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Sensor Application in Managing In-season CropVariability
Wireless Sensor Networks
In-Season Nitrogen Management
Industry
Decision Support Systems in Precision Agriculture
Profitability and Success Stories in Precision Agriculture
Applications of UAVs (unmanned aircraft vehicle systems) in precision agriculture
Community and Regional Meeting
Education and Training in Precision Agriculture
No Group Selected
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Authors
Adamchuk, V.I
Akune, V.S
Albarenque, S.M
Amaral, L.R
Ammar, K
Anderson, V
Araujo, R
Arias, A.C
Ashley, R
Ault, A
Baharom, S.N
Bajwa, S
Bajwa, S
Balboa, G
Balboa, G
Balmos, A
Baumbauer, C
Bazzi, C.L
Bazzi, C.L
Been, T
Been, T
Belec, C
Beneduzzi, H.M
Benez, S.H
Betzek, N.M
Betzek, N.M
Bonfil, D.J
Booij, J.A
Bosse, D
Bouroubi, M.Y
Bruce, A.E
Brungardt, J.J
Bu, H
Buckmaster, D
Caicedo, J.H
Cambouris, A
Cammarano, D
Cao, Q
Caron, J
Carter, A
Celades, J.A
Cesario Pereira Pinto, J
Chae, Y
Chen, Z
Cheng, S
Choi, M
Chowdury, M
Chung, S
Ciampitti, I
Ciampitti, I.A
Citon, L.C
Coble, K
Coonen, J
Coulter, J.A
Cox, M
Crawford, K
Cummings, T
Custer, S
De Baerdemaeker, J
De Ketelaere, B
Deckers, T
Dhillon, R
Dhoubhadel, S
Dillon, C
Dong, R
Dorado, J
Dos Reis, A.A
Drummond, S.T
Duchemin, M
Duncan, S
Dzinaj, T
Ellingson, J.L
Endres, G
Erdle, K
Fallon, E
Ferguson, R.B
Ferguson, R.B
Ferraz, M.N
Figueiredo, G.K
Flint, E.A
Fountas, S
Franzen, D.W
Franzen, D.W
Freitas, R.G
Fulton, J.P
Gérard, B.G
Gadler, D.J
Gandorfer, M
Gandorfer, M
García, C.E
Gavioli, A
Gavioli, A
Gerth, S
Ghimire, D
Gitelson, A.A
Goodrich, P.J
Griffin, T.W
Griffin, T.W
Gumiere, S.J
Gunzenhauser, R
Gupta, S
Hagolle, O
Hallema, D.W
Hambly, H
Hamm, P.B
Haneklaus, S
Hanke, R
Harnisch, W
Hartschuh, J
Hatfield, J
Hatfield, J.L
Hawkins, E
Holub, B.K
Hopkins, B.G
Horneck, D.A
Huang, J
Huh, Y
Hunt, E
Jacquin, A
Jia, M
Johnson, D
Jung, K
Kana, I
Kandel, H
Karatay, Y
Kemerer, A.C
Kempenaar, C
Kempenaar, C
Kessel, G.J
Khakbazan, M
Khosla, R
Khot, L
Kim, S
Kinder, T
Kitchen, N.R
Kitchen, N.R
Kitchen, N.R
Klopfenstein, A
Klose, R
Kocks, C
Kodaira, M
Krogmeier, J
Kuehner, K
López-Granados, F
Lacerda, L.N
Lafond, J.A
Lamparelli, R.A
Lampinen, B
Lange, A
Layton, A
Lee, J
Lepoivre, B
Li, D
Li, X
Li, Y
Liakos, V
Lilienthal, H
Lima, J.P
Lindblom, J
Liu, F
