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Nafziger, E.D
Rocha, D.M
Milics, G
Holthaus, D
Martin, S.W
Rudramuni, T
Rabia, A.H
Lamker, D
Bishop-Hurley, G.J
Blacker, C
Lenz-Wiedemann, V
Li, F
Hartschuh, J.M
Nino, P
Berretta, B.G
Zebrath, B
Long, D.S
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Authors
Nino, P
Vanino, S
Lupia, F
Altobelli, F
Vuolo, F
Namdarian, I
De Michele, C
Miao, Y
Li, F
Romier, C
Hyrien, M
Lamker, D
Liu, B
Miao, Y
Feng, G
Yue, S
Li, F
Gao, X
Miao, Y
Cao, Q
Cui, Z
Li, F
Dao, T.H
Khosla, R
Chen, X
Long, D.S
Wuest, S.B
Williams, J.D
Bailey, M.J
Reese, C.L
Clay, D.E
Beck, D.L
Clay, S.A
Long, D.S
Shahinian, M
Long, D.S
Velandia, M
Mooney, D.F
Roberts, R.K
English, B.C
Larson, J.A
Lambert, D.M
Larkin, S.L
Marra, M.C
Rejesus, R
Martin, S.W
Paxton, K.W
Mishra, A
Wang, C
Segarra, E
Reeves, J.M
McNeill, D
Bishop-Hurley, G.J
Irvine, L
Freeman, M
Bellenguez, R
Cao, Q
Miao, Y
Feng, G
Li, F
Liu, B
Gao, X
Liu, Y
Giriyappa, M
Sheshadri, T
Hanumanthappa, D
Shankar, M
Salimath, S.B
Rudramuni, T
Raju, N
Devakumar, N
Mallikaarjuna, G
Malagi, M.T
Jangandi, S
Huang, S
Miao, Y
Yuan, F
Gnyp, M.L
Yao, Y
Cao, Q
Lenz-Wiedemann, V
Bareth, G
Nyeki, A
Milics, G
Kovacs, A.J
Neményi, M
Kalmar, J
Cambouris, A
Lajili, A
Chokmani , K
Perron, I
Adamchuk, V
Biswas , A
Zebrath, B
Bean, G.M
Kitchen, N.R
Camberato, J.J
Ferguson, R.B
Fernandez, F.G
Franzen, D.W
Laboski, C.A
Nafziger, E.D
Sawyer, J.E
Scharf, P.C
Taylor, J
Shahar, Y
James, P
Blacker, C
Leese, S
Sanderson, R
Kavanagh, R
Li, D
Miao, Y
Fernández, .G
Kitchen, N.R
Ransom, C.
Bean, G.M
Sawyer, .E
Camberato, J.J
Carter, .R
Ferguson, R.B
Franzen, D.W
Franzen, D.W
Franzen, D.W
Franzen, D.W
Laboski, C.A
Nafziger, E.D
Shanahan, J.F
Hartschuh, J.M
Fulton, J.P
Shearer, S.A
Enger, B.D
Schuenemann, G.M
Avila, E.N
Bazzi, C.L
Oliveira, W.K
Schenatto, K
Sobjak, R
Rocha, D.M
Brorsen, W
Poursina, D
Patterson, C
Mieno, T
Edge, B
Nafziger, E.D
McFadden, J
Erickson, B
Lowenberg-DeBoer, J
Milics, G
Spiesman, B
Grijalva, I
Holthaus, D
McCornack, B
Stahl, K
Hartschuh, J.M
Gahler, A
Rabia, A.H
Eldeeb, E
Rabia, A.H
Eldeeb, E
Coppola, A
Zsebő, S
Kukorelli, G
Vona, V
Bede, L
Stencinger, D
Kovacs, A
Milics, G
Kulmany, I.M
Horváth, B
Hegedűs, G
Abdinoor, J.A
Hartschuh, J.M
Fulton, J.P
Shearer, S.A
Enger, B.D
Schuenemann, G.M
Hartschuh, J.M
Minyo, R
Rai, S
Sharda, A
Berretta, B.G
Rabia, A.H
Allam, D.G
Abdelaty, E.F
Abderaouf, E.A
Rabia, A.H
Salem, M.A
Salem, M.A
Rabia, A.H
Topics
Remote Sensing Applications in Precision Agriculture
Precision Nutrient Management
Education and Training in Precision Agriculture
Proximal Sensing in Precision Agriculture
Precision Nutrient Management
Precision Conservation
Remote Sensing Applications in Precision Agriculture
Precision Carbon Management
Profitability, Sustainability, and Adoption
Precision Livestock Management
Precision Nutrient Management
Remote Sensing Applications in Precision Agriculture
Precision Agriculture and Climate Change
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
In-Season Nitrogen Management
Geospatial Data
ISPA Community: Nitrogen
Precision Dairy and Livestock Management
Big Data, Data Mining and Deep Learning
On Farm Experimentation with Site-Specific Technologies
Drivers and Barriers to Adoption of Precision Ag Technologies or Digital Agriculture
In-Season Nitrogen Management
Proximal and Remote Sensing of Soils and Crops (including Phenotyping)
Land Improvement and Conservation Practices
Scouting and Field Data collection with Unmanned Aerial Systems
Precision Dairy and Livestock Management
Precision Crop Protection
Artificial Intelligence (AI) in Agriculture
Type
Poster
Oral
Year
2012
2010
2014
2016
2018
2022
2024
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Filter results33 paper(s) found.

