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Rigney, J.D
Berger-Wolf, T
Lukach, J
Li, L
Li, T
Lavado, R
Luck, J.D
Le Roux, M
Lianqing, Z
Rivest, J
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Authors
Li, T
Hu, J
Gao, L
Hu, H
Bai, X
Liu, X
Sama, M.P
Shearer, S.A
Luck, J.D
Franzen, D.W
Endres, G
Ashley, R
Staricka, J
Lukach, J
McKay, K
Rodriguez, M
Civeira, G
Urricariet, S
Muschietti, P
Lavado, R
Stombaugh, T
Zandonadi, R.S
Luck, J.D
McDonald, T.P
McGraw, T
Sharda, A
Luck, J.D
Fulton, J.P
Shearer, S.A
Shearer, S.A
Mullenix, D
Vanacht, M
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
Rigney, J.D
Zhao, C
Wu, G
Meng, Z
Fu, W
Li, L
Wei, X
Lianqing, Z
Zhou, S
Songchao, C
Yafei, Y
Pimstein, A
Zur, Y
Le Roux, M
Pomar, C
Andretta, I
Rivest, J
Hauschild, L
Pomar, J
Bathke, K.J
Ge, Y
Choudhury, S.D
Luck, J.D
Shi, Y
Islam, M
Steele, K
Luck, J.D
Pitla, S
Ge, Y
Jhala, A
Knezevic, S
Dalla Betta, M.M
Puntel, L
Thompson, L
Mieno, T
Luck, J.D
Cafaro La Menza, N
Paccioretti, P
Bathke, K.J
Cross, T
Luck, J.D
Monroe, T
Luck, J.D
Marx, S
Stansell, J
Luck, J.D
Cross, T
Bathke, K.J
Smith, T
Narayana, C
VanderPlas, S
Bathke, K.J
Luck, J.D
Narayana, C
Thorson, N
Luck, J.D
Vinod, S
Luck, J.D
Kalra, A
Pitla, S
Luck, J.D
Spina, A.N
Fulton, J.P
Shearer, S.A
Berger-Wolf, T
Drewry, D
Balboa, G
Tobaldo, B
Lexow, T
Luck, J.D
Luck, J.D
Topics
Guidance, Robotics, Automation, and GPS Systems
Engineering Technologies and Advances
Precision A-Z for Practitioners
Precision Conservation
Engineering Technologies and Advances
Precision Weed Management
Engineering Technologies and Advances
Engineering Technologies and Advances
Proximal Sensing in Precision Agriculture
Remote Sensing Applications in Precision Agriculture
Precision Dairy and Livestock Management
Proximal and Remote Sensing of Soils and Crops (including Phenotyping)
Drone Spraying
On Farm Experimentation with Site-Specific Technologies
Digital Agriculture Solutions for Soil Health and Water Quality
Precision Crop Protection
In-Season Nitrogen Management
Extension or Outreach Education of Precision Agriculture
Geospatial Data
Artificial Intelligence (AI) in Agriculture
Education of Precision Agriculture Topics and Practices
Type
Poster
Oral
Year
2012
2010
2014
2016
2018
2024
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Filter results26 paper(s) found.

1. Revising Nitrogen Recommendations For Wheat In Response To The Need For Support Of Variable-rate Nitrogen Application

Sampling studies in North Dakota conducted from 1994 to 2003 showed that variable-rate N application could be practically directed with zone soil sampling. Results from variable-rate N studies using zone soil sampling were often less than rewarding due in part to the use of a whole-field predicted yield-based formula for developing the N recommendation in each zone. Nitrogen rate studies on spring wheat and durum were established in 2005 through 2009 to reexamine N recommendations. The results... D. Franzen, G. Endres, R. Ashley, J. Staricka, J. Lukach, K. Mckay

2. The Application Of Fertilizer Using Management Zone (MZ) In Pampas Soils With Texture Variability Affects Residual Nitrate After Harvest

          The maize yields are usually associated with soil texture heterogeneity in western Argentinean Pampas.  In this area, the uniform fertilizer management (UM) increased the risk of nitrate leaching due to over-fertilizing but it could be minimized by using different management zones criteria (MZ). In a field experiment, the nitrates distribution in soil depth (0-1.80 m) at sowing and harvest times (residual Nitrate) and the maize... M. Rodriguez, G. Civeira, S. Urricariet, P. Muschietti, R. Lavado

3. Tools For Evaluating The Potential Of Automatic Section Control

One of the newest technologies in precision agriculture is automatic section control on application equipment. This technology has tremendous potential to reduce wasted inputs, especially on irregularly shaped fields. Paybacks are not necessarily as great on rectangular fields. Producers considering adoption of the technology need to decide whether they will receive sufficient payback for their field shapes. They must also decide... T. Stombaugh, R.S. Zandonadi, J.D. Luck, T.P. Mcdonald, T. Mcgraw

