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Nielsen, M.B
Betzek, N
Bruggeman, S
Bourgain, O
Nguyen, T
Hamann, H.F
Bryan, W
Ragab, R
Ferrandis Vallterra, S
Hijazi, B
Ferraz Pueyo, C
Gonzalez-Dugo, V
Guo, W
Issaka, F
Neményi, M
Burns, D
Galzki, J
Hüging, H
Fausti, S
Bajwa, S
Botsali, F.M
Franzen, D.W
Frizzel, L
Nyéki , A
Guimarães, M
Yoshida, K
Yilma, W.A
Fassana, N
Yida, D
Rejesus, R
Hackl, H
Bodas, V
Berger, A.G
Whelan, B.M
Rainbow, R
Frazier, R
Dhawale, N
Bosompem, M
Destain, M
Wilson, R
Gérard, B.G
Gregory, S
Boydston, R
Fernandez, F.G
Gu, H
Howatt, T
Westerdijk, K
Nienaber, J.A
Dong, R
Fox, C.W
Whattoff, D
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Authors
Klein, R.N
Wilson, R
Burns, D
Overstreet, D
Kruse, D
Frazier, R
Blanche, D
Vancutsem, F
Leemans, V
Ferrandis Vallterra, S
Bodson, B
Destain, J
Destain, M
Dumont, B
Hongo, C
Furukawa, T
Sigit, G
Maki, M
Honma, K
Yoshida, K
Oki, K
Shirakawa, H
Baresel, P
Mistele, B
Yuncai, H
Schmidhalter, U
Hackl, H
vangeyte, J
cointault, F
paindavoine, M
pieters, J
Hijazi, B
Ragab, R
Bourgain, O
Duval, C
Llorens, J
Cointault, F
Hijazi, B
Dubois, J
Vangeyte, J
Paindavoine, M
Bosompem, M
Kwarteng, J.A
Ntifo-Siaw, E
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
Pena-Yewtukhiw, E.M
Mata-Padrino, D
Bryan, W
Zarco-Tejada, P.J
Gonzalez-Dugo, V
Girona, J
Fereres, E
Bellvert, J
Feher, T
Kocks, C
Kempenaar, C
Westerdijk, K
Basso, B
Destain, J
Bodson, B
Destain, M
Dumont, B
Adamchuk, V.I
Dhawale, N
Rene-Laforest, F
Sivarajan, S
Bajwa, S
Nowatzki, J
Bajwa, S
Nowatzki, J
Harnisch, W
Schatz, B
Anderson, V
Rodrigues Junior, F.A
Ortiz-Monasterio, I
Zarco-Tejada, P.J
Ammar, K
Gérard, B.G
Kovács, A.J
Nyéki, A
Milics, G
Neményi, M
Ruiz, M
Yida, D
Molin, J.P
Colaço, A.F
Nowatzki, J
Bajwa, S
Sivarajan, S
Maharlooei, M
Kandel, H
Sanchez, L.A
Klein, L.J
Claassen, A
Lew, D
Mendez-Costabel, M
Sams, B
Morgan, A
Hinds, N
Hamann, H.F
Dokoozlian, N
Bosompem, M
Kwarteng, J.A
Acquah, H.D
Destain, M
Leemans, V
Marlier, G
Goffart, J
Bodson, B
Mercatoris, B
Gritten, F
Baklouti, I
Mansouri, M
Destain, M
Hamida, A
Nguyen, T
Slaughter, D
Townsley, B
Carriedo, L
Maloof, J
Sinha, N
Whattoff, D
Mouazen, D
Waine, D
Trotter, M
Gregory, S
Trotter, T
Acuna, T
Swain, D
Fasso, W
Roberts, J
Zikan, A
Cosby, A.M
Trotter, M
Andersson, K
Welch, M
Chau, M
Frizzel, L
Schneider, D
Shirzadi, A
Maharlooei, M
hassanijalilian, O
Bajwa, S
Howatt, K
Sivarajan, S
Nowatzki, J
Nowatzki, J
Bajwa, S
Roberts, D
Ossowski, M
Scheve, A
Johnson, A
Chaplin, Y
Adamchuk, V.I
Dhawale, N
Biswas, A
Lauzon‎, S
Dutilleul, P
Khot, L
Zhou, J
Boydston, R
Miklas, P.N
Porter, L
Ferreyra, R
Applegate, D.B
Berger, A.W
Berne, D.T
Craker, B.E
Daggett, D.G
Gowler, A
Bullock, R.J
Haringx, S.C
Hillyer, C
Howatt, T
Nef, B.K
Rhea, S.T
Russo, J.M
Nieman, S.T
Sanders, P
Wilson, J.A
Wilson, J.W
Tevis, J.W
Stelford, M.W
Shearouse, T.W
Schultz, E.D
Reddy, L
Erickson, B
Clay, D.E
Clay, S.A
Fausti, S
Maharlooei, M
Bajwa, S
Mireei, S.A
Shirzadi, A
Sivarajan, S
Berti, M
Nowatzki, J
Eigenberg, R.A
Woodbury, B.L
Nienaber, J.A
Pecker, K
Botsali, F.M
Topal, A
Zengin, M
Binch, A
Cooke, N
Fox, C.W
Bosompem, M
Dallago, G.M
Guimarães, M
Godinho, R
Carvalho, R
Lobo Júnior, A
Dallago, G.M
Guimarães, M
Godinho, R
Carvalho, R
Lobo Júnior, A
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
Berger, A.G
Hoffman, E
Fassana, N
Alfonso, F
Trindall, J
Rainbow, R
Nyéki , A
Milics, G