Lopez-Granados, F
Lowrance, C
Lu, J
Lundström, C
Magalhães, P.S
Maharjan, B
Maharlooei, M
Mandel, R
Mangus, D
Marjerison, R
Massey, R
Massey, R.E
Maxwell, T
McArtor, B
McFadden, J
McGary, S.D
Melchiori, R.J
Metcalf, S
Meyer-Aurich, A
Miao, Y
Miao, Y
Miao, Y
Miao, Y
Miao, Y
Michiels, P
Mieno, T
Mizuta, K
Mizuta, K
Moebiu-Clune, B
Moebius-Clune, D
Mohammad, A.S
Molendijk, L.P
Molin, J.P
Molin, J.P
Mora, H
Morales, A.C
Morgan, S.E
Moulin, A
Mueller, N
Mulla, D.J
Musacchi, S
Nakazawa, P.H
Nayse, S.P
Nielsen, R.L
Noel, S
Nowatzki, J
Nowatzki, J
Nysten, S
Ortiz-Monasterio, I
Otto, R
Périard, Y
Pauly, K
Peña, J
Peña, J.M
Pereira, F.R
Pereira, F.R
Pereira, J.C
Poilvé, H
Portz, C
Portz, G
Posada, L.V
Prasad, V
Price, K
Puntel, L
Quaderer, J
Quinn, D.J
Ransom, C.J
Reisinger, S
Roach, J
Roberts, D
Rodrigues Junior, F.A
Rojo, F
Romanelli, T.L
Rosburg, A
Rosen, C
Roumiguié, A
Ruckelshausen, A
Saeys, W
Sanches, G.M
Sankaran, S
Santana Neto, A.J
Schatz, B
Schenatto, K
Schenatto, K
Schepers, A.R
Schepers, J.S
Schepters, J.S
Schindelbeck, R
Schleicher, S
Schneider, S
Schnug, E
Schulte-Ostermann, S
Sela, S
Serra, S
Shannon, D.K
Sharda, A
Sharda, A
Sharma, L
Shearer, S
Shen, J
Shibusawa, S
Shibusawa, S
Shockley, J.M
Shoups, D
Shroyer, K
Sigel, G
Sivarajan, S
Souza, E.G
Souza, W.J
Spekken, M
Spinelli, C.B
Stamm, M.J
Stevens, L.J
Sudduth, K.A
Teboh, J
Thompson, L
Torres-Sánchez, J
Torres-Sanchez, J
Tremblay, N
Trevisan, R.G
Turner, R.W
Uhlmann, N
Upadhyaya, S
Van Beers, R
Varela, S
Vellidis, G
Vigil, M
Vigneault, P
Vilanova Jr., N.D
Wagner, P
Waits, M
Wakahara, S
Wakahara, S
Walthall, C
Wang, H
Wang, X
Wang, Y
Werkmeister, B.K
Westerdijk, K
Williams, J.D
Wouters, N
Wulfsohn, D
Xie, R
Yeager, E.A
Yost, M
Yost, M.A
Zamora, I
Zarco-Tejada, P.J
Zhang, J
Zhang, Y
Zhang, Y
Zhao, X
Ziadi, N
chen, D
chen, T
de Castro, A
de Castro, A.I
de Souza, E.G
dong, J
jiang, S
van Es, H
van Evert, F
van Evert, F.K
Topics
Sensor Application in Managing In-season CropVariability
Education and Training in Precision Agriculture
Decision Support Systems in Precision Agriculture
Applications of UAVs (unmanned aircraft vehicle systems) in precision agriculture
In-Season Nitrogen Management
Wireless Sensor Networks
Profitability and Success Stories in Precision Agriculture
No Group Selected
Type
Oral
Poster
Year
2014
2010
2016
2022
2018
Home » Topics » Results

