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Li, J.C
Lee, D
Ewanik, C
L, R.N
Leonard, B.J
Rodrigues, M
Rocha, D.M
Liu, X
Fulton, J.P
Lai, C
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Li, T
Hu, J
Gao, L
Hu, H
Bai, X
Liu, X
Bazzi, C.L
Souza, E.G
Nobrega, L.H
Uribe-Opazo, M.A
Rocha, D.M
Gowda, H.H
Reddy, K.A
Patil, M.B
L, R.N
Shanwad, U
Chung, S
Kong, J
Huh, Y
Bae, K
Hur, S
Lee, D
Chae, Y
Ortiz, B.V
Vellidis, G
Balkcom, K
Stone, H
Fulton, J.P
vanSanten, E
Torino, M.S
Ortiz, B.V
Fulton, J.P
Balkcom, K
Poncet, A.M
McDonald, T.P
Pate, G
TISSEYRE, B
Fulton, J.P
Balkcom, K
Ortiz, B
Shockley, J
Fulton, J.P
Mullenix, D
Troesch, A.M
Fulton, J.P
Winstead, A.T
Norwood, S.H
Winstead, A.T
Norwood, S.H
Griffin, T
Adrian, A.M
Runge, M
Fulton, J.P
Winstead, A.T
Norwood, S.H
Fulton, J.P
Adrian, A.M
Norwood, S.H
Fulton, J.P
Winstead, A.T
Shaw, J.N
Rodekohr, D
Brodbeck, C.J
Macy, T
Sharda, A
Luck, J.D
Fulton, J.P
Shearer, S.A
Shearer, S.A
Mullenix, D
Vanacht, M
Fulton, J.P
Darr, M.J
Taylor, R.K
McDonald, T.P
Sharda, A
Luck, J.D
Fulton, J.P
Shearer, S.A
McDonald, T.P
Mullenix, D
Luck, J.D
Sharda, A
Pitla, S.K
Fulton, J.P
Shearer, S.A
Myers, D.B
Kitchen, N.R
Sudduth, K.A
Leonard, B.J
Lai, C
Belsky, C
Fulton, J.P
Balkcom, K.S
Ortiz, B.V
McDonald, T.P
Pate, G.L
Virk, S.S
Poncet, A
Chen , J
Chen, P.L
Zhao, J.C
Wang, S.Y
Li, J.C
Zhang, Q
Hu, T.H
Shi, G.L
Poncet, A.M
Fulton, J.P
McDonald, T.P
Knappenberger, T
Bridges, R.W
Shaw, J
Balkcom, K
Kantipudi, K
Lai, C
Min, C
Chiang, R.C
Lai, C
Min, C
Chiang, R
Hafferman, A
Morgan, S
Fulton, J.P
Hawkins, E
Colley III, R
Port, K
Shearer, S
Klopfenstein, A
Souza, E.G
Bazzi, C
Hachisuca, A
Sobjak, R
Gavioli, A
Betzek, N
Schenatto, K
Mercante, E
Rodrigues, M
Moreira, W
Aikes Junior, J
Souza, E.G
Bazzi, C
Sobjak, R
Hachisuca, A
Gavioli, A
Betzek, N
Schenatto, K
Moreira, W
Mercante, E
Rodrigues, M
Hachisuca, A
Souza, E.G
Mercante, E
Sobjak, R
Ganascini, D
Abdala, M
Mendes, I
Bazzi, C
Rodrigues, M
Fulton, J.P
Shearer, S.A
Gauci, A
Lindsey, A
Barker, D
Hawkins, E
Fulton, J.P
Hawkins, E
Shearer, S
Klopfenstein, A
Hartschuh, J
Custer, S
Hartschuh, J.M
Fulton, J.P
Shearer, S.A
Enger, B.D
Schuenemann, G.M
Thomas, A.D
Fulton, J.P
Khanal, S
Ortez, O
McGlinch, G
Barai, K
Ewanik, C
Dhiman, V
Zhang, Y
Hodeghatta, U.R
Neupane, J
Joshi, N
Fulton, J.P
Khanal, S
B K, A
Bhattarai, B
Hartschuh, J.M
Fulton, J.P
Shearer, S.A
Enger, B.D
Schuenemann, G.M
Leininger, A
Verhoff, K
Lovejoy, K
Thomas, A
Davis, G
Emmons, A
Fulton, J.P
Fulton, J.P
Wilson, D
Tietje, R
Hawkins, E
Trefz, K
Fulton, J.P
Shearer, S.A
Venkatesh, R
Spina, A.N
Fulton, J.P
Shearer, S.A
Berger-Wolf, T
Drewry, D
Koppelman, G
Fulton, J.P
Khanal, S
Berger-Wolf, T
Fulton, J.P
Topics
Guidance, Robotics, Automation, and GPS Systems
Precision Nutrient Management
Spatial Variability in Crop, Soil and Natural Resources
Emerging Issues in Precision Agriculture (Energy, Biofuels, Climate Change)
Sensor Application in Managing In-season Crop Variability
Education and Training in Precision Agriculture
Guidance, Auto Steer, and GPS Systems
Profitability, Sustainability, and Adoption
Precision A-Z for Practitioners
Spatial Variability in Crop, Soil and Natural Resources
Engineering Technologies and Advances
Optimizing Farm-level use of Spatial Technologies
Precision Weed Management
Spatial Variability in Crop, Soil and Natural Resources
Emerging Issues in Precision Agriculture (Energy, Biofuels, Climate Change, Standards)
Engineering Technologies and Advances
Profitability, Sustainability and Adoption
Spatial Variability in Crop, Soil and Natural Resources
Big Data, Data Mining and Deep Learning
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
On Farm Experimentation with Site-Specific Technologies
Decision Support Systems
On Farm Experimentation with Site-Specific Technologies
In-Season Nitrogen Management
Precision Dairy and Livestock Management
Application of Granular Materials with Drones
Proximal and Remote Sensing of Soils and Crops (including Phenotyping)
Site-Specific Nutrient, Lime and Seed Management
Precision Dairy and Livestock Management
Drone Spraying
On Farm Experimentation with Site-Specific Technologies
Education of Precision Agriculture Topics and Practices
Artificial Intelligence (AI) in Agriculture
Type
Poster
Oral
Year
2012
2010
2014
2016
2018
2022
2024
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Filter results40 paper(s) found.