1. Quantifying Spatial Variability Of Indigenous Nitrogen Supply For Precision Nitrogen Management In North China Plain

... Y. Miao, Q. Cao, Z. Cui, F. Li, T.H. Dao, R. Khosla, X. Chen

2. Contour Planting: A Strategy To Reduce Soil Erosion On Steep Slopes

  Practices that combine GPS-based guidance for terrain contouring and tillage for runoff detention have potential to increase water infiltration and reduce runoff.  The objective of this study was to investigate contour planting as a means to reduce soil erosion on steep slopes of the Columbia Plateau dryland wheat region.  An exploratory field study was conducted on a Ritzville... D.S. Long, S.B. Wuest, J.D. Williams, M.J. Bailey,

3. Nitrogen And Water Stress Impacts Hard Red Spring Wheat (Triticum Aestivum) Canopy Reflectance

  Remote sensing-based in-season N recommendations have been proposed as a technique to improve N fertilizer use efficiency. Remote sensing estimation of South Dakota hard red spring wheat N requirements needs assessment. Research objectives were: (1) determine the effect of an in-season N application on grain yield, yield loss to nitrogen stress (YLNS), and grain protein; and (2) assess if remote sensing collected at different growth stages may be used to predict yield... C.L. Reese, D.E. Clay, D.L. Beck, S.A. Clay, D.S. Long, M. Shahinian

4. On-combine Sensing Technique For Mapping Straw Yield Within Wheat Fields

Straw from production of wheat is available for conversion to bioenergy. However, not all of this straw is available for conversion because a certain amount must be returned to the soil for conservation. County and state-wide inventories do not account for variation within farm fields. In this study, a technique is described that applies information from on-combine crop sensors into estimation of straw yield across fields. Straw yield... D.S. Long, ,

5. Cotton Precision Farming Adoption In The Southern United States: Findings From A 2009 Survey

The objectives of this study were 1) to determine the status of precision farming technology adoption by cotton producers in 12 states and 2) to evaluate changes in cotton precision farming technology adoption between 2000 and 2008. A mail survey of cotton producers located in Alabama, Arkansas, Florida, Georgia, Louisiana, Mississippi, Missouri, North Carolina, South Carolina, Tennessee, Texas and Virginia was conducted in February and March of 2009 to establish the use of precision farming technologies... M. Velandia, D.F. Mooney, R.K. Roberts, B.C. English, J.A. Larson, D.M. Lambert, S.L. Larkin, M.C. Marra, R. Rejesus, S.W. Martin, K.W. Paxton, A. Mishra, C. Wang, E. Segarra, J.M. Reeves

6. A Preliminary Evaluation Of Proximity Loggers To Detect Oestrus Behaviour In Grazing Dairy Cows

... D. Mcneill, G.J. Bishop-hurley, L. Irvine, M. Freeman, R. Bellenguez

7. Applications for Precision Agriculture: the Italian Experience of SIRIUS Project

    This paper reports the results of the project SIRIUS (Sustainable Irrigation water management and River-basin... P. Nino, S. Vanino, F. Lupia, F. Altobelli, F. Vuolo, I. Namdarian, C. De michele

8. Deriving Nitrogen Indicators of Maize Using the Canopy Chlorophyll Content Index

Many spectral indices have been proposed to derive aerial nitrogen (N) status parameters of crops in recent decades. However, most of red light based spectral indices easily loss sensitivity at moderate-high aboveground biomass. The objective of present study is to assess the performance of red edge based... Y. Miao, F. Li

9. A New Approach to Yield Map Creation

    One of the barriers to using yield maps as a data layer in precision agriculture activities is that the maps being generated to day are not very accurate in representing what really happened in field.  Numerous data errors in the way the data is collected, poor calibration habits on the part of operators... C. Romier, M. Hyrien, D. Lamker