Topics

Filter results73 paper(s) found.

1. Developing And Teaching A Site-specific Crop/soil Management Course

           Site-specific crop/soil management technologies have been available for over fifteen years. Consequently, there is a demand for classroom and laboratory education across a variety of agricultural disciplines in the University community. To meet this demand, a course was developed in 1998 to teach the basic concepts of site-specific crop/soil management. This class is designed as a upper level undergraduate and graduate class and generally has between 1... M. Cox, D. Roberts

2. Precision Agriculture Education Program In Nebraska

With the cost of agricultural inputs and the instability of commodity prices increasing, demand is growing for training in the essential skills needed to successfully implement site-specific crop management. This set of skills is uniquely interdisciplinary in nature. Thus, it is essential for potential users of precision agriculture to understand the basics of geodetic and electronic control equipment, principles of geographic information systems, fundamenta... V.I. Adamchuk, R.B. Ferguson

3. Interpretation Of Thinking Process In Farmer’s Decision

An idea of knowledge management is composed of (1) defining the four steps of recognition: data, information, knowledge and wisdom, (2) decision-make actions of evidence mining and context making, (3) system makeup of input and output on management. In simulating expert farmers’ practiced, five factors of farming system and eleven units of thinking were derived. The five factors are crop, field, techno... S. Shibusawa

4. Experiencs Of Extension Education Via Online Delivery Of Programming Related To Precision Agriculture Technologies

This paper will describe the content and experiences teaching an extension education course on precision agriculture technologies via online delivery. The course was developed to be delivered in 16 weeks meeting one time a week online. There was also a one-day face-to-face hands-on session focused around 4 lab type activities related to GPS guidance, diagnosis, and setup and maximizing the usefulness of precision agriculture technologies. This course focuses on agricultura... D.K. Shannon

5. Revisited: A Case Study Approach For Teaching And Applying Precision Agriculture

Current agricultural students understand and are excited about new technologies, but often do not understand how precision agriculture can be applied to farming operations. A case-study approach that requires students to develop precision agriculture management practices which includes selecting equipment and assessing the financial feasibility could help students understand and apply precision agriculture. This paper revisits a case-study approach to teaching precision agriculture and descri... J.D. Williams, S.D. Mcgary, M. Waits

6. Isobus Demonstrator And Working Environment For Agricultural Engineering Education

ISOBUS is the international standard for communication on agricultural equipment. In practice, however, a manufacturer independent tractor-implement communication is still a significant problem. This aspect has been identified as a major hindrance for the transfer of research results into products for precision farming.  As a consequence the ISOBUS standard should strongly be included in education and research, which is the focus of this work. &nb... A. Ruckelshausen, T. Dzinaj, T. Kinder, D. Bosse, R. Klose

7. Farmer Perspectives Of Precision Agriculture In Western Australia

Many farmers in the Western Australian wheatbelt have successfully adopted guidance and yield mapping technologies. However they have so far avoided adopting variable rate technology (VRT).  While agronomists and farmers can determine the limiting factors to production, whether it is soil fertility, pH, plant available water capacity (PAWC) or others, they have less confidence in managing spatial variability. Although WA farmers understand the need to adopt these techniques they h... R. Mandel

8. Application based Wireless Sensor Node for Underground Moisture Sensing for Precision Agriculture

In this paper, we are attempting to examine the WUWSN (wireless underground water sensor node*) for precision agriculture. The development and function of this sensor along with its software application is described in this paper. The equipment is under testing and the laboratory results and interpretations are discussed in this paper. This equipment is based on the new concept of sensing underground soil moisture. The sensor is cost effective sensor and has a lon... S.P. Nayse, A.S. Mohammad

9. Rapidscan And CropCircle Radiometers: Opportunities And Limitation In Assessing Wheat Biomass And Nitrogen

Remote sensing is a promising technology that provides information about the crop's physiological and phenological status. This information is based on the spectral absorption and scattering features of the plants. Many different vegetation indices (VI) have been developed, and are in use to estimate quantitatively the relationship between multi and hyper-spectral reflectance and effective crop physiological parameters, i.e. nitrogen (N) content, biomass, leaf area index (LAI). The C... A.A. Gitelson, D.J. Bonfil

10. Active Optical Sensor Algorithms For Corn Yield Prediction And In-Season N Application In North Dakota

A recent series of seventy seven field N rate experiments with corn (Zea mays, L.) in North Dakota was conducted. Multiple regression analysis of the characteristics of the data set indicated that segregating the data into those with high clay soils and those with medium textures increased the relationship between N rate and corn yield. However, the nearly linear positive slope relationship in high clay soils and coarser texture soils with lower yield productivity indic... L. Sharma, H. Bu, R. Ashley, G. Endres, J. Teboh, D.W. Franzen

