility Rate and Timing in Winter Wheat. Agriculture. 2024; 14(1):95. https://doi.org/10.3390/agriculture14010095
8. Johnson, Kellie; Drape, Tiffany; Oakes, Joseph; Simpson, Joseph; Brown, Ann; Westfall-Rudd, Donna M.; and Duncan, Susan (2023) "An Interdisciplinary Approach to Experiential Learning in Cyberbiosecurity and Agriculture Through Workforce Development," Journal of Cybersecurity Education, Research and Practice: Vol. 2024, Article 2. Available at: https://digitalcommons.kennesaw.edu/jcerp/vol2024/iss1/2
9. Dhakal, K.; Sivaramakrishnan, U.; Zhang, X.; Belay, K.; Oakes, J.; Wei, X.; Li, S. Machine Learning Analysis of Hyperspectral Images of Damaged Wheat Kernels. Sensors2023, 23, 3523. https://doi.org/10.3390/s23073523
10. Jordan, D. L., Anco, D., Balota, M., Langston, D., Lux, L., Shew, B., & Brandenburg, R. L. (2024). Survey of herbicide and fungicide use in peanut in North Carolina and Virginia in the United States. Crop, Forage & Turfgrass Management, 10(1), e20263.
11. Jordan, D. L., Anco, D., Balota, M., & Brandenburg, R. L. (2024). Farmer insights on harvesting peanut: A survey from the Virginia–Carolina region of the United States. Crop, Forage & Turfgrass Management, 10(1), e20262.
12. Jordan, D. L., Shew, B. B., Brandenburg, R. L., Anco, D., & Balota, M. 2023. Summary of tillage practices in peanut in the Virginia–Carolina region of the United States. Crop, Forage & Turfgrass Management, 9(1), e20222.
13. Oteng-Frimpong R, Karikari B, Sie EK, Kassim YB, Puozaa DK, Rasheed MA, Fonceka D, Okello DK, Balota M, Burow M and Ozias-Akins P (2023) Multi-locus genome-wide association studies reveal genomic regions and putative candidate genes associated with leaf spot diseases in African groundnut (Arachis hypogaea) germplasm. Front. Plant Sci. 13:1076744.doi: 10.3389/fpls.2022.1076744
14. Lachowiec J, Feldman MJ, Matias FI, LeBauer D, Gregory A. (2024) ”Adoption of unoccupied aerial systems in agricultural research”. The Plant Phenome Journal. 7(1): e20098
15. Prince Czarnecki, Joby M., et al. "Estimation of the economic impacts and operational limitations imposed on unmanned aerial systems by poor sky conditions." Precision Agriculture6 (2023): 2607-2619.Are unmanned aerial vehicle-based hyperspectral imaging and machine learning advancing crop science? (Trends in Plant Science)
16. Czarnecki, J. M. P., et al. "Evaluating the spectral response of cotton and corn to different cover crops using UAV imagery." Precision agriculture’23. Wageningen Academic Publishers, 2023. 677-683.High-accuracy infrared thermography of cotton canopy temperature by unmanned aerial systems (UAS): Evaluating in-season prediction of yield (Smart Agricultural Technology)
17. Bagnall, G. Cody, et al. "Uncrewed aerial vehicle radiometric calibration: A comparison of autoexposure and fixed‐exposure images." The Plant Phenome Journal1 (2023): e20082.Plastic Contaminant Detection in Aerial Imagery of Cotton Fields Using Deep Learning (Agriculture)
18. Yadav, Pappu Kumar, et al. "Detecting volunteer cotton plants in a corn field with deep learning on UAV remote-sensing imagery." Computers and Electronics in Agriculture204 (2023): 107551.
19. Nguyen, A., J.P. Ore, C. Castro-Bolinaga, S.G. Hall, S. Young, 2024. Towards Autonomous, Optimal Water Sampling with Aerial and Surface Vehicles for Rapid Water Quality Assessment American Society of Agricultural and Biological Engineers 67 (1), 91-98
20. Howell AW, Leon RG, Everman WJ, Mitasova H, Nelson SAC, Richardson RJ. Performance of unoccupied aerial application systems for aquatic weed management: Two novel case studies.Weed Technology. 2023;37(3):277-286. doi:10.1017/wet.2023.32 (Selected as Outstanding Paper in Weed Technology for 2023)
21. Rockstad, G. B. G., Austin, R. E., Gouveia, B. T., Carbajal, E. M., & Milla-Lewis, S. R. (2023, December 19). Assessing unmanned aerial vehicle-based imagery for breeding applications in St. Augustinegrass under drought and non-drought conditions. Crop Science, Vol. 12. https://doi.org/10.1002/csc2.21128
22. Jones, Eric A. L., Robert Austin, Jeffrey C. Dunne, Charles W. Cahoon, Katherine M. Jennings, Ramon G. Leon, and Wesley J. Everman. Utilization of Image-Based Spectral Reflectance to Detect Herbicide Resistance in Glufosinate-Resistant and Glufosinate-Susceptible Plants: A Proof of Concept. Weed Science, December 19, 2022, 1–11. https://doi.org/10.1017/wsc.2022.68.