1. Profitability Of RTK Autoguidance And Its Influence On Peanut Production

Efficient harvest of peanuts (Arachis hypogea L.) requires that the digging implement be accurately positioned directly over the target rows. Small driving... K. Balkcom, B. Ortiz, J. Shockley, J.P. Fulton

2. Economic Analysis Of Auto-swath Control For Alabama Crop Production

With the rising costs of fertilizer and pesticides and a push towards increasing environmental stewardship, farmers are seeking means to save money while preserving the environment and wildlife habitat. One technology that aids in remedying these concerns is auto-swath control. This investigation evaluates overlap savings using this technology on different application equipment and resulting in economic savings for those adopting it. Several field boundaries were obtained from across the state... D. Mullenix, A.M. Troesch, J.P. Fulton, A.T. Winstead, S.H. Norwood

3. Adoption And Use Of Precision Agriculture Technologies By Practitioners

A survey of farmers and farm service providers were initiated to ascertain the adoption and use of precision agriculture technologies as well as the barriers to and incentives for adoption. Farm-level data were collected via audience response system at the 2009 Alabama Precision Ag and Field Crops Conference and local winter production meetings across the six crop reporting districts in Alabama. Service provider data were collected using an online survey. Questions common to farmers and service... A.T. Winstead, S.H. Norwood, T. Griffin, A.M. Adrian, M. Runge, J.P. Fulton