11. Development Of An Enterprise Level Precision Agriculture System

Development of an Enterprise Level Precision Agriculture System   James Ellingson, Chih Lai University of St. Thomas, School of Engineering 2115 Summit Ave, St. Paul, MN USA elli4729@stthomas.edu;   Abstract – In this paper, a plan for the development of an Enterprise Level system for Precision Agriculture (PA) is described. The ... J.L. Ellingson, B.K. Holub, S.E. Morgan, B.K. Werkmeister

12. Detection Of Nitrogen Deficiency In Potatoes Using Small Unmanned Aircraft Systems

  Small Unmanned Aircraft Systems (sUAS) are recognized as potentially important remote-sensing platforms for precision agriculture. A nitrogen rate experiment was established in 2013 with ‘Ranger Russet’ potatoes by applying four rates of nitrogen fertilizer (112, 224, 337, and 449 kg N/ha) in a randomized block design with 3 replicates. A Tetracam Hawkeye sUAS and Agricultural Digital Camera Lite sensor were used to collect imagery with near-infra... D.A. Horneck, D.J. Gadler, A.E. Bruce, R.W. Turner, C.B. Spinelli, J.J. Brungardt, P.B. Hamm, E. Hunt

13. The TOAS Project: UAV Technology For Optimizing Herbicide Applications In Weed-Crop Systems

Site-specific weed management refers to the application of customised control treatments, mainly herbicide, only where weeds are located within the crop-field. In this context, the TOAS project is being developed under the financial support of the European Commission with the main objective of generating georeferenced weed infestation maps of certain herbaceous (corn and sunflower) and permanent woody crops (poplar and olive orchards) by using aerial images collected by an unmanned aeria... J.M. Peña, J. Torres-sanchez, A.I. De castro, J. Dorado, F. Lopez-granados

14. In-Season Nitrogen Requirement For Maize Using Model And Sensor-Based Recommendation Approaches

Nitrogen (N), an essential element, is often limiting to plant growth.  There is great value in determining the optimum quantity and timing of N application to meet crop needs while minimizing losses.  Low nitrogen use efficiency (NUE) has been attributed to several factors including poor synchrony between N fertilizer and crop demand, unaccounted for spatial variability resulting in varying crop N needs, and temporal variances in crop N needs.  Applying a portion... L.J. Stevens, R.B. Ferguson, D.W. Franzen, N.R. Kitchen

15. Modeling Canopy Light Interception For Estimating Yield In Almond And Walnut Trees

A knowledge of spatio-temporal variability in potential yield is essential for site-specific nutrient management in crop production. The objectives of this project were to develop a model for photosynthetically active radiation (PAR) intercepted by almond and walnut trees based on data obtained from respective tree(s) and estimate potential crop yield in individual trees or in blocks of five trees. This project uses proximally sensed PAR interception data measured using a lightb... R. Dhillon, S. Upadhyaya, J. Roach, K. Crawford, B. lampinen, S. Metcalf, F. Rojo

16. Applying Conventional Vegetation Vigor Indices To UAS-Derived Orthomosaics: Issues And Considerations

In recent years, unmanned airborne systems (UAS) have gained a lot of interest for their potential use in precision agriculture. While the imagery from near-infrared (NIR) enabled off-the-shelf cameras included in UAS can be directly used to facilitate crop scouting, the application in quantitative analyses remains cumbersome. The ultimate goal is to calculate (nitrogen) prescription maps from vegetation indices obtained from UAS imagery, but two main issues hamper this workflow: (1) the... J. Quaderer, J. Coonen, A. Lange, K. Pauly

17. 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 pro... S. Bajwa, J. Nowatzki, W. Harnisch, B. Schatz, V. Anderson

18. 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 conductivi... F.A. Rodrigues junior, I. Ortiz-monasterio, P.J. Zarco-tejada, K. Ammar, B.G. Gérard

19. Development Of An Index-Based Insurance Product: Validation Of A Forage Production Index Derived From Medium Spatial Resolution fCover Time Series