Kovács, A.J
Neményi, M
Kulmány, I
Zsebő, S
Wilson, G.L
Mulla, D.J
Galzki, J
Laacouri, A
Vetsch, J
Ransom, C.J
Kitchen, N.R
Camberato, J.J
Carter, P.R
Ferguson, R.B
Fernandez, F.G
Franzen, D.W
Laboski, C.A
Nafziger, E.D
Shanahan, J
Sawyer, J.E
Filippi, P
Jones, E.J
Fajardo, M
Whelan, B.M
Bishop, T.F
Wang, X
Miao, Y
Batchelor, W.D
Dong, R
Mulla, D.J
Wang, X
Miao, Y
Xia, T
Dong, R
Mi, G
Mulla, D.J
Issaka, F
Yongtao, L
Jiuhao, L
Buri, M.M
Asenso, E
Sheka Kanu, A
Zhao, Z
Osann, A
Campos, I
Calera, M
Plaza, C
Bodas, V
Calera, A
Villodre, J
Campoy, J
Sanchez, S
Jimenez, N
Lopez, H
Thies, S
Clay, D.E
Bruggeman, S
Joshi, D
Clay, S
Miller, J
Souza, E.G
Bazzi, C
Hachisuca, A
Sobjak, R
Gavioli, A
Betzek, N
Schenatto, K
Mercante, E
Rodrigues, M
Moreira, W
Rydahl, P
Boejer, O
Jensen, N
Hartmann, B
Jorgensen, R
Soerensen, M
Andersen, P
Paz, L
Nielsen, M.B
Aikes Junior, J
Souza, E.G
Bazzi, C
Sobjak, R
Hachisuca, A
Gavioli, A
Betzek, N
Schenatto, K
Moreira, W
Mercante, E
Rodrigues, M
Yilma, W.A
Siegfried, J
Khosla, R
Yang, C
Suh, C
Guo, W
Zhao, H
Zhang, J
Eyster, R
Bareth, G
Jenal, A
Hüging, H
Gu, H
Guo, W
Karn, R
Gu, H
Adedeji, O
Guo, W
Adedeji, O.I
Ghimire, B.P
Gu, H
Karn, R
Lin, Z
Guo, W
Cabrera Dengra, M
Ferraz Pueyo, C
Pajuelo Madrigal, V
Moreno Heras, L
Inunciaga Leston, G
Fortes, 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
Dong, R
Miao, Y
Wang, X
Topics
Profitability, Sustainability and Adoption
Modeling and Geo-statistics
Remote Sensing Applications in Precision Agriculture
Sensor Application in Managing In-season Crop Variability
Machine Vision / Multispectral & Hyperspectral Imaging Applications to Precision Agriculture
Modeling and Geo-statistics
Profitability, Sustainability, and Adoption
Engineering Technologies and Advances
Global Proliferation of Precision Agriculture and its Applications
Spatial Variability in Crop, Soil and Natural Resources
Remote Sensing Applications in Precision Agriculture
Spatial Variability in Crop, Soil and Natural Resources
Precision Nutrient Management
Proximal Sensing in Precision Agriculture
Precision Conservation Management
Applications of UAVs (unmanned aircraft vehicle systems) in precision agriculture
Sensor Application in Managing In-season CropVariability
Emerging Issues in Precision Agriculture (Energy, Biofuels, Climate Change, Standards)
Precision Horticulture
Profitability, Sustainability and Adoption
Proximal Sensing in Precision Agriculture
Spatial Variability in Crop, Soil and Natural Resources
Engineering Technologies and Advances
Agricultural Education
Remote Sensing Applications in Precision Agriculture
Unmanned Aerial Systems
Big Data Mining & Statistical Issues in Precision Agriculture
Standards & Data Stewardship
Adoption of Precision Agriculture
Applications of Unmanned Aerial Systems
Small Holders and Precision Agriculture
Farm Animals Health and Welfare Monitoring
In-Season Nitrogen Management
Big Data, Data Mining and Deep Learning
On Farm Experimentation with Site-Specific Technologies
Decision Support Systems
Land Improvement and Conservation Practices
Precision Agriculture and Global Food Security
Decision Support Systems
Precision Crop Protection
Applications of Unmanned Aerial Systems
Profitability and Success Stories in Precision Agriculture
ISPA Community: Nitrogen
In-Season Nitrogen Management
Type
Poster
Oral
Year
2012
2010
2014
2016
2008
2018
2022
Home » Authors » Results