4. PA Education: Using Social Media

Social media and web-based applications are gaining in popularity for disseminating information and communicating with others. The traditional method of transferring information through print and face-to-face meetings is now often supplemented and/or replaced by web-based outlets. The Alabama Precision Agriculture Program initiated a social media and web campaign as a method of distributing educational information while gaining recognition as a source for precision... A.T. Winstead, S.H. Norwood, J.P. Fulton, A.M. Adrian

5. A Case Study For Variable-rate Seeding Of Corn And Cotton In The Tennessee Valley Of Alabama

      Farmers have recently become more interested in implementing variable-rate seeding of corn and cotton in Alabama due to increasing seed costs and the potential to maximize yields site-specifically due to inherent field variability.  Therefore, an on-farm case study was conducted to evaluate the feasibility of variable-rate seeding for a corn and cotton rotation. ... S.H. Norwood, J.P. Fulton, A.T. Winstead, J.N. Shaw, D. Rodekohr, C.J. Brodbeck, T. Macy

6. Application Rate Stability When Implementing Automatic Section Control Technology On Agricultural Sprayers

Automatic section control (on and off) technology of sprayer boom sections is an intelligent solution to maximize spray application efficiency during field operations. This technology can reduce over-application of products. Spray controllers available with this technology attempt to maintain the set target rate by adjusting system flow rate based on ground speed and application width.  Therefore, as sections are turned on or off, the flow regulating hardware must respond to maintain... A. Sharda, J.D. Luck, J.P. Fulton, S.A. Shearer, S.A. Shearer, D. Mullenix, M. Vanacht

7. Proper Implementation Of Precision Agricultural Technologies For Conducting On-farm Research

Precision agricultural technologies provide farmers, practitioners and researchers the ability to conduct on-farm or field-scale research to refine farm management, improve long term crop production decisions, and implement site-specific management strategies. However, the limitations of these technologies must be understood to draw accurate and meaningful conclusions from such investigations. Therefore, the objective of this paper was to outline the limitations of several... J.P. Fulton, M.J. Darr, R.K. Taylor, T.P. Mcdonald

8. Tip Flow Uniformity When Using Different Automatic Section Control Technologies During Field Operations

Automatic section control (ASC) technology provides a means to reduce double-coverage and application in unwanted areas thereby leading to input savings and improved environmental stewardship.  However, the impact of ASC on spray boom dynamics and tip flow uniformity are unknown. Therefore, a study was conducted to evaluate tip flow rate uniformity and control system response in maintaining target application rates during field operation. Field experiments were conducted using two self-propelled... A. Sharda, J.D. Luck, J.P. Fulton, S.A. Shearer, T.P. Mcdonald, D. Mullenix

9. Generating Herbicide Effective Application Rate Maps Based On GPS Position, Nozzle Pressure, And Boom Section Actuation Data Collected From Sprayer Control Systems

The application of pre- and post- emergence burn-down herbicides (i.e., glyphosate) continues to increase as producers attempt to reduce both negative environmental impacts from tillage and input costs from labor, machinery and materials.  The use of precision agriculture technologies such as automatic boom section control allows producers to reduce off-target application when applying herbicides.  While automatic boom section control has provided benefits, pressure differences across... J.D. Luck, A. Sharda, S.K. Pitla, J.P. Fulton, S.A. Shearer

10. Research on Straight-Line Path Tracking Control Methods in an Agricultural Vehicle Navigation System

In the precision agriculture (PA), an agricultural vehicle navigation system is essential and precision of the vehicle path tracking is of great importance in such a system. As straight line operation is the main way of agricultural vehicles on large fields, this paper focuses on the discussion of straight-line path tracking control methods and proposes an agricultural vehicle path tracking algorithm based on the optimal control theory. First, the paper deduces a relative kinematics model of agricultural... T. Li, J. Hu, L. Gao, H. Hu, X. Bai, X. Liu