4. 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

5. 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

6. 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

7. 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

8. Spray Pattern and Droplet Spectra Characteristics from an Actively Controlled Variable-Orifice Nozzle

... M.P. Sama, S.A. Shearer, J.D. Luck

9. NOAA's National Geodetic Survey?s National Spatial Reference System And The National Height Modernizatio

The National Geodetic Survey (NGS) is responsible for the establishment and maintenance of the National Spatial Reference System (NSRS). NGS manages a network of Continuously Operating Reference Stations (CORS) that provides Global Navigation Satellite System (GNSS) data and serves as the backbone of the NSRS.  Our goal is to maintain a network of stations to serve as control for any project undertaken by local surveyors.  In addition, numerous other applications benefit from an... J.D. Rigney

10. The Device of Air-assisted Side Deep Precision Fertilization for Rice Transplanter

Rice is the most important crop in China, which has the largest plant area. Fertilization is an important process of rice production, which directly affects the yield of crops, reasonable and effective use of chemical fertilizer can improve the yield of crops. At present, the mechanization level of rice fertilization is very low in China, and the artificial fertilization requires a large amount of fertilizer which caused the uneven distribution. The rice side deep fertilizing is an ideal way of... C. Zhao, G. Wu, Z. Meng, W. Fu, L. Li, X. Wei

11. Development of Micro-tractor-based Measurement Device of Soil Organic Matter Using On-the-go Visual-near Infrared Spectroscopy in Paddy Fields of South China

Soil organic matter (SOM) is an essential soil property for assessing the fertility of paddy soils in South China. In this study, a set of micro-tractor-based on-the-go device was developed and integrated to measure in-situ soil visible and near infrared (VIS–NIR) spectroscopy and estimate SOM content. This micro-tractor-based on-the-go device is composed of a micro-tractor with toothed-caterpillar band, a USB2000+ VIS–NIR spectroscopy detector, a self-customized steel plow and a self-customized... Z. Lianqing, S. Zhou, C. Songchao, Y. Yafei

12. Retrieving Crops' Quantitative Biophysical Parameters Through a Newly Developed Multispectral Sensor for UAV Platforms

Today’s intensive agricultural production needs to increase its efficiency in order to keep its profitability in the current market of decreasing prices on one hand, and to reduce the environmental impact on the other. Crop growers are starting to adopt side dressing nitrogen fertilization as part of their fertilization programs, for which they need accurate information about biomass development and nitrogen condition in the crop. This information is usually acquired through ground sampling,... A. Pimstein, Y. Zur, M. Le roux

13. Precision Feeding Can Significantly Reduce Lysine Intake and Nitrogen Excretion Without Compromising the Performance of Growing Pigs

The impact of using a mathematical model estimating real-time daily lysine requirements in a sustainable precision feeding program for growing pigs was investigated in two performance trials. Three treatments were tested in the first trial (60 pigs of 41.2±0.5 kg): a three-phase feeding program (3P) obtained by blending fixed proportions of feeds A (high nutrient concentration) and B (low nutrient concentration); and two daily-phase feeding programs in which the blended proportions of feeds... C. Pomar, I. Andretta, J. Rivest, L. Hauschild, J. Pomar

14. Enhancing Nutrient-related Stress Detection: High Throughput Phenotyping and Image Analysis for Improved Precision

In the 21-century agriculture has the unique responsibility to provide food, fuel, fiber and feed for the growing population under the stress of climate change and diminishing natural resources. A feat that will take considerable change to the sustainability of such practices. One of which is the idea of assessing phenotypic expression of complex traits in response to environmental factors. This idea elevates the use of phenotyping to quantitatively monitor stress manifestation.   Therefore,... K.J. Bathke, Y. Ge, S.D. Choudhury, J.D. Luck

15. Onboard Weed Identification and Application Test with Spraying Drone Systems

Commercial spraying drone systems nowadays have the ability to implement variable rate applications according to pre-loaded prescription maps. Efforts are needed to integrate sensing and computing technologies to realize on-the-go decision making such as those on the ground based spraying systems. Besides the understudied subject of drone spraying pattern and efficacy, challenges also exist in the decision making, control, and system integration with the limits on payload and flight endurance... Y. Shi, M. Islam, K. Steele, J.D. Luck, S. Pitla, Y. Ge, A. Jhala, S. Knezevic