23. Ranjan R., Amogi, B. R., Chandel, A. K., Khot, L. R., Sallato, B. V. and Peters, R. T. (2024). Efficacy evaluation of apple sunburn mitigation techniques in WA 38 cultivar using crop physiology sensing system. Computers and Electronics in Agriculture. https://doi.org/10.1016/j.compag.2023.108501
24. Molaei, B., Chandel, A. K., Peters, R. T., Khot, L. R., Khan, A., Maureira, F. and Stockle, C. (2023). Investigating the application of artificial hot and cold reference surfaces for improved ETc estimation using the UAS-METRIC energy balance model. Agricultural Water Management, 284, 108346. https://doi.org/10.1016/j.agwat.2023.108346
25. Molaei, B., Peters, R. T., Chandel, A. K., Khot, L. R., Stockle, C. O. and Campbell, C. S. (2023). Measuring evapotranspiration suppression from the wind drift and spray water losses for LESA and MESA sprinklers in a center pivot irrigation system. Water, 15(13), 2444. https://doi.org/10.3390/w15132444
26. Betitame, Kelvin, et al. "Evaluation of Dicamba Drift Injury and Yield Loss on Soybean Using Small Unmanned Aircraft Systems (sUAS) and Multispectral Imaging Technologies." (2024): 63-76.
27. Delavarpour, Nadia, et al. "A review of the current unmanned aerial vehicle sprayer applications in precision agriculture." (2023): 703-721.
28. G Chen, L Li, H Zhang, Z Shi, B Shang. (2023). Aerial Nondestructive Testing and Evaluation (aNDT&E). Materials Evaluation 81 (1): 67–73 https://doi.org/10.32548/2023.me-04300
29. Zhang, Liangji & Lu, Chao & Xu, Haiwen & Chen, Aibin & Li, Liujun & Zhou, Guoxiong. (2023). MMFNet: Forest Fire Smoke Detection Using Multiscale Convergence Coordinated Pyramid Network with Mixed Attention and Fast-robust NMS. IEEE Internet of Things Journal. PP. 1-1. 10.1109/JIOT.2023.3277511.
30. Zhang, Yukai & Zhou, Guoxiong & Chen, Aibin & He, Mingfang & Li, Johnny & Hu, Yahui. (2023). A precise apple leaf diseases detection using BCTNet under unconstrained environments. Computers and Electronics in Agriculture. 212. 108132. 10.1016/j.compag.2023.108132.
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33. Ladino, K.S., Sama, M.P. 2024. A Method for Evaluating Global Navigation Satellite System Position Accuracy in Small Unmanned Aircraft Systems. Journal of the ASABE. Vol 67(2): 153-167. https://doi.org/10.13031/ja.15890
34. Agioutanti, R., Ford, W.I., Sama, M.P., McGill, T. 2024. Impacts of aquatic vegetation dynamics on nitrate removal in karst agricultural streams: Insights from UAS imagery and in situ sensing. Journal of the ASABE. Vol. 67(2): 89-104. https://doi.org/10.13031/ja.15791
35. Bailey, S.C., Smith, S.W., Sama, M.P., Al-Ghussain L., de Boer, G. 2023. Shallow Katabatic Flow in a Complex Valley: An Observational Case Study Leveraging Uncrewed Aircraft Systems. Boundary-Layer Meteorology. 186(2): 399-422.
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36. Dhakal, R., Maimaitijiang, M., Chang, J., & Caffe, M. (2023). Utilizing Spectral, Structural and Textural Features for Estimating Oat Above-Ground Biomass Using UAV-Based Multispectral Data and Machine Learning. Sensors, 23(24), 9708.
37. Kaushal, S., Gill, H.S., Billah, M.M., Khan, S.N., Halder, J., Bernardo, A., Amand, P.S., Bai, G., Glover, K., Maimaitijiang, M. and Sehgal, S.K., 2024. Enhancing the potential of phenomic and genomic prediction in winter wheat breeding using high-throughput phenotyping and deep learning. Frontiers in Plant Science, 15, p.1410249.
38. Khan, S.N., Maimaitijiang, M., Millett, B., Paheding, S., Li, D., Caffé, M. and Kovács, P., 2023, July. Simultaneously Estimating Crop Yield and Seed Composition using Multitask Learning from UAV Multispectral Data. In IGARSS 2023-2023 IEEE International Geoscience and Remote Sensing Symposium (pp. 2771-2774). IEEE.
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Extension Publications

1. Chandel, A.K., Langston, D., 2023. Aerial multispectral imagery for high-throughput mapping of spatial corn yield potentials. VCE Publications, SPES-526NP.
2. Chandel, A.K., Langston, D., 2023. Aerial multispectral imagery for high-throughput mapping of spatial soybean yield potentials. VCE Publications, SPES-527NP.
3. Chandel A.K., 2023. Aerial imagery to improve disease diagnosis and management in field crops. VCE Publications, SPES-515NP.
4. Lee, J. Oakes. Effective Tiller Management for Winter Wheat. 2023. https://www.pubs.ext.vt.edu/content/dam/pubs_ext_vt_edu/spes/spes-431/SPES-431.pdf
5. Joseph Oakes. Aerial Spectral Imagery to Determine Wheat Fertility Rate and Timing. 2024. https://www.pubs.ext.vt.edu/content/dam/pubs_ext_vt_edu/spes/spes-582/SPES-582.pdf
6. Young, P. Ore, S. Hall, 2023.  The Coming Wave of Aquatic Robotics, Resource Magazine, https://tinyurl.com/4crkbb8j
7. Amogi, B. R., Schrader, M. J., Khot, L. R. and Hoheisel, G. A. (2023). Decision support tools for frost mitigation. Washington State University - Viticulture and Enology Extension News, Spring 2023, 6-7
8. Jackson, J.J., Ladino, K.S. 2024. Drone Sprayer Sizing for Agricultural Applications AEN-174. University of Kentucky Cooperative Extension Service. https://www2.ca.uky.edu/agcomm/pubs/AEN/AEN174/AEN174.pdf