Authors

Filter results67 paper(s) found.

1. Saltmed Model As An Integrated Management Tool For Precision Management Of Water, Crop, Soil, And Fertilizers

                 SALTMED-2009: A modelling tool for Precision Agriculture                                                    R. Ragab Centre for Ecology and Hydrology,... R. Ragab

2. Economic Profitability Of Site-specific Pesticide Management At The Farm Scale For Crop Systems In Haute-Normandie (France)

 Modern agriculture requires decision making criteria applicable to different scales of territory in order to reconcile productivity and respect of the environment, particularly for pest management. Taking into account the recent environmental... O. Bourgain, C. Duval, J. Llorens

3. New Power-leds Based Illumination System For Fertilizer Granule Motion Estimation

Environmental problems have become more and more pressing in the past twenty years particularly with the fertilization operation, one main contributor to environmental imbalance. The understanding of the global centrifugal spreading process, most commonly used in Europe, can contribute to provide essential information about fertiliser granule deposition on the soil. This last one can be predicted using a ballistic flight model and several fertilizer characteristic’s determination... F. Cointault, B. Hijazi, J. Dubois, J. Vangeyte, M. Paindavoine

4. Is Precision Agriculture Feasible In Cocoa Production In Ghana? : The Case Of “Cocoa High Technology Programme” In The Eastern Region Of Ghana

  Ghana is the second largest producer of cocoa in the world supplying 25% of the world’s cocoa, thus cocoa production contributes significantly to the economy of ... M. Bosompem, J.A. Kwarteng, E. Ntifo-siaw

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. Impact Of Winter Grazing On Forage Biomass Topography Soil Strength Spatial Relationships

Spatial relationships between soil properties, forage productivity, and landscape can be used to manage site-specific grazing. Soil penetration resistance and forage biomass were collected for three years in winter grazing experiment. The three ha experimental area was divided into six paddocks, hay was cut twice per year in the months of May and June, and forage stockpiled after the second cutting. Animals were admitted to paddocks at the end of November, at a stocking rate... E.M. Pena-yewtukhiw, D. Mata-padrino, W. Bryan

7. Using Crop Budgeting Spreadsheets Can Assist Producers In Evaluating The Cost Effectiveness Of Adoption Of The Various Precision Agriculture Technologies

Producers asked the question which Precision Agriculture Technologies can be economical in my farming operation?  The use of easily modified crop budgets can help the producer evaluate the technologies and how they affect the profitability of one’s agricultural enterprise.... R.N. Klein, R. Wilson

8. On-Farm Trials Using Precision Ag in Northeast Louisiana

The availability of yield monitors and precision application equipment on producers’ farms have made it much easier for researchers to take the results from experiment station trials and apply them to producers’ fields.  Treatments/methods are applied in strips, by prescription, embedded plots or in combination.  Fields are divided into zones for analyzing the harvest yield data.  These can include soil type, soil Ec, or other criteria.  Treatments are analyzed... D. Burns, D. Overstreet, D. Kruse, R. Frazier, D. Blanche

9. Assessing the Potential of an Algorithm Based On Mean Climatic Data to Predict Wheat Yield

In crop yield prediction, the unobserved future weather remains the key point of predictions. Since weather forecasts are limited in time, a large amount of information may come from the analysis of past weather data. Mean data over the past years and stochastically generated data are two possible ways to compensate the lack of future data. This research aims to demonstrate that it is possible to predict... F. Vancutsem, V. Leemans, S. Ferrandis vallterra, B. Bodson, J. Destain, M. Destain, B. Dumont

10. Estimation of Rice Yield from MODIS Data in West Java, Indonesia

Chiharu Hongo1*, Takaaki Furukawa1, Gunardi Sigit2, Masayasu Maki3, Koki Honma3,... C. Hongo, T. Furukawa, G. Sigit, M. Maki, K. Honma, K. Yoshida, K. Oki, H. Shirakawa

11. A Comparison of Plant Temperatures as Measured By Thermal Imaging and Infrared Thermometry

... P. Baresel, B. Mistele, H. Yuncai, U. Schmidhalter, H. Hackl

12. A 3-D Stereovision Simulator for Centrifugal Fertilizer Granule Spreading

... J. Vangeyte, F. Cointault, M. Paindavoine, J. Pieters, B. Hijazi

13. Detection Of Fruit Tree Water Status In Orchards From Remote Sensing Thermal Imagery

In deciduous fruit trees there is a growing need of using water status indicators for scheduling irrigation and adopt regulated deficit irrigation (RDI) strategies taking into account spatial variability of orchards. RDI strategies have been successfully adopted for many fruit trees as a means for reducing water use and because yield and quality at harvest are not sensitive to water stress at some developmental stages. Although water status is generally monitored by measuring tree... P.J. Zarco-tejada, V. Gonzalez-dugo, J. Girona, E. Fereres, J. Bellvert

14. First Results Of Development Of A Smart Farm In The Netherlands

GNSS technology has been introduced on about 20 % of the Dutch arable farms in The Netherlands today. Use of sensor technology is also slowly but gradually being adopted by farmers, providing them large amounts of digital data on soil, crop and climate conditions. Typical data are spatial variation in soil organic matter, crop biomass, crop yield, and presence of pests and diseases. We still have to make major steps to use all this data in a way that agriculture becomes more sustainable. We... T. Feher, C. Kocks, C. Kempenaar, K. Westerdijk

15. Nitrogen Fertilisation Recommendations : Could They Be Improved Using Stochastically Generated Climates In Conjunction With Crop Models ?

In the context of precision nitrogen (N) management, to ensure that the yield potential could be reached each year, farmers have too often applied quantities of fertilizers much larger than what was strictly required. However, since 2002, the Belgian Government transposed the European Nitrate Directive 91/676/EEC in the Belgian law, with the aim to maintain the productivity and the revenue of Belgian's farmers while reducing the environmental impact of excessive N management... B. Basso, J. Destain, B. Bodson, M. Destain, B. Dumont

16. Development Of An On-The-Spot Analyzer For Measuring Soil Chemical Properties

Proximal soil sensing (PSS) is a growing area of research and development focusing on the use of sensors to obtain information on the physical, chemical and biological attributes of soil when they are placed in contact with, or at a distance of less than 2 m, from the target. These sensor systems have been used to 1) make measurements at specific locations, 2) produce a set of measurements related to soil depth profiles, or 3) monitor changes in soil properties over time. In each... V.I. Adamchuk, N. Dhawale, F. Rene-laforest

17. Soil Compaction: Impact Of Tractor And Equipment On Corn Growth, Development And Yield

This project looks at the impact of soil compaction on corn emergence, growth and development, and yield. This is a two-year study, begun in the in the spring of 2013, it will be completed after the 2014 growing season. Corn was produced in the field both years.   The project hypotheses are to: 1) Soil compaction does impact corn growth, development and yield; 2) Soil compacted in the fall season by farm equipment is measurable the following... S. Sivarajan, S. Bajwa, J. Nowatzki