An index-based insurance solution is developed by Pacifica Crédit Agricole Assurances and Astrium GEO-Information to estimate and monitor the near real-time forage production in France. In this system, payouts are indexed on an indicator, called Forage Production Index (FPI), calculated using a biophysical characterization of the grassland from medium spatial resolution remote sensing time series. We used the Fraction of green Vegetation Cover (fCover) integral ... A. Jacquin, G. Sigel, O. Hagolle, B. Lepoivre, A. Roumiguié, H. Poilvé

20. Detection Of Drainage Failure In Reconstructed Cranberry Soils Using Time Series Analysis

A cranberry farm is often a semi-closed water system, where water is applied by means of irrigation and drained using an artificial drainage system. Cranberry bogs must be drained to the water level inside the surrounding ditches in order to maintain an optimal pore pressure within the root zone, which is important for a number of reasons. First of all, Phytophthara causing root rot are commonly associated with irrigation with contaminated surface water (Oudemans, 1999)... S.J. Gumiere, Y. Périard, J. Caron, D.W. Hallema, J.A. Lafond

21. Comparison Of Calibration Models Developed For A Visible-Near Infrared Real-Time Soil Sensor

The visible-near infrared (Vis-NIR) based real-time soil sensor (RTSS) is found to be a great tool for determining distribution of various soil properties for precision agriculture purposes. However, the developed calibration models applied on the collected spectra for prediction of soil properties were site-specific (local). This is found to be less practical since the RTSS needs to be calibrated separately for every field. General calibration approach is expected to ... S. Shibusawa, M. Kodaira, I. Kana, S.N. Baharom

22. Cotton Field Relations Of Plant Height To Biomass Accumulation And N-Uptake On Conventional And Narrow Row Systems

Although studied for decades, cotton field management remains a challenge for growers, especially due to spatial variability of soil conditions and crop growth, which demands the use of variable rate application technology (VRT) for nitrogen and growth regulators to improve yields and quality and/or save inputs. Canopy optical reflectance sensors are being studied as an option to detect infield variability but may have some limitations due to the known effect of signal saturation when us... N. . Vilanova jr., J.P. Molin, C. Portz, L.V. Posada, G. Portz, R.G. Trevisan

23. X-Ray Computed Tomography For State Of The Art Plant And Root Analysis

During the last years, the formerly in medical applications established technique of X-ray computed tomography (CT) is used for non-destructive material analysis as well. Adapting this technique for the visualization and analysis of growth processes of plants above and underneath the soil enables new possibilities in the so called smart agriculture. Using State-of-the-art CT systems the computed 3D volume datasets allows the visualization and virtual analysis of hidden structures like ro... S. Reisinger, N. Uhlmann, R. Hanke, S. Gerth

24. 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

25. Crop Circle Sensor-Based Precision Nitrogen Management Strategy For Rice In Northeast China

GreenSeeker (GS) sensor-based precision N management strategy for rice has been developed, significantly improved N fertilizer use efficiency. Crop Circle ACS-470 (CC) active sensor is a new user configurable sensor, with a choice of 6 possible bands. The objectives of this study were to identify important vegetation indices obtained from CC sensor for estimating rice yield potential and rice responsiveness to topdressing N application and evaluate their potential improvements over GS no... Q. Cao, Y. Miao, J. Shen, S. Cheng, R. Khosla, F. Liu

26. Design And Construction Of An Ultrasonic Cutting Width Sensor For Full-Feed Type Mid-Sized Multi-Purpose Combines

Precision agriculture analyzes the spatial variability according to the characteristics of an optimum setting of agricultural materials. To raise the profitability of agriculture and to reduce the environmental impact, technological research and development of precision agriculture has been conducted. In Asian countries such as Ja... Y. Huh, S. Chung, Y. Chae, J. Lee, S. Kim, M. Choi, K. Jung

27. Unmanned Aerial System Applications In Washington State Agriculture

Three applications of unmanned aerial systems (UAS) based imaging were explored in row, field, and horticultural crops at Washington State University (WSU). The applications were: to evaluate the necrosis rate in potato field crop rotation trials, to quantify the emergence rates of three winter wheat advanced yield trials, and detecting canker disease-infection in pear. The UAS equipped with green-NDVI imaging was used to acquire field aerial images. In the first appli... L. Khot, S. Sankaran, D. Johnson, A. Carter, S. Serra, S. Musacchi, T. Cummings