16. Determining Site-Specific Soybean Optimal Seeding Rate Using On-Farm Precision Experimentation

Ten on-farm precision experiments were conducted in Nebraska during 2018 – 2022 to address the following: i) determine the Economic Optimal Seeding Rates (EOSR), ii) identify the most important site-specific variables influencing the optimal seeding rates for soybeans. Seeding rates ranged from 200,000 to 440,000 seeds ha-1, and treatments were randomized and replicated in blocks across the entire field. The study was implemented using a variable rate prescription. Yield... M.M. Dalla betta, L. Puntel, L. Thompson, T. Mieno, J.D. Luck, N. Cafaro la menza, P. Paccioretti

17. Fertigation Management Strategies Effect on Residual Nitrates in the Soil Profile and Ground Water

Nitrogen is an input that is vital for growth and productivity within the corn belt states of the U.S. However, when nitrogen as an input into agricultural cropping systems is often over-applied and thus not optimally utilized by the cropping system. Therefore, it is at risk of loss within the environment through processes of leaching, denitrification, and volatilization. This is a major concern in Nebraska, as the reality is that much of the state’s groundwater has been contaminated with... K.J. Bathke, T. Cross, J.D. Luck

18. Development and Evaluation of a Novel Variable-orifice Nozzle Flow and Droplet Size Control System

Spray drift from crop production operations has been a critical concern across the U.S. as evidenced by the EPA’s efforts to mitigate pesticide drift. Recently, a novel spray control system was developed and evaluated which provided real-time control of both spray droplet size and flow rate. This was achieved via electromechanical control of a variable orifice nozzle along with a novel control system which incorporates real-time weather data to vary system pressure and orifice size and shape.... T. Monroe, J.D. Luck, S. Marx

19. Sensor Based Fertigation Management

Sensor-based fertigation management (SBFM) is a relatively new technology for directing nitrogen (N) decisions, specifically tailored for delivery of N via center pivot irrigation systems (fertigation). The development of SBFM began in 2018 at the University of Nebraska-Lincoln with the help of cooperating producers across the state. Over two dozen field sites provided testbeds for the development and evaluation of the technology. The key technique in this fertigation approach is the... J. Stansell, J.D. Luck, T. Cross, K.J. Bathke, T. Smith

20. In-Season Nitrogen Management: Leveraging Data Visualization for Precision Agriculture

The agricultural sector nitrogen management-related research has been extensively high by experiencing a data revolution, with an increasing influx of information from diverse sources like sensors, satellites, and Unmanned Aerial Vehicles (UAVs) imaging technologies. In this context, effective in-season nitrogen data management has become a critical factor; however, the ability of farmers to visualize the impact of such technologies in field research settings has been limited. This project... C. Narayana, S. vanderplas, K.J. Bathke, J.D. Luck

21. Pesticide Application Management Toolset for Improved Worker Protection

The practice of pesticide use has been widely adopted by production agriculture to maximize yields since the 1950s. Even though it provides beneficial economic returns to the farmers, it also enhances the risk of environmental pollution and is directly associated with the risk of poisoning to agricultural workers. While adhering to United States Federal Environmental Protection Agency (EPA) Worker Protection Standard (WPS) guidelines, the current systems need considerable time to provide crucial... C. Narayana, N. Thorson, J.D. Luck

22. A Multi-level Filtering Approach for Yield Data Cleaning and Automated Analysis Using R Programming

In the realm of on-farm studies, a recurring challenge surfaces in the form of disparities between field implementation and experimental design within Rx treatment plots. This disjunction underscores the critical need for intensive data cleaning and analysis to generate precise outcomes for the experiments. Complicating matters is the absence of readily available ground truth data for comparative analyses, making it particularly challenging to ascertain the extent of necessary data cleaning and... S. Vinod, J.D. Luck

23. AIR-N: AI-Enabled Robotic Precision Nitrogen Management Platform

The AI-Enabled Robotic Nitrogen Management (AIR-N) system is a versatile, cloud-based platform designed for precision nitrogen management in agriculture, targeting the reduction of nitrous oxide emissions as emphasized by the EPA. This end-to-end integrated system is adaptable to various cloud services, enhancing its applicability across different farming environments. AIR-N's framework consists of three primary components: a sensing layer for gathering data, a cloud layer where AI and machine... A. Kalra, S. Pitla, J.D. Luck

24. 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

25. Driving Growth Through Precision Agriculture: the Evolution of the Nebraska On-farm Research Network

The Nebraska On-Farm Research Network (NOFRN), allows farmers to answer production, profitability and sustainability questions in their own field. The University of Nebraska (USA) sponsors the NOFRN and provides technical support in the experimental design, execution, data analysis and results dissemination. In recent years, precision agriculture technologies have expanded network capabilities through an increasing ​number of experiments and provided new avenues for data analyses. The goal is... G. Balboa, B. Tobaldo, T. Lexow, J.D. Luck

26. University of Nebraska-Lincoln - Sponsor Presentation

... J.D. Luck