18. Verify The Effectiveness Of UAS-Mounted Sensors In Field Crop And Livestock Production Management Issues

This research project is a “proof-of-concept” demonstrating specific UAS applications in production agriculture. Project personnel will use UAS-mounted sensors to collect data of ongoing crop and livestock research projects during the 2014 crop season at the North Dakota State University (NDSU) Carrington Research Extension Center (CREC). Project personnel will collaborate with NDSU research scientists conducting research at the CREC. During the first year of the project... S. Bajwa, J. Nowatzki, W. Harnisch, B. Schatz, V. Anderson

19. Using Precision Agriculture And Remote Sensing Techniques To Improve Genotype Selection In A Breeding Program

Precision Agriculture (PA) and Remote Sensing (RS) technologies are increasingly being used as tools to assess crop and soil properties by breeders and physiologists.  These technologies are showing potential to improve genotype selections over their traditional field measurements, by providing quick access to crop properties throughout the crop cycle and yield estimation. The objective of this work was to use vegetation indices (VIs) and soil apparent electrical conductivity... F.A. Rodrigues junior, I. Ortiz-monasterio, P.J. Zarco-tejada, K. Ammar, B.G. Gérard

20. Climate Change And Sustainable Precision Crop Production With Regard To Maize (Zea Mays L.)

Precision crop production research activities were started during the mid-‘90s at the Institute of Biosystems Engineering, Faculty of Agricultural and Food Sciences, University of West Hungary. On the basis of the experiences with DSSAT (Decision Support System for Agrotechnology Transfer) the impact of climate change on maize yield (three soil types) was investigated until 2100. DSSAT crop growth model is used worldwide. The coupled model intercomparison project... A.J. Kovács, A. Nyéki, G. Milics, M. Neményi

21. Management Zones Delineation In Brazilian Citrus Orchards

Precision Agriculture (PA) is in its first steps in Brazil citrus production. Variable rate fertilization based on soil grid sampling and yield maps has been tested in São Paulo orchards. In a long term study results showed potential on increasing fertilizer use efficiency and improving soil fertility management. Despite the good results, in some cases it is noticed that systematic methods of investigation (grid sampling and yield data) and prescription (standardized prescription equations)... M. Ruiz, D. Yida, J.P. Molin, A.F. Colaço

22. Evaluation Of In-Field Sensors To Monitor Nitrogen Status In Soybean

In recent years, active optical crop sensors have been gaining importance to determine in-season nitrogen (N) fertilization requirements for on-the-go variable rate application.  Although most of these active in-field crop sensors have been evaluated in corn and wheat crops, they have not yet been evaluated in soybean production systems in North Dakota. Recent research from both South Dakota and North Dakota indicate that in-season N application in soybean can increase soybean yield... J. Nowatzki, S. Bajwa, S. Sivarajan, M. Maharlooei, H. Kandel

23. Effect Of A Variable Rate Irrigation Strategy On The Variability Of Crop Production In Wine Grapes In California

Pruning and irrigation are the cultural practices with the highest potential impact on yield and quality in wine grapes. In particular, irrigation start date, rates and frequency can be synchronized with crop development stages to control canopy growth and, in turn, positively influence light microclimate, berry size and fruit quality. In addition, canopy management practices can be implemented in vineyards with large canopies to ensure fruit zone microclimate... L.A. Sanchez, L.J. Klein, A. Claassen, D. Lew, M. Mendez-costabel, B. Sams, A. Morgan, N. Hinds, H.F. Hamann, N. Dokoozlian

24. Determinants of Ex-ante Adoption of Precision Agriculture Technologies by Cocoa Farmers in Ghana

The study was to identify the best predictors of cocoa Farmers willingness to adopt future Precision Agriculture Technology (PAT) Development in Ghana. Correlational research design was used. The target population was all cocoa farmers who benefited from Cocoa High Technology Programme (an initiative of distributing free fertilizer by government to cocoa farmers) in Ghana. Multistage sampling technique was used to select 422 out of 400,000 cocoa farmers in the six (6) out of the seven (7) cocoa... M. Bosompem, J.A. Kwarteng, H.D. Acquah

25. Detection of Nitrogen Stress on Winter Wheat by Multispectral Machine Vision

Hand-held sensors (SPAD meter, N-Tester, …) used for detecting the leaves nitrogen  concentration (Nc) present several drawbacks. The nitrogen concentration is gained by an indirect way through the chlorophyll concentration and the leaves have to be fixed in a defined position for the measurements. These drawbacks could be overcome by an imaging device that measures the canopy reflectance. Hence, the objective of the paper is to analyse the potential of multispectral imaging for detecting... M. Destain, V. Leemans, G. Marlier, J. Goffart, B. Bodson, B. Mercatoris, F. Gritten

26. Estimating Environmental Systems Using Iterated Sigma Point Techniques: a Biomass Substrate Hypothetical System

This paper addresses the problem of biomass substrate hypothetical system estimation using sigma points kalman filter (SPKF) methods. Various conventional and state-of-theart state estimation methods are compared for the estimation performance, namely the unscented Kalman filter(UKF), the central difference Kalman filter (CDKF), the square-root unscented Kalman filter (SRUKF), the square-root central difference Kalman filter (SRCDKF), the iterated unscented Kalman filter (IUKF), the iterated central... I. Baklouti, M. Mansouri, M. Destain, A. Hamida

