Performing Department
Entomology
Non Technical Summary
The long-term goal of The Digital and Data-Driven Demonstration Farm (4-D Farm) is to develop climate-smart production systems leveraging renewable energy, automation, intelligence and human capital to meet the required food and fiber needs of a burgeoning world population. Most currently funded research is driven by individual commodity and discipline needs and rarely investigates integrating multiple agricultural enterprises to improve farm resilience so that the farmer does not have all their "eggs in one basket". In this project, data-driven farm strategies will be implemented to create an interdependent and diverse crop/livestock rotation that addresses thereduced effectiveness of chemical inputs, climate change effects, feeding an increasing population, loss of biodiversity and pollinators, water quality/quantity, rural economic stability, labor shortages and supply chain disruptions. These issues are addressed by the 4-D Farm: 1) Creating data-driven, integrated precision and climate-smart agriculture with intelligent automation technologies andsolutions, 2) Developing and testing resilient agricultural practices and 3) Assessing the socioeconomic consequences of these new technologies and practices. The 4-D farm will be executed on a 90-acre D.A.T.A. (Demonstrating Applied Technology in Ag) farm at the Abraham Baldwin Agricultural College (ABAC), multiple Emerging Techology and Demonstration Site's (ETDS's) located on University of Georgia (UGA) research farms, and a Data Management and Analysis Center at the UGA Tifton Campus, Future Farmstead Carriage House. We have assembled an inter-disciplinary team in precision and climate-smart agriculture, data science, livestockmanagement, peanut, cotton, and corn production, extension and education programming, and autonomous and intelligent rover research and development.
Animal Health Component
10%
Research Effort Categories
Basic
10%
Applied
90%
Developmental
0%
Goals / Objectives
The long-term goal of the 4-D Farm is to develop climate smart and sustainable production systems leveraging renewable energy, automation, intelligence and human capital to meet the required food and fiber needs of a burgeoning world population.To develop, demonstrate, and implement the 4-D Farm, The University of Georgia and its strategic partners and stakeholders will integrate precision crop and livestock production systems with new and emerging technologies to provide a framework for creating a long-term sustainable 4-D Farm Site that is environmentally sound, socially acceptable, and economically viable for small and medium-size producers. The main focus of the farm will be to develop, test and demonstrate 1) precision technologies that improve crop emergence and production, pest management, and harvest efficiency and tracking, 2) autonomous and robotic platforms and tools that are efficient, multi-purpose and scalable for small to mid-sized farmers, 3) scouting and/or monitoring with IoT-enabled devices, UAV's and satellites that remotely monitor livestock and crop health, 4) management strategies to conserve soil and water through innovative crop integration and rotation with livestock grazing, 5) educational and outreach programs for extension agents, farmers, consultants, and K-PhD students; and 6) AI for analysis of spatio-temporal collected data to forecast economic and environmental outcomes from precision crop/livestock management strategies.?The specific objectives and subobjectives are:1. Test develop and implement data-driven, integrated precision agriculture and intelligent automationa. Big-Data management analysis and forecasting: data-driven models will be developed to assist with in-season management decisions and end-of-season planning for the coming seasonb. Improve efficiency and precision of liquid/dry material application for protection and nutrition in crops and livestockc. Improve Crop Emergence in cotton, corn and peanuts.d. Monitor herd behavior and health using advanced precision livestock toolse. Test optical, thermal and volatile sensors to measure crop stress on intelligent ground vehiclesf. Automate UAV flights using a drone command centerg. Monitor crop and livestock pests remotely with IoT remote pest detection stationh. Develop and administer agricultural demonstrations, curriculum and trainings on 4-D farm for farmers, college students, agricultural youth and other stakeholdersi. Develop a "farm of the future" office of the 4-D farmj. Conduct county extension trainingsk. Incorporate a virtual reality and augmented reality2. Develop and implement resilient agricultural practicesa. Institute a livestock grazing management system using ATVb. Measure GHG's in livestock and crop systems before, during after sustainable and circular applied management practicesc. Institute a green mulch for conservation tillage practices and incorporated with cattle grazingd. Increase the efficient utilization of livestock waste to reduce artificial fertilizerse. Work with federal agencies and NPO's to conserve and preserve wildlife habitatf. Improve irrigation management using variable rate irrigation and irrigation management modelsg. Develop educational modules for Ag. Educators, 4-H agents and others h. Develop and maintain webpage and social media content for information dispersal and program assessmenti. Train county extension personnel on resilient agricultural practicesj. Utilize existing solar panels to power farm office at the future farmstead carriage hose.3. Use applied socioeconomics to determine the sustainable adoption of practices developed in the projecta. Conduct a net returns assessment of each 4-D farm subsystemb. Perform a utility maximization analysis of profit including tradeoffs of labor and leisure activitiesc. Determine consequences of varying human capital states of technology levels on quality of life and adoptiond. Assess the effects of multiple parameters on adoption of multi-purpose intelligent vehiclese. Conduct county agent training to reduce the anxiety of new technology
Project Methods