28. Weed Seedlings Detection In Winter Cereals For Site-Specific Control: Use Of UAV Imagery To Overcome The Challenge

Weed management is an important part of the investments in crop production. Cost of herbicides accounts for approximately 40% of the cost of all the chemicals applied to agricultural land in Europe. In order to increase the profitability of crop production and to reduce the environmental concerns related to chemicals application, it is needed to develop site-specific weed management strategies in which herbicides are only applied in the crop zones were weeds spread. Moreover, th... J. Peña, A. De castro, F. López-granados, J. Torres-sánchez

29. Design And Implementation Of Agricultural Sensor Data Of Multiple And Heterogeneous Access Architecture

For the moment, the Internet of things system oriented to the whole industry chain is gradually established in some fields of agriculture; At the same time, traditional management style of agricultural sensor data lack effective sharing mechanism, that can not meet the demand of agricultural network system for the multiple and heterogeneous sensor data. Especially with the growing the demand of agricultural products quality safety supervision system to the monitoring of agricult... T. Chen, D. Chen, J. Dong, S. Jiang

30. Towards Automated Pneumatic Thinning Of Floral Buds On Pear Trees

Thinning of pome and stone fruit is an important horticultural practice that is used to enhance fruit set and quality by removing excess floral buds. As it is still mostly conducted through manual labor, thinning comprises a large part of a grower’s production costs. Various thinning machines developed in recent years have clearly demonstrated that mechanization of this technique is both feasible and cost effective. Generally, these machines still lack sufficient selectivi... N. Wouters, R. Van beers, B. De ketelaere, T. Deckers, J. De baerdemaeker, W. Saeys

31. Unmanned Aerial System To Determine Nitrogen Status In Maize

Maize field production shows spatial variability during vegetative crop growth that could be used to prescribe nitrogen variable rates. The use of portable sensors mounted on high-clearance applicators is well documented, however new UAS vehicle equipped with high resolution digital cameras could be used to determine crop spatial variability with the advantage of survey extensive field areas. To our knowledge, comparisons between vegetation indices obtained by a modified digital camera a... A.C. Kemerer, S.M. Albarenque, R.J. Melchiori

32. sUAVS Technology For Better Monitoring Crop Status For Winter Canola

The small-unmanned aircraft vehicles (sUAVS) are currently gaining more popularity in agriculture with uses including identification of weeds and crop production issues, diagnosing nutrient deficiencies, detection of chemical drift, scouting for pests, identification of biotic or abiotic stresses, and prediction of biomass and yield. Research information on the use of sUAVS have been published and conducted in crops such as rice, wheat, and corn, but the development of... I.A. Ciampitti, K. Shroyer, V. Prasad, A. Sharda, M.J. Stamm, H. Wang, K. Price, D. Mangus

33. A Comparison Of Performance Between UAV And Satellite Imagery For N Status Assessment In Corn

A number of platforms are available for the sensing of crop conditions. They vary from proximal (tractor-mounted) to satellites orbiting the Earth. A lot of interest has recently emerged from the access to unmanned aerial vehicles (UAVs) or drones that are able to carry sensors payloads providing data at very high spatial resolution. This study aims at comparing the performance of a UAV and satellite imagery acquired over a corn nitrogen response trial set-up. The nitrogen (N) r... P. Vigneault, N. Tremblay, M.Y. Bouroubi, C. Bélec, E. Fallon

34. Using Imagery As A Proxy Yield Map And Scouting Tool

Combine yield maps represent a post-mortem quantification of the spatial variability in crop vigor that occurred during the growing season. The spatial resolution of yield maps is defined by the width of the combine header but the length of the cell depends on the ground-speed of the implement and how long it takes for the grain t... J.S. Schepers, A.R. Schepers