27. In-field Plant Phenotyping Using Multi-view Reconstruction: an Investigation in Eggplant

Rapid methods for plant phenotyping are a growing need in agricultural research to help accelerate improvements in crop performance in order to facilitate more efficient utilization of plant genome sequences and the corresponding advancements in associated methods of genetic improvement. Manual plant phenotyping is time-consuming, laborious, frequently subjective, and often destructive. There is a need for building field-deployable systems with advanced sensors that have both high-speed and high-performance... T. Nguyen, D. Slaughter, B. Townsley, L. Carriedo, J. Maloof, N. Sinha

28. A Multi Sensor Data Fusion Approach for Creating Variable Depth Tillage Zones.

Efficiency of tillage depends largely on the nature of the field, soil type, spatial distribution of soil properties and the correct setting of the tillage implement.  However, current tillage practice is often implemented without full understanding of machine design and capability leading to lowered efficiency and further potential damage to the soil structure. By modifying the physical properties of soil only where the tillage is needed for optimum crop growth, variable depth tillage (VDT)... D. Whattoff, D. Mouazen, D. Waine

29. SMARTfarm Learning Hub: Next Generation Precision Agriculture Technologies for Agricultural Education

The industry demands on higher education agricultural students are rapidly changing. New precision agriculture technologies are revolutionizing the farming industry but the education sector is failing to keep pace. This paper reports on the development of a key resource, the SMARTfarm Learning Hub (www.smartfarmhub.com) that will increase the skill base of higher education students using a range of new agricultural technologies and innovations. The Hub is a world first; it links real industry... M. Trotter, S. Gregory, T. Trotter, T. Acuna, D. Swain, W. Fasso, J. Roberts, A. Zikan, A. Cosby

30. Evaluating low-cost Lidar and Active Optical Sensors for pasture and forage biomass assessment

Accurate and reliable assessment of pasture or forage biomass remains one of the key challenges for grazing industries. Livestock managers require accurate estimates of the grassland biomass available over their farm to enable optimal stocking rate decisions. This paper reports on our investigations into the potential application of affordable Lidar (Light Detection and Ranging) systems and Active Optical (reflectance) Sensors (AOS) to estimate pasture biomass. We evaluated the calibration accuracy... M. Trotter, K. Andersson, M. Welch, M. Chau, L. Frizzel, D. Schneider

31. Greenhouse Study to Identify Glyphosate-resistant Weeds Based on Canopy Temperature

Development of herbicide-resistant crops has resulted in significant positive changes to agronomic practices, while repeated and intensive use of herbicides with the same mechanisms of action has caused the development of herbicide-resistant weeds. As of 2015, 35 weed species are reported to be resistant to glyphosate worldwide. A greenhouse study was conducted to identify characteristics which can be helpful in field mapping of glyphosate resistant weeds by using UAV imagery. The experiment included... A. Shirzadi, M. Maharlooei, O. Hassanijalilian, S. Bajwa, K. Howatt, S. Sivarajan, J. Nowatzki

32. Large-scale UAS Data Collection, Processing and Management for Field Crop Management

North Dakota State University research and Extension personnel are collaborating with Elbit Systems of America to compare the usefulness and economics of imagery collected from a large unmanned aircraft systems (UAS), small UAS and satellite imagery. Project personnel are using a large UAS powered with an internal combustion engine to collect high-resolution imagery over 100,000 acres twice each month during the crop growing season. Four-band multispectral Imagery is also being collected twice... J. Nowatzki, S. Bajwa, D. Roberts, M. Ossowski, A. Scheve, A. Johnson, Y. Chaplin

33. Integrated Analysis of Multilayer Proximal Soil Sensing Data

Data revealing spatial soil heterogeneity can be obtained in an economically feasible manner using on-the-go proximal soil sensing (PSS) platforms. Gathered georeferenced measurements demonstrate changes related to physical and chemical soil attributes across an agricultural field. However, since many PSS measurements are affected by multiple soil properties to different degrees, it is important to assess soil heterogeneity using a multilayer approach. Thus, analysis of multiple layers of geospatial... V.I. Adamchuk, N. Dhawale, A. Biswas, S. Lauzon‎, P. Dutilleul

34. Small UAS Integrated Sensing Tools for Abiotic Stress Monitoring in Irrigated Pinto Beans

Precision agriculture is a practical approach to maximize crop yield with optimal use of rapidly depleting natural resources. Availability of specific and high resolution crop data at critical growth stages is a key for real-time data driven decision support for precision agriculture management during the production season. The goal of this study was to evaluate the feasibility of using small unmanned aerial system (UAS) integrated remote sensing tools to monitor the abiotic stress of eight irrigated... L. Khot, J. Zhou, R. Boydston, P.N. Miklas, L. Porter

35. Toward Geopolitical-Context-Enabled Interoperability in Precision Agriculture: AgGateway's SPADE, PAIL, WAVE, CART and ADAPT

AgGateway is a nonprofit consortium of 240+ businesses working to promote, enable and expand eAgriculture. It provides a non-competitive collaborative environment, transparent funding and governance models, and anti-trust and intellectual property policies that guide and protect members’ contributions and implementations. AgGateway primarily focuses on implementing existing standards and collaborating with other organizations to extend them when necessary. In 2010 AgGateway identified... R. Ferreyra, D.B. Applegate, A.W. Berger, D.T. Berne, B.E. Craker, D.G. Daggett, A. Gowler, R.J. Bullock, S.C. Haringx, C. Hillyer, T. Howatt, B.K. Nef, S.T. Rhea, J.M. Russo, S.T. Nieman, P. Sanders, J.A. Wilson, J.W. Wilson, J.W. Tevis, M.W. Stelford, T.W. Shearouse, E.D. Schultz, L. Reddy