Precision Ag and Intelligent Automation1. Data collection and processing - Data from satellite, UAV, UGV, soil, water, weather and markets will be collected and processed through ML algorithms to provide in-season management recommendations. Data from each year will build on a basic model framework of the farm data. Machine learning metrics, such as F-1 score, precision and mean average precision will be used to validate models. Graph networks will be used as a method of combining disparate data sets and then predictive models created using embedded graph neural networks and other AI techniques.2. Improved Efficiency and Precision of Liquid/Dry Material Application for Protection and Nutrition in Crops and Livestock: Information on effective and efficient utilization of current technologies will be tested and demonstrated on the farm. Variable-rate control and real-time machine adjustment systems for dry fertilizer applications will become an integral part of 4-D farm operations.3. Improved Crop Emergence: Precision technologies for cotton and peanut production will be developed on ETDS and integrated on the demonstration farm along with determining ways to effectively utilize the data generated on these machines to enable data-driven, site-specific planting decisions to maximize crop emergence and yield potential.4. Herd behavior and Health monitoring: The CowManager tag system will be incorporated into already occurring grazing evaluations to identify and track individual animal behavior and health statistics including data reflecting eating time, rumination, and external body temperature on ETSD. To quantify water utilization within the grazing system, water level, temperature and time of day will be monitored.5. Intelligent Ground Vehicles: We will leverage the modular Watson peanut scouting rover design and the Red Rover (both developed at UGA) to test sensors for cotton and peanut scouting. We will develop trajectory planning methods to enable each rover to gather data, harvest cotton and/or manage weeds.6. Automation of UAV Flights: a fully autonomous drone scouting system consisting of a "drone in a box" will fly field scouting missions over corn, cotton and peanut fields assessing plant height, plant population and vigor. Measurements will be correlated with ground rover and utilized as one of the sensor inputs for developing predictive machine learning algorithms.7. IoT-enabled Monitoring for Crop and Livestock Pests: Web-based real-time automated monitoring station will provide scheduled insect counts.8. Experiential Learning for K-PhD: The 4-D farm demonstration site will be used to train educators and showcase the educational modules developed, host FFA and 4-H events and provide hands-on educational content.9. Future Farmers Office: A manager will monitor all operations occurring on the farm from the data center. These data coupled with forecasting analysis will allow the manager to make real-time agricultural production decisions.10. Virtual/Augmented Reality: A real-time view of the current 4-D farm activities will be seen using 360° camera with IoT connectivity. The UGA Virtual Experiences Lab will provide support.Resilient PracticesLivestock grazing management: The CDax® ATV mounted pasture evaluation system will be used to quickly quantify available forage and make informed grazing decisions to determine necessary adjustments in stocking rate, stocking density, and/or livestock rotations between paddocks on an ETDS. The CDax® system will be evaluated in comparison to more traditional research field data collection methodologies for accuracy.GHG monitoring: C-Lock GreenFeed and Super SmartFeed systems will control livestock nutrition intake and measure GHG emissions to understand how nutrition composition affects GHG and animal weight gain. Once these technologies have been implemented and evaluated for basic and applied research on ETDS, we will integrate at the 4-D demonstration farm. This system will offer producers precision feeding plans. Soil GHG emissions will be monitored multiple times per year to assess effect of management practicesGreen mulch implementation: A green mulch conservation tillage system will go hand in hand with grazing in established crop stands. Planter technologies will be integrated to maximize the benefits of a green mulch system while also maximizing seed placement and crop emergenceLivestock waste utilization: A poultry litter manure injector will be developed to match field capacity and efficiency of a standard fertilizer spreader and aid in more precise placement and utilization of animal waste and manures for the purpose of crop and pasture nutrient supplementation.Conservation/habitat preservation: The 4-D demonstration farm has some unproductive farmland. We will work with local organizations such as Quail Forever and NRCS to conserve wetlands, wildlife habitat and promote spatial and temporal BMP's.Irrigation management: An ETDS will support remote soils monitoring, sensing of crop water requirements, pivot monitoring and control, development, implementation and testing of irrigation scheduling technologies. We will monitor water use efficiency temporally and spatially through the Carriage House data hub.Education modules: Educational modules to train undergraduate Agricultural Education students on emerging technology will be developed. In addition to training students at the collegiate level, faculty from both UGA and ABAC will work with the GA FFA Association to develop short educational modules and training for currently employed K-12 Agricultural Educators.Webpage and Social Media Content and Assessment: A suite of communication materials will be created and shared with all stakeholders. A robust website will be developed to host the resources studied and developed to extend the reach and scope of the 4-D Farm.Solar Power implementation: Two solar arrays are wired to the Carriage House and will be connected to Solar battery. Charging for electric rovers will be investigated. SocioeconomicsNet Returns Assessment: Traditional economic analysis evaluating changes in output, inputs , and net returns will be conducted for each sub-system of the demonstration farm including post-harvest foraging in cotton or peanut fields, multipurpose system of small rovers, poultry litter injection, solar powered irrigation, carriage house systems, cover crop benefits, and non-chemical weed control.Utility maximization analysis: To supplement the profitability analysis of the individual technologies as well as the 4-D Farming system within the circular economy, the utility aspects of these systems including quality-of-life and required human capital will be measured and evaluated.Human Capital and Quality of Life Assessment: The digital agricultural technologies comprising the 4-D Farm will be evaluated with respect to quality-of-life on the benefits side and human capital requirements on the cost side of the benefit cost analysis to supplement traditional profitability analysis.Multipurpose intelligent vehicles: Costs of autonomous systems will be closely monitored. Models will be parameterized from prior knowledge plus data specific to the 4-D demonstration farm to understand how new autonomous harvest technology affects crop yield and quality.Extension TrainingUGA Extension network is the main avenue for educating stakeholders on the results and implications of the 4-D farm. We will work with agents to ensure that timely and relevant information is provided to producers. Information dissemination will occur through multiple channels, which includes but is not limited to social media, websites, blogs, presentations, videos, in-person trainings, producer meetings, field days, and one-on-one training sessions. For this specific goal, extension trainings will be developed based around 4-D farm results.