11. Use of Chemical and Physical Attributes Of the Soil in Management Units Definition

Several equipments and methodologies have been developed to make available precision agriculture, especially the high cost of its implantation and sampling. An interesting possibility... C.L. Bazzi, E.G. Souza, L.H. Nobrega, M.A. Uribe-opazo, D.M. Rocha

12. Natural Resources Management through Frontier Technologies - A Case Study from India

The social and economic development of the state is interlaced with our natural resources, and the manner in which they are managed and exploited.  The unplanned development and overexploitation of resources are exerting various... H.H. Gowda, K.A. Reddy, M.B. Patil, R.N. L, U. Shanwad

13. Evaluation of Photovoltaic Modules at Different Installation Angles and Times of the Day

Several electricity-consuming components for cooling and heating, illumination, ventilation, and irrigation are used to maintain proper environments of protected crop cultivation facilities. Photovoltaic system is considered as one of the most promising alternative power source for protected cultivation. Effects of environment,... S. Chung, J. Kong, Y. Huh, K. Bae, S. Hur, D. Lee, Y. Chae

14. Evaluation of The Advantages of Using GPS-Based Auto-Guidance on Rolling Terrain Peanut Fields

  ... B.V. Ortiz, G. Vellidis, K. Balkcom, H. Stone, J. Fulton, E. Vansanten

15. Evaluation of Differences in Corn Biomass and Nitrogen Uptake at Various Growth Stages Using Spectral Vegetation Indices

Application of canopy sensors for nitrogen (N) fertilizer management for corn grain production in the Southeast US requires... M.S. Torino, B.V. Ortiz, J. Fulton, K. Balkcom

16. Maximizing Agriculture Equipment Capacity Using Precision Agriculture Technologies

Guidance systems are one of the primary Precision Agriculture technologies adopted by US farmers. While most practitioners establish their initial AB lines for fields based on previous management patterns, a potential exists in conducting analyses to establish AB lines or traffic patterns which maximize field capacity. The objective of this study was to... A.M. Poncet, T.P. Mcdonald, G. Pate, B. Tisseyre, J.P. Fulton

17. Physiological Repsonses Of Corn To Variable Seeding Rates In Landscape-Scale Strip Trials

Many producers now have the capability to vary seeding rates on-the-go. Methods are needed to develop variable rate seeding approaches in corn but require an understanding of the physiological response of corn to soil-landscape and weather conditions. Interplant competition fundamentally differs at varied seeding rate and may affect corn leaf area, transpiration, plant morphology, and assimilate partitioning. Optimizing these physiological effects with optimal seeding rates in a site-specific... D.B. Myers, N.R. Kitchen, K.A. Sudduth, B.J. Leonard

18. Building Proactive Predictive Models With Big Data Technology For Precision Agriculture

In a world with ever increasing shortages of food production due to increasing populations and depletion of resources, the need for new technologies and techniques for sustainable and efficient agriculture with long term financial, environmental and cultural benefits are critical.  An area of scientific study concerning crop-production management called Precision Agriculture (PA) is a concept based on integrating modern information technologies such as Big Data Analytics, GPS... C. Lai, C. Belsky

19. Row-Crop Planter Requirements To Support Variable-Rate Seeding Of Maize

Current planting technology possesses the ability to increase crop productivity and improve field efficiency by precisely metering and placing crop seeds. Growing high yielding crops not only requires using the right seed variety and rate but also achieving optimal performance with available planter technology. Planter performance depends on using the correct planter and technology (display and rate controller system) setup which consists of determining optimal settings for different planting... J.P. Fulton, K.S. Balkcom, B.V. Ortiz, T.P. Mcdonald, G.L. Pate, S.S. Virk, A. Poncet

20. Yield, Residual Nitrogen and Economic Benefit of Precision Seeding and Laser Land Leveling for Winter Wheat

Rapid socio-economic changes in China, such as land conversion and urbanization etc., are creating new scopes for application of precision agriculture (PA). It remains unclear the application effective and economic benefits of precision agriculture technologies in China. In this study, our specific goal was to analyze the impact of precision seeding and laser land leveling on winter wheat yield,... J. Chen , P.L. Chen, J.C. Zhao, S.Y. Wang, J.C. Li, Q. Zhang, T.H. Hu, G.L. Shi