36. Knowledge, Skills and Abilities Needed in the Precision Ag Workforce: an Industry Survey

Precision agriculture encompasses a set of related technologies aimed at better utilization of crop inputs, increasing yield and quality, reducing risks, and enabling information flow throughout the crop supply and end-use chains.  The most widely adopted precision practices have been automated systems related to equipment steering and precise input application, such as autoguidance and section controllers.  Once installed, these systems are relatively easy for farmers and their supporting... B. Erickson, D.E. Clay, S.A. Clay, S. Fausti

37. Vis/NIR Spectroscopy to Estimate Crude Protein (CP) in Alfalfa Crop: Feasibility Study

The fast and reliable quality determination of alfalfa crop is of interest for producers to make management decisions, the dealers to determine the price, and the dairy producers for livestock management. In this study, the crude protein (CP), one of the main quality indices of alfalfa, was estimated using the visible and near-infrared (Vis/NIR) spectroscopy. A total of 68 samples from various variety trials of alfalfa crop were collected under the irrigated and rainfed conditions. The diffuse... M. Maharlooei, S. Bajwa, S.A. Mireei, A. Shirzadi, S. Sivarajan, M. Berti, J. Nowatzki

38. Precision Management of Cattle Feedlot Waste

Open-lot cattle feeding operations face challenges in control of nutrient runoff, leaching, and gaseous emissions. This report investigates the use of precision management of saline soils as found on 1) feedlot surfaces and on a 2) vegetative treatment area (VTA) utilized to control feedlot runoff. An electromagnetic induction soil conductivity meter was used to collect apparent soil electrical conductivity (ECa) from a feedlot pen and a research VTA at the U.S. Meat Animal Research Center, Clay...

39. The Review of Studying and Using Advanced Technologies for Site Specific Management in Konya, Turkey

Using advanced (information) technologies in agriculture is increasing rapidly especially in the developed countries such as USA, Japan, and some members of EU. Advanced technologies in agriculture are mostly based on sensors. Site specific management is a form of agricultural management, which is governed by optimum use of variables. Input such as chemical, water, and seed in agricultural production can be managed by using the technologies. Geographic information systems (GIS), Global Position... K. Pecker, F.M. Botsali, A. Topal, M. Zengin

40. Rumex and Urtica Detection in Grassland by UAV

Previous work (Binch & Fox, 2017) used autonomous ground robotic platforms to successfully detect Urtica (nettle) and Rumex (dock) weeds in grassland, to improve farm productivity and the environment through precision herbicide spraying. It assumed that ground robots swathe entire fields to both detect and spray weeds, but this is a slow process as the slow ground platform must drive over every square meter of the field even where there are no weeds. The present study examines a complimentary... A. Binch, N. Cooke, C.W. Fox

41. Prospects and Challeges to Precision Agriculture Technologies Development in Ghana: Scientists' and Extension Agents' Perspectives.

The main objective of the research was to examine the prospects and challenges of developing and implementing precision agriculture (PA) in cocoa production in Ghana. A census of cocoa research scientists and a survey of cocoa extension agents (CEAs) in Ghana were taken. Five major challenges they perceived to pose serious challenges to the development and implementation of future Precision Agriculture Technologies (PATs), in their decreasing order of importance, were (a) farmer-demographic... M. Bosompem

42. The Animal Welfare of Dairy Cows Housed in Free-Stall Barn According to the Welfare Quality® Protocol: Good Feeding and Good Housing Principles

The objective of the present study was to evaluate the animal welfare of dairy cows according to good feeding and good housing principles of the Welfare Quality® protocol. The protocol was applied to animals kept confined in a free-stall barn during their lactation. The farm was located in São João Batista do Glória, Minas Gerais state - Brazil. One hundred and one animals were evaluated (47 primiparous and 54 multiparous). The welfare measures were collected mostly through... G.M. Dallago, M. Guimarães, R. Godinho, R. Carvalho, A. Lobo júnior

43. The Correlation Between Criteria from Welfare Quality® Protocol Applied to Dairy Cows Housed in Free-Stall Barn

The objective of this study was to evaluate correlations between animal welfare criteria from the Welfare Quality® protocol applied to dairy cows. The protocol was applied on 47 primiparous and 54 multiparous dairy cows housed in a free-stall barn located in São João Batista do Glória, Minas Gerais - Brazil. Twelve welfare criteria were obtained from mostly animal-based welfare measures as proposed by the protocol. Pearson correlation coefficients (r) were calculated between... G.M. Dallago, M. Guimarães, R. Godinho, R. Carvalho, A. Lobo júnior

44. 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

45. Active Canopy Sensors for the Detection of Non-Responsive Areas to Nitrogen Application in Wheat

Active canopy sensors offer accurate measurements of crop growth status that have been used in real time to estimate nitrogen (N) requirements. NDVI can be used to determine the absolute amount of fertilizer requirement, or simply to distribute within the field an average rate defined by decision models using other diagnostics. The objective of this work was to evaluate the capacity of active canopy sensors to determine yield and N application requirements within a site at jointing stage (Feeks... A.G. Berger, E. Hoffman, N. Fassana, F. Alfonso

46. Accelerating Precision Agriculture to Decision Agriculture: Enabling Digital Agriculture in Australia

For more than two decades, the success of Australia’s agricultural and rural sectors has been supported by the work of the Rural Research and Development Corporations (RDCs). The RDCs are funded by industry and government. For the first time, all fifteen of Australia’s RDC’s have joined forces with the Australian government to design a solution for the use of big data in Australian agriculture. This is the first known example of a nationwide approach for the digital transformation... J. Trindall, R. Rainbow