10. Different Leaf Sensing Approaches for the Estimation of Winter Wheat Nitrogen Status

Nondestructive real time diagnosis of crop N status is crucial to the development of precision nitrogen (N) management strategies. Chlorophyll meter has been a popular sensor for such purposes and different approaches to use this sensor has been developed using a threshold value, nitrogen sufficiency index (NSI) or ratio of... B. Liu, Y. Miao, G. Feng, S. Yue, F. Li, X. Gao

11. Evaluating Different Nitrogen Management Strategies For The Intensive Wheat-Maize System In North China Plain

The sustainable agricultural development involves both environmental challenges and production goals to meet growing food demand. However, excessive nitrogen (N) applications are threatening the sustainability of intensive agriculture in the North China Plain (NCP). Improved N management should result in greater N use efficiency (NUE) and producer profit while reducing the risk of environmental contamination. Therefore, developing and disseminating feasible N management strategies... Q. Cao, Y. Miao, G. Feng, F. Li, B. Liu, X. Gao, Y. Liu

12. Precision Nutrient Management For Enhancing The Yield Of Groundnut In Peninsular India

               Groundnut is an important oil seed crop grown in an area of around 8 lakh hectares in Karnataka state of India under rainfed conditions. In these situations farmers applied inadequate fertilizer without knowing the initial nutrient status of the soil which resulted in low nutrient use efficiency that intern lead to low productivity of groundnut in these areas. Soil fertility deterioration due to... M. Giriyappa, T. Sheshadri, D. Hanumanthappa, M. Shankar, S.B. Salimath, T. Rudramuni, N. Raju, N. Devakumar, G. Mallikaarjuna, M.T. Malagi, S. Jangandi

13. Potential Improvement in Rice Nitrogen Status Monitoring Using Rapideye and Worldview-2 Satellite Remote Sensing

For in-season site-specific nitrogen (N) management of rice to be successful, it is crucially important to diagnose rice N status efficiently across large area in a timely fashion. Satellite remote sensing provides a promising technology for crop growth monitoring and precision management over large areas. The FORMOSAT-2 satellite remote sensing imageries with 4 wavebands have been used to estimate rice N status. The objective of this study was to evaluate the potential of using high spatial resolution... S. Huang, Y. Miao, F. Yuan, M.L. Gnyp, Y. Yao, Q. Cao, V. Lenz-wiedemann, G. Bareth

14. Climate Sensitivity Analysis on Maize Yield on the Basis of Precision Crop Production

In this paper by prediction we have defined maize yield in precision plant production technologies according to five different climate change scenarios (Ensembles Project) until 2100 and in one scenario until 2075 using DSSAT v. 4.5.0. CERES-Maize decision support model. Sensitivity analyses were carried out. The novelty of the method presented here is that precision, variable rate technologies from relatively small areas (in our case 2500 m2) enable a large amount of data to be collected... A. Nyeki, G. Milics, A.J. Kovacs, M. Neményi, J. Kalmar

15. Use of Proximal Soil Sensing to Delineate Management Zones in a Commercial Potato Field in Prince Edward Island, Canada

Management zones (MZs) are delineated areas within an agricultural field with relatively homogenous soil properties. Such MZs can often be used for site-specific management of crop production inputs. The purpose of this study was to determine the efficiency of two proximal soil sensors for delineating MZs in an 8.1-ha commercial potato (Solanum tuberosum L.) field in Prince Edward Island (PEI), Canada. A galvanic contact resistivity sensor (Veris-3100 [Veris]) and electromagnetic induction sensors... A. Cambouris, A. Lajili, K. Chokmani , I. Perron, V. Adamchuk, A. Biswas , B. Zebrath

16. Corn Nitrogen Fertilizer Recommendation Models Based on Soil Hydrologic Groups Aid in Predicting Economically Optimal Nitrogen Rates

Nitrogen (N) fertilizer recommendations that match corn (Zea mays L.) N needs maximize grower profits and minimize water quality consequences. However, spatial and temporal variability makes determining future N requirements difficult. Studies have shown no single soil or weather measurement is consistently increases accuracy, especially when applied over a regional scale, in predicting economically optimal N rate (EONR). Basing site N response on soil hydrological group could help account for... G.M. Bean, N.R. Kitchen, J.J. Camberato, R.B. Ferguson, F.G. Fernandez, D.W. Franzen, C.A. Laboski, E.D. Nafziger, J.E. Sawyer, P.C. Scharf

17. Experiences in the Development of Commercial Web-Based Data Engines to Support UK Growers Within an Industry-Academic Partnership