21. Measurement of In-field Variability for Active Seeding Depth Applications in Southeastern US

Proper seeding depth control is essential to optimize row-crop planter performance, and adjustment of planter settings to within field spatial variability is required to maximize crop yield potential. The objectives of this study were to characterize planting depth response to varying soil conditions within fields, and to discuss implementation of active seeding depth technologies in Southeastern US. This study was conducted in 2014 and 2015 in central Alabama for non-irrigated maize (Zea mays... A.M. Poncet, J.P. Fulton, T.P. Mcdonald, T. Knappenberger, R.W. Bridges, J. Shaw, K. Balkcom

22. Weed Detection Among Crops by Convolutional Neural Networks with Sliding Windows

One of the primary objectives in the field of precision agriculture is weed detection. Detecting and expunging weeds in the initial stages of crop growth with deep learning technique can minimize the usage of herbicides and maximize the crop yield for the farmers. This paper proposes a sliding window approach for the detection of weed regions using convolutional neural networks. The proposed approach involves two processes: (1) Image extraction and labelling, (2) building and training our neural... K. Kantipudi, C. Lai, C. Min, R.C. Chiang

23. Precision Agriculture Research Infrastructure for Sustainable Farming

Precision agriculture is an emerging area at the intersection of engineering and agriculture, with the goal of intelligently managing crops at a microscale to maximize yield while minimizing necessary resource. Achieving these goals requires sensors and systems with predictive models to constantly monitor crop and environment status. Large datasets from various sensors are critical in developing predictive models which can optimally manage necessary resources. Initial experiments at University... C. Lai, C. Min, R. Chiang, A. Hafferman, S. Morgan

24. eFields – An On-Farm Research Network to Inform Farm Recommendations

On-farm research has been traditionally used to provide local, field-scale information about agronomic practices. Farmers tend to have more confidence in on-farm research results because they are perceived to be more relevant to their farm operations compared to small plot research results. In recent years, more farmers have been conducting on-farm studies to help evaluate practices and input decisions.  Recent advances in precision agriculture technologies have stream-lined the on-farm... J.P. Fulton, E. Hawkins, R. Colley iii, K. Port, S. Shearer, A. Klopfenstein

25. AgDataBox: Web Platform of Data Integration, Software, and Methodologies for Digital Agriculture

Agriculture is challenging to produce more profitably, with the world population expected to reach some 10 billion people by 2050. Such a challenge can be achieved by adopting precision agriculture and digital agriculture (Agriculture 4.0). Digital agriculture has become a reality with the availability of cheaper and more powerful sensors, actuators and microprocessors, high-bandwidth cellular communication, cloud communication, and Big Data. Digital agriculture enables the flow of information... E.G. Souza, C. Bazzi, A. Hachisuca, R. Sobjak, A. Gavioli, N. Betzek, K. Schenatto, E. Mercante, M. Rodrigues, W. Moreira

26. Web Application for Automatic Creation of Thematic Maps and Management Zones - AgDataBox-Fast Track

Agriculture is challenging to produce more profitably, with the world population expected to reach some 10 billion people by 2050. Such a challenge can be achieved by adopting precision agriculture and digital agriculture (Agriculture 4.0). Digital agriculture (DA) has become a reality with the availability of cheaper and more powerful sensors, actuators and microprocessors, high-bandwidth cellular communication, cloud communication, and Big Data. DA enables information to flow from used agricultural... J. Aikes junior, E.G. Souza, C. Bazzi, R. Sobjak, A. Hachisuca, A. Gavioli, N. Betzek, K. Schenatto, W. Moreira, E. Mercante, M. Rodrigues