47. Improving Yield Prediction Accuracy Using Energy Balance Trial, On-the-Go and Remote Sensing Procedure

 Our long term experience in the ~23.5 ha research field since 2001 shows that decision support requires complex databases from each management zone within that field (eg. soil physical and chemical parameters, technological, phenological and meteorological data). In the absence of PA sustainable biomass production cannot be achieved. The size of management zones will be ever smaller. Consequently, the on the go and remote sensing data collection should be preferred.  The... A. Nyéki , G. Milics, A.J. Kovács, M. Neményi, I. Kulmány, S. Zsebő

48. Predicted Nitrate-N Loads for Fall, Spring, and VRN Fertilizer Application in Southern Minnesota

Nitrate-N from agricultural fields is a source of pollution to fresh and marine waters via subsurface tile drainage.  Sensor-based technologies that allow for in-season monitoring of crop nitrogen requirements may represent a way to reduce nitrate-N loadings to surface waters by allowing for fertilizer application on a more precise spatial and temporal resolution.  However, little research has been done to determine its effectiveness in reducing nitrate-N losses.  In this study,... G.L. Wilson, D.J. Mulla, J. Galzki, A. Laacouri, J. Vetsch

49. Improving Corn Nitrogen Rate Recommendations Through Tool Fusion

 Improving corn (Zea maysL,) nitrogen (N) fertilizer rate recommendation tools can improve farmer’s profits and help mitigate N pollution. One way to improve N recommendation methods is to not rely on a single tool, but to employ two or more tools. Thiscould be thoughtof as “tool fusion”.The objective of this analysis was to improve N management by combining N recommendation tools used for guiding rates for an in-seasonN application. This evaluation was... C.J. Ransom, N.R. Kitchen, J.J. Camberato, P.R. Carter, R.B. Ferguson, F.G. Fernandez, D.W. Franzen, C.A. Laboski, E.D. Nafziger, J. Shanahan, J.E. Sawyer

50. Forecasting Crop Yield Using Multi-Layered, Whole-Farm Data Sets and Machine Learning

The ultimate goal of Precision Agriculture is to improve decision making in the business of farming. Many broadacre farmers now have a number of years of crop yield data for their fields which are often augmented with additional spatial data, such as apparent soil electrical conductivity (ECa), soil gamma radiometrics, terrain attributes and soil sample information. In addition there are now freely available public datasets, such as rainfall, digital soil maps and archives of satellite remote... P. Filippi, E.J. Jones, M. Fajardo, B.M. Whelan, T.F. Bishop

51. Improving the Precision of Maize Nitrogen Management Using Crop Growth Model in Northeast China

The objective of this project was to evaluate the ability of the CERES-Maize crop growth model to simulate grain yield response to plant density and N rate for two soil types in Northeast China, with the long-term goal of using the model to identify the optimum plant density and N fertilizer rate forspecific site-years. Nitrogen experiments with six N rates, three plant densities and two soil types were conducted from 2015 to 2017 in Lishu county, Jilin Province in Northeast China. The CERES-Maize... X. Wang, Y. Miao, W.D. Batchelor, R. Dong, D.J. Mulla

52. Improving Active Canopy Sensor-Based In-Season N Recommendation Using Plant Height Information for Rain-Fed Maize in Northeast China

The inefficient utilization of nitrogen (N) fertilizer due to leaching, volatilization and denitrification has resulted in environmental pollution in rain-fed maize production in Northeast China. Active canopy sensor-based in-season N application has been proven effective to meet maize N requirement in space and time. The objective of this research was to evaluate the feasibility of using active canopy sensor for guiding in in-season N fertilizer recommendation for rain-fed maize in Northeast... X. Wang, Y. Miao, T. Xia, R. Dong, G. Mi, D.J. Mulla

53. Characterization of Soil Properties, Nutrient Distribution and Rice (Oryza Sativa.) Productivity As Influenced by Tillage Methods in a Typical Gleysols

Global emphasis and interest in conservation Tillage in agricultural soils has tremendously increased in the last few years, especially no tillage with its potential to improve soil physicochemical properties, reduce nutrient leaching as well as improve crop productivity in a more sustainable manner.  Several questions still exist with regard to the true role of no tillage in improving soil fertility. A two year field study was conducted to characterize the effects of different tillage methods... F. Issaka, L. Yongtao, L. Jiuhao, M.M. Buri, E. Asenso, A. Sheka kanu, Z. Zhao

54. Practical Prescription of Variable Rate Fertilization Maps Using Remote Sensing Based Yield Potential

This paper describes a practical approach for the prescription of variable rate fertilization maps using remote sensing data (RS) based on satellite platforms, Landsat 8 and Sentinel-2 constellation. The methodology has been developed and evaluated in Albacete, Spain, in the framework of the project FATIMA (http://fatima-h2020.eu/). The global approach considers the prescription of N management prior to the growing season, based on a spatially distributed N balance. Although the diagnosis of N... A. Osann, I. Campos, M. Calera, C. Plaza, V. Bodas, A. Calera, J. Villodre, J. Campoy, S. Sanchez, N. Jimenez, H. Lopez

55. Precision Fall Urea Fertilizer Applications: Timing Impact on Carbon Dioxide, Ammonia Volatilization and Nitrous Oxide Emissions