35. The Use Of A Multirotor And High-Resolution Imaging For Precision Horticulture In Chile: An Industry Perspective

As part of the prototype development of a yield forecasting and precision agriculture service for Chilean horticulture, we evaluated the use of an eight-rotor Mikrokopter for high-resolution aerial imaging to support ground-based surveys. Specific considerations for UAV and communications performance under Chilean conditions are windy conditions, limited space for take-off and landing in orchards, tree height and plantation density, and the presence of high metal contents in soils. We di... I. Zamora, D. Wulfsohn

36. Site Specific Costs Concerning Machine Path Orientation

Computer algorithms have been created to simulate in advance the orientation/pattern of a machine operation on a field. Undesired impacts were obtained and quantified for these simulations, like: maneuvering and overlap of inputs in headlands; servicing of secondary units; and soil loss by water erosion. While the efforts could minimize the overall costs, they disregard the fact that these costs aren’t uniformly distributed over irregular fields. The cost of a non-productive machine pro... M. Spekken, J.P. Molin, T.L. Romanelli, M.N. Ferraz

37. Considering Farmers' Situated Expertise in AgriDSS Development to Fostering Sustainable Farming Practices in Precision Agriculture

Agriculture is facing immense challenges and sustainable intensification has been presented as a way forward where precision agriculture (PA) plays an important role. More sustainable agriculture needs farmers who embrace situated expertise and can handle changing farming systems. Many agricultural decision support systems (AgriDSS) have been developed to support farm management, but the traditional approach to AgriDSS development is mostly based on knowledge transfer. This has resulted in te... C. Lundström, J. Lindblom

38. Comparing Adapt-N to Static N Recommendation Approaches for US Maize Production

Large temporal and spatial variability in soil N availability leads many farmers across the US to over apply N fertilizers in maize (Zea Mays L.) production environments, often resulting in large environmental N losses.  Static N recommendation tools are typically promoted in the US, but new dynamic model-based tools allow for more precise and adaptive N recommendations that account for specific production environments and conditions. This study compares two static N recommendation tools... H. Van es, S. Sela, R. Marjerison, B. Moebiu-clune, R. Schindelbeck, D. Moebius-clune

39. Data Normalization Methods for Definition of Management Zones

The use of management zones is considered a viable economic alternative for the management of crops due to low cost of adoption as well as economic and environmental benefits. The decision whether or not to normalize the attributes before the grouping process (independent of use) is a problem of methodology, because the attributes have different metric size units, and may influence the result of the clustering process. Thus, the aim of this study was to use a Fuzzy C-Means algorithm to evalua... K. Schenatto, E.G. De souza, C.L. Bazzi, A. Gavioli, N.M. Betzek, H.M. Beneduzzi

40. EZZone - An Online Tool for Delineating Management Zones

Management zones are a pillar of Precision Agriculture research.  Spatial variability is apparent in all fields, and assessing this variability through measurement devices can lead to better management decisions.  The use of Geographic Information Systems for agricultural management is common, especially with management zones.  Although many algorithms have been produced in research settings, no online software for management zone delineation exists.  This research used a ... G. Vellidis, C. Lowrance, S. Fountas, V. Liakos

41. Smart Agriculture: A Futuristic Vision of Application of the Internet of Things (IoT) in Brazilian Agriculture

With the economy based on agribusiness, Brazil is an important representative on the world stage in agricultural production, either in terms of quantity or cultivated diversity due to a scenario with vast arable land and favorable climate. There are many crops that are adapteble to soils of the country. Despite the global representation, it is known that the Brazilian agricultural production does not yet have a modern agriculture by restricting the use of new technologies to farmers with bett... C.L. Bazzi, R. Araujo, E.G. Souza, K. Schenatto, A. Gavioli, N.M. Betzek

42. Towards Data-intensive, More Sustainable Farming: Advances in Predicting Crop Growth and Use of Variable Rate Technology in Arable Crops in the Netherlands