27. AgDataBox-IoT Application Development for Agrometeorogical Stations in Smart Farm

Currently, Brazil is one of the world’s largest grain producers and exporters. Brazil produced 125 million tons of soybean in the 2019/2020 growing season, becoming the world’s largest soybean producer in 2020. Brazil’s economic dependence on agribusiness makes investments and research necessary to increase yield and profitability. Agriculture has already entered its 4.0 version, also known as digital agriculture, when the industry has entered the 4.0 era. This new paradigm uses... A. Hachisuca, E.G. Souza, E. Mercante, R. Sobjak, D. Ganascini, M. Abdala, I. Mendes, C. Bazzi, M. Rodrigues

28. Limitations of Yield Monitor Data to Support Field-scale Research

Precision agriculture adoption on farms continues to grow globally on farms.  Today, yield monitors have become standard technologies on grain, cotton and sugarcane harvesters.  In recent years, we have seen industry and even academics leveraging the adoption of precision agriculture technologies to conduct field-scale, on-farm research.  Industry has been a primary driver of the increase in on-farm research globally through the development of software to support on-farm research. ... J.P. Fulton, S.A. Shearer, A. Gauci, A. Lindsey, D. Barker, E. Hawkins

29. Nitrogen Placement Considerations for Maize Production in the Eastern US Cornbelt

Proper fertilizer placement is essential to optimize crop performance and amount of applied nitrogen (N) along with crop yield potential. There exists several practices currently used in both research within farming operations on how and when to apply N to maize (Zea mays L). Split applications of N in Ohio is popular with farmers and provides an economic benefit but more recently some farmers have been using mid- and late-season N fertilizer applications for their maize production. ... J.P. Fulton, E. Hawkins, S. Shearer, A. Klopfenstein, J. Hartschuh, S. Custer

30. Evaluation of Indwelling Rumen Temperature Monitoring System for Dairy Calf Illness Detection and Management

Precision Dairy Farming technology has mostly focused on tools to improve cow care, but new tools are available to improve the care of pre-wean calves and heifers. These technologies apply real-time monitoring to measure individual animal data and detect a deviation from normal. On-farm validation of new technologies remains important for successful deployment of new technologies within commercial farms to understand how the technology can improve dairy calf welfare, performance, and health. The... J.M. Hartschuh, J.P. Fulton, S.A. Shearer, B.D. Enger, G.M. Schuenemann

31. Assessing the Distribution Uniformity of Broadcast-interseeded Cover Crops at Different Crop Stages by an Unmanned Aerial Vehicle

Drones can now carry larger payloads and have become more affordable, making them a viable option to use for broadcast-interseeding cover crops in the fall, prior to main crop harvest. This strategy has become popular in Ohio over the past two years. However, this new strategy arose quickly with a limited understanding of field performance of the drone’s distribution uniformity under different parameters such as rates, swath widths, speeds, or cash crop type. Therefore, the objective of... A.D. Thomas, J.P. Fulton, S. Khanal, O. Ortez, G. Mcglinch

32. Airborne Spectral Detection of Leaf Chlorophyll Concentration in Wild Blueberries

Leaf chlorophyll concentration (LCC) detection is crucial for monitoring crop physiological status, assessing the overall health of crops, and estimating their photosynthetic potential. Fast, non-destructive, and spatially extensive monitoring of LCC in crops is critical for accurately diagnosing and assessing crop health in large commercial fields. Advancements in hyperspectral remote sensing offer non-destructive and spatially extensive alternatives for monitoring plant parameters such as LCC.... K. Barai, C. Ewanik, V. Dhiman, Y. Zhang, U.R. Hodeghatta

33. Assessing Crop Yield and Profitability with Site-specific Seed Rate Management in Corn and Soybean Cropping Systems

Integrating the information about soil and topographic properties for variable rate seeding is a prerequisite for improved crop production and thus profit. However, limited studies have explored the geospatial and machine learning approaches to understand factors influencing crop yield and profit under site-specific seed rate management. The objectives of this study were to: a) observe the effect of variable seeding rate based on soil and topographic properties on soybean and corn grain yield,... J. Neupane, N. Joshi, J.P. Fulton, S. Khanal, A. B k, B. Bhattarai