To minimize ammonia (NH3) volatilization and nitrous oxide (N2O) emissions from fall applied fertilizer, it is generally recommended to not apply the fertilizer until the soil temperature decreases below 10 C. However, this recommendation is not based on detailed measurements of NH3and N2O emissions. The objective of this study was to determine the influence of fertilizer application timing on nitrous oxide, carbon dioxide, and ammonia volatilization emissions.  Nitrogen fertilizer was... S. Thies, D.E. Clay, S. Bruggeman, D. Joshi, S. Clay, J. Miller

56. 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

57. Economic Potential of RoboWeedMaps - Use of Deep Learning for Production of Weed Maps and Herbicide Application Maps

In Denmark, a new IPM ‘product chain’ has been constructed, which starts with systematic photographing of fields and ends up with field- or site-specific herbicide application. A special high-speed camera, mounted on an ATV took sufficiently good pictures of small weed plants, while driving up to 50 km/h. Pictures were uploaded to the RoboWeedMaps online platform, where appointed internal- and external persons with agro-botanical experience executed ‘virtual field inspection’... P. Rydahl, O. Boejer, N. Jensen, B. Hartmann, R. Jorgensen, M. Soerensen, P. Andersen, L. Paz, M.B. Nielsen

58. 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

59. Delineation of Site-specific Management Zones with Proximal Data and Multi-spectral Imagery

Many findings suggested that it’s possible to improve the accuracy of delineating site-specific management zones (SSMZs) through a combination of proximal data with remote sensing imagery. The objective of this study is to assess the feasibility of delineating SSMZs with a wide range of ancillary data (proximal survey and multi-spectral data). The study area is a 22.1acre located 10 miles north of Fort Collins, CO and is known for having a high spatial and temporal variability of soil properties.... W.A. Yilma, J. Siegfried, R. Khosla

60. Evaluation of Image Acquisition Parameters and Data Extraction Methods on Plant Height Estimation with UAS Imagery

Aerial imagery from unmanned aircraft systems (UASs) has been increasingly used for field phenotyping and precision agriculture. Plant height is one important crop growth parameter that has been estimated from 3D point clouds and digital surface models (DSMs) derived from UAS-based aerial imagery. However, many factors can affect the accuracy of aerial plant height estimation. This study examined the effects of image overlap, pixel resolution, and data extraction methods on estimation... C. Yang, C. Suh, W. Guo, H. Zhao, J. Zhang, R. Eyster

61. N-management Using Structural Data: UAV-derived Crop Height As an Estimator for Biomass, N Concentration, and N Uptake in Winter Wheat

In the last 15 years, sensors mounted on Unmanned Aerial Vehicles (UAVs) have been intensively investigated for crop monitoring. Besides known remote sensing approaches based on multispectral and hyperspectral sensors, photogrammetric methods became very important. Structure for Motion (SfM) and Multiview Stereopsis (MVS) analysis approaches enable the quantitative determination of absolute crop height and crop growth. Since the first paper on UAV-derived crop height was published by Bendig et... G. Bareth, A. Jenal, H. Hüging

62. Integration of Unmanned Aerial Systems Images and Yield Monitor in Improving Cotton Yield Estimation

The yield monitor is one of the most adopted precision agriculture technologies because it generates dense yield data to quantify the spatial variability of crop yield as a basis for site-specific management. However, yield monitor data has various errors that prevent proper interpretation and precise field management. The objective of this study was to evaluate the application of unmanned aerial systems (UAS) images in improving cotton yield monitor data. The study was conducted in a dryland... H. Gu, W. Guo

63. Evaluation of Unmanned Aerial Vehicle Images in Estimating Cotton Nitrogen Content

Estimating crop nitrogen content is a critical step for optimizing nitrogen fertilizer application. The objective of this study was to evaluate the application of UAV images in estimating cotton (Gossypium hirsutum L.) N content. This study was conducted in a dryland cotton field in Garza County, Texas, in 2020. The experiment was implemented as a randomized complete block design with three N rates of 0, 34, and 67 kg N ha-1. A RedEdge multispectral sensor was used to acquire... R. Karn, H. Gu, O. Adedeji, W. Guo

64. Estimation of Cotton Biomass Using Unmanned Aerial Systems and Satellite-based Remote Sensing

Satellite and unmanned aerial system (UAS) images are effective in monitoring crop growth at various spatial, temporal, and spectral scales. The objective of the study was to estimate cotton biomass at different growth stages using vegetation indices (VIs) derived from UAS and satellite images. This research was conducted in a cotton field in Hale County, Texas, in 2021. Data collected include 54 plant samples at different locations for three dates of the growing season. Multispectral images from... O.I. Adedeji, B.P. Ghimire, H. Gu, R. Karn, Z. Lin, W. Guo

65. Use of MLP Neural Networks for Sucrose Yield Prediction in Sugarbeet

INTRODUCTION Sugar beet is one of the more technified agro industries in Spain. In the last years, it has leaded as well the digital transformation with the objective of maintaining sugar beet competitivity both national and internationally. Among other lines, very high potential has been identified in determining the sucrose content using a combination of Artificial Intelligence and Remote Sensing. This work presents the conclusions of an extensive data acquisition task, creation of... M. Cabrera dengra, C. Ferraz pueyo, V. Pajuelo madrigal, L. Moreno heras, G. Inunciaga leston, R. Fortes

66. 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

67. In-season Nitrogen Management of Maize Based on Nitrogen Status and Lodging Risk Prediction

Development of effective precision nitrogen (N) management strategies is crucially important for food security and sustainable development. Lodging is one of the major constraints to increasing maize yield that can be induced by strong winds, and is also influenced by management practices, like N rate. When making in-season N application decisions, lodging risk should be considered to avoid yield loss. Little has been reported on in-season N management strategies that also incorporate lodging... R. Dong, Y. Miao, X. Wang