Precision farming (PF) will contribute to more sustainable agriculture and the global challenge of producing ‘More with less’. It is based on the farm management concept of observing, measuring and responding to inter- and intra-field variability in crops. Computers enabled the use of Farm Management Information Systems (FMIS) and farm and field specific Decision Support Systems (DSS) since mid-1980s. GIS and GNSS allowed since ca. 2000 geo-referencing of data and controlled traff... C. Kempenaar, F. Van evert, T. Been, C. Kocks, K. Westerdijk, S. Nysten

43. Agronomic Characteristics of Green Corn and Correlations with Productivity for the Establishment of Management Zones in Vale Do Ribeira, SP, Brazil

In Brazil, the progressive development in the cultivation of the corn for consumption in the green stadium stands by the relevant socio-economic role that this related to multiple applications, the attractive market price and continuous demand for the product in nature. Therefore, this study was to analyze the correlations and spatial variability of the productivity of the culture of the green corn in winter, in alluvial soil of the type Cambisols eutrophic in the amount areas and Hydromorphi... W.J. Souza, V.S. Akune, S.H. Benez, L.C. Citon, P.H. Nakazawa, A.J. Santana neto

44. On Farm Studies to Determine Seeding Rate in Corn

Seeding rate (SDR) is one of the most critical production practices impacting productivity and economic return for corn (Zea mays L.) By changing SDRs in different zones within a field, herein termed as site-specific management, better economic results can be produced as the outcome of reducing SDRs in low productivity areas and increasing SDRs under high-yielding environments, relative to the uniform SDR management performed by the producer. The aim of this study was to analyze yield respons... G. Balboa, S. Varela, I. Ciampitti, S. Duncan, T. Maxwell, D. Shoups, A. Sharda

45. Closing Yield Gaps with GxExM and Precision Agriculture

There are many challenges to be faced by agriculture if the global population of nine billion people projected for 2050 is to be fed and clothed, especially given the effects of changing climate.  A focus on the interactions of genetics x environment x management (GxExM) offers potential for meeting the yield, and environment and economic sustainability goals that are integral to these challenges.  The yield gap –defined as the difference between current farmer yields and pote... C. Walthall, J. Hatfield, S. Schneider, M. Vigil

46. 25 Years Precision Agriculture in Germany - a Retrospective

It all started with the availability of Global Positioning Systems for civil services in 1988. In the same year variable rate applications of fertilizers were demonstrated in northern Germany and Denmark, which were globally the first of their kind and introduced a new era of agricultural production. The idea of Computer Aided Farming (CAF) was born. Only one year later the first yield maps were established. In 1992 at the Soil Specific Crop Management Workshop in Bloomington, Minnesota which... H. Lilienthal, E. Schnug, S. Haneklaus

47. An Economic Feasibility Assessment for Adoption of Autonomous Field Machinery in Row Crop Production

A multi-faceted whole farm planning model was developed to compare conventional and autonomous machinery for grain crop production.  Results suggested that autonomous machinery could be an economically viable alternative to conventional manned machinery if the establishment of intelligent controls was cost effective.  An increase in net returns of 22% over operating with conventional machinery was found.  This study also identified the break-even investment price for intelligen... J.M. Shockley, C. Dillon

48. A Long-Term Precision Agriculture System Maintains Profitability

After two decades of availability of grain yield-mapping technology, long-term trends in field-scale profitability for precision agriculture (PA) systems and conservation practices can now be assessed. Field-scale profitability of a conventional or ‘business-as-usual’ system with an annual corn (Zea mays L.)-soybean (Glycine max [L.]) rotation and annual tillage was assessed for 11 years on a 36-ha field in central Missouri during 1993 to 2003. Following this, a ‘precision a... M.A. Yost, N.R. Kitchen, K.A. Sudduth, S.T. Drummond, R.E. Massey

49. Yield Maps, Soil Maps, and Technical Efficiency: Evidence from U.S. Corn Fields

Yield maps and GPS-based soil maps have been increasingly used in U.S. agriculture but little research has explored the economic relationship between mapping technologies and agricultural productivity. Research on this relationship is lacking, perhaps because maps are information inputs that do not directly enter the production function in a comparable way to conventional inputs. A stochastic frontier model was used to evaluate one potential avenue through which mapping technologies may influ... J. Mcfadden, A