The lifecycle of Precision Agriculture data begins the moment that the measurement is taken, after which it may pass through each multiple data processes until finally arriving as an output employed back in the production system. This flow can be hindered by the fact that many farm datasets have different spatial resolutions. This makes the process to aggregate or analyse multiple Precision Agriculture layers arduous and time consuming.  Precision Decisions Ltd located in Yorkshire,... J. Taylor, Y. Shahar, P. James, C. Blacker, S. Leese, R. Sanderson, R. Kavanagh

18. Developing a Machine Learning and Proximal Sensing-based In-season Site-specific Nitrogen Management Strategy for Corn in the US Midwest

Effective in-season site-specific nitrogen (N) management strategies are urgently needed to ensure both food security and sustainable agricultural development. Different active canopy sensor-based precision N management strategies have been developed and evaluated in different parts of the world. Recent studies evaluating several sensor-based N recommendation algorithms across the US Midwest indicated that these locally developed algorithms generally did not perform well when used broadly across... D. Li, Y. Miao, .G. Fernández, N.R. Kitchen, C. . Ransom, G.M. Bean, .E. Sawyer, J.J. Camberato, .R. Carter, R.B. Ferguson, D.W. Franzen, D.W. Franzen, D.W. Franzen, D.W. Franzen, C.A. Laboski, E.D. Nafziger, J.F. Shanahan

19. 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

20. Geographic Database in Precision Agriculture for the Development of AI Research

Agriculture 4.0 has profoundly transformed production processes by incorporating technologies such as Precision Agriculture, Artificial Intelligence, the Internet of Things, and telemetry. This evolution has enabled more accurate and timely decision-making in agriculture. In response to this movement, the Precision Agriculture Laboratory (AgriLab) of UTFPR, located in Medianeira, proposes the establishment of a consistent and standardized database. This database is continually updated with surveys... E.N. Avila, C.L. Bazzi, W.K. Oliveira, K. Schenatto, R. Sobjak, D.M. Rocha

21. Using Informative Bayesian Priors and On-farm Experimentation to Predict Optimal Site-specific Nitrogen Rates

Most U.S. Corn Belt states now recommend the Maximum Return to Nitrogen (MRTN) method for determining optimal nitrogen rates, which is based on 15 years of on-farm yield response to nitrogen trials. The MRTN method recommends a uniform rate for a region of a state. This study combines Illinois MRTN data, Bayesian methods, and on-farm experimentation from the Data Intensive Farm Management (DIFM) project to provide site-specific nitrogen recommendations. On-farm trials are now being used to provide... W. Brorsen, D. Poursina, C. Patterson, T. Mieno, B. Edge, E.D. Nafziger

22. Global Adoption of Precision Agriculture: an Update on Trends and Emerging Technologies

The adoption of precision agriculture (PA) has been mixed. Some technologies (e.g., Global Navigation Satellite System (GNSS) guidance) have been adopted rapidly worldwide wherever there is mechanized agriculture. Adoption of some of the original PA technologies introduced in the 1990s has been modest almost everywhere (e.g., variable rate fertilizer). New and more advanced technologies based on robotics, uncrewed aerial vehicles (UAVs), machine vision, co-robotic automation, and artificial intelligence... J. Mcfadden, B. Erickson, J. Lowenberg-deboer, G. Milics

23. Sampling Bumble Bees and Floral Resources Using Deep Learning and UAV Imagery

Pollinators, essential components of natural and agricultural systems, forage over relatively large spatial scales. This is especially true of large generalist species, like bumble bees. Thus, it can be difficult to estimate the amount and diversity of floral resources available to them. Floral cover and diversity are often estimated over large areas by extrapolation from small scale samples (e.g., a 1-m quadrat) but the accuracy of such estimates can vary depending on the spatial patchiness of... B. Spiesman, I. Grijalva, D. Holthaus, B. Mccornack

24. Evaluation of Fall and Spring Nitrogen Rates Effect on Cereal Rye Forage Crude Protein and Tillering Using NDVI and Canopeo to Make Infield Nitrogen Rate Decisions

Fall applied nitrogen has been used to increase plant tiller and protein in wheat but less research has been done of its effects on cereal rye forage and how NDVI and Canopeo readings can be used to make nitrogen application management decisions. This study took place at the Ohio State University North Central Agricultural Research Station in Fremont, Ohio. The experiment is a randomized complete block split-plot design with four nitrogen rates in the fall (0, 30, 60, and 90 lbs/ac) and in the... K. Stahl, J.M. Hartschuh, A. Gahler