34. Relationship of Activity and Temperature of Dairy Calves As Measured by Indwelling Rumen Boluses

Circadian rhythm of body temperature is naturally occurring in animals with a lower temperature at dawn and higher at dusk. In the past, this work was manually completed by a person using rectal temperature with temperature recorded every 2 or 3 hours. Rumen indwelling boluses allow for continuous temperature monitoring without human intervention. Human intervention can increase animal stress which can elevate temperature. Current literature indicates that the animal’s body temperature also... J.M. Hartschuh, J.P. Fulton, S.A. Shearer, B.D. Enger, G.M. Schuenemann

35. Deposition Characteristics of Different Style Spray Tips at Varying Speeds and Altitudes from an Unmanned Aerial System

The application of pesticides with a UAS has become a popular practice over the past few years within crop production. The ability to carry larger volumes of liquid i onboard, reduced costs, and simple operation has attributed to the increased popularity. Additionally, the increased number of fungicide applications in corn due to the tar spot disease has shown that the demand for aerial applications of all types has increased with UAS pesticide application technology providing the opportunity... A. Leininger, K. Verhoff, K. Lovejoy, A. Thomas, G. Davis, A. Emmons, J.P. Fulton

36. Creating Value from On-farm Research: Efields Data Workflow and Management Successes and Challenges

Farm operations today generate a large amount of data that can be difficult to properly manage. This challenge is further compounded when conducting on-farm research. The Ohio State University eFields program partners with farmers to conduct on-farm research and share results in a timely manner. Since 2017, the team has conducted and shared 987 trials across Ohio with the annual number of trials increasing from 45 to 292. This rapid increase has required development of a data workflow that streamlines... J.P. Fulton, D. Wilson, R. Tietje, E. Hawkins

37. Ohio State Food, Agricultural and Biological Engineering (FABE) Certificate Program for Digital Agriculture-moving from the Classroom to Online.

Digital Agriculture encompasses Precision Agriculture, Precision Livestock Farming, Controlled Environment Agriculture, On-Farm Research, and Enterprise Agriculture. We started developing teaching modules focused on Precision Agriculture. To start with, we are creating a series of modules focused on Variable Rate Technology (VRT) and Variable Rate Application (VRA). These initial modules were distilled from existing for credit courses offered by FABE and other extension and professional... K. Trefz, J.P. Fulton, S.A. Shearer, R. Venkatesh

38. Determining Desirable Swine Traits that Correlate to High Carcass Grades for Artificial Intelligence Predictions

With the global population continuing to grow, there has been an increased stress applied to the agriculture industry to improve efficiency and yield. To achieve this goal within the cattle industry, selection and reproductive decisions have been lucrative aspects, both genetically and fiscally. Breeding animal selection impacts farms through passing on favorable market, reproductive, and temperament traits. The cattle industry has experienced genetic advancement due to the flexibility of artificial... A.N. Spina, J.P. Fulton, S.A. Shearer, T. Berger-wolf, D. Drewry

39. Utilizing Image-based Artificial Intelligence for Grading Bovine Oocytes

For years, proper oocyte selection has been carried out with the precision of a lab technician’s eyes. The classification of oocytes using image-based artificial intelligence is a new technology that IVF lab technicians, cattle genetics companies, and veterinarians can utilize. Via the aspiration of the follicles on a cow’s ovaries, oocytes are able to be collected. Once oocytes are obtained from the ovaries of a cow, they are sent to an IVF lab to be cleaned and evaluated by a lab... G. Koppelman, J.P. Fulton, S. Khanal, T. Berger-wolf

40. The Ohio State University - Sponsor Presentation

... J.P. Fulton