25. Dynamic Management Zones for Real-time Precision Agriculture Optimization

Precision agriculture is an evolving management approach aimed at optimizing resource utilization, enhancing financial returns, and mitigating environmental impacts. The dynamic nature of agricultural conditions throughout a growing season necessitates the integration of innovative remote sensing and precision agriculture techniques. This research explores the creation of dynamic management zones (DMZ) that adapt in real-time to evolving soil and crop conditions. This study focuses on the establishment... A.H. Rabia, E. Eldeeb

26. Modelling Hydrological Processes in a Wadi Basin in Egypt: Wadi Kharouba Case Study

Wadi Flash Flood (WFF) is one of the most crucial problems facing the north‐western coastal region in Egypt. Water harvesting (WH) approaches may be an effective tool to reduce the WFF risk while storing the runoff water for agricultural activities. In this study, the Agarma sub-catchment of the Wadi Kharouba was taken as a reference investigation site to study terraced WA systems. The main problem in this area is that local farmers independently build terraces using traditional knowledge to... A.H. Rabia, E. Eldeeb, A. Coppola

27. Comparison of NDVI Values at Different Phenological Stages of Winter Wheat (Triticum Aestivum L.)

The main objective of this study is to monitor, detect and quantify the presence of live green vegetation with the MicaSense RedEdge-MX Dual Camera System (MS) mounted on a DJI Matrice 210 V2 and GreenSeeker HCS 250 (GS) in winter wheat (Triticum aestivum L.) by using Normalized Difference Vegetation Index (NDVI). Surveys were conducted in the North-Western part of Hungary, in Mosonmagyaróvár on six different dates. A small-scale field trial in winter wheat was constructed as a randomized... S. Zsebő, G. Kukorelli, V. Vona, L. Bede, D. Stencinger, A. Kovacs, G. Milics, I.M. Kulmany, B. Horváth, G. Hegedűs, J.A. Abdinoor

28. 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

29. Fungicide Application Methods and Corn Variety Effect on Corn Silage Deoxynivalenol Levels

Mycotoxin contamination is a major challenge for dairy producers. Deoxynivalenol, (DON) a mycotoxin produced by the fungus Fusarium graminearum, can infect both the corn stalk and ear. Studies have found that 86% of corn silage samples have some concentration of DON. Deoxynivalenol causes major issues in the dairy industry causing decreased milk production, lower components, higher SCC, and decreased reproductive performance. The objective of this research project was to determine... J.M. Hartschuh, R. Minyo

30. Enhancing Seeding Efficiency: Evaluating Row Cleaners with Computer Vision in Precision Agriculture

In precision agriculture, the effective sowing of seeds is crucial but often hindered by challenges like hair pinning, low soil temperatures, and heavy residue on the soil surface. To address these issues, row cleaners are employed to clear the path for seeder opener discs, ensuring a clean, uniform trench for seed placement. This study examines the performance of various row cleaner models and introduces a novel method for their automatic, quantitative evaluation using computer vision technology.  We... F. Sidharth, A. Sharda, B.G. Berretta

31. Utilizing Thermal and RGB Imaging for Nutrient Deficiency and Chlorophyll Status Evaluation in Plants

As global population growth and climate change continue to challenge food security, addressing agricultural issues efficiently and cost-effectively is vital for enhancing productivity. Integrating technology into agriculture, particularly through timely interventions, offers promising solutions to mitigate challenges before they escalate. This study investigates the feasibility of using thermal and RGB imaging as efficient, non-destructive methods to assess nutrient deficiencies and chlorophyll... A.H. Rabia, D.G. Allam, E.F. Abdelaty, E.A. Abderaouf

32. Potato Disease Detection Using Laser Speckle Imaging and Deep Learning

Early detection of potato diseases is essential for minimizing crop loss. Implementing advanced imaging techniques can significantly improve the accuracy and efficiency of disease detection in potato crops. Leveraging machine learning algorithms can further enhance the speed and precision of disease identification, enabling timely intervention measures. This work presents a novel potato disease detection technique using whole-potato speckle imaging and deep learning. Laser Speckle Imaging (LSI),... A.H. Rabia, M.A. Salem

33. Development of a High-throughput UAV System for Precision Weed Detection and Control Using Laser Speckle Imaging and UV-C Irradiation

Traditional weed control methods, predominantly reliant on herbicides or labor-intensive ground robots, present notable environmental and efficiency challenges within agricultural practices. To address these concerns, this study introduces an innovative approach utilizing unmanned aerial vehicles (UAVs) for autonomous weed detection and control in agricultural fields. Our proposed system depends on the agility of UAV platforms, integrating two primary technologies. Firstly, Laser Speckle Imaging... M.A. Salem, A.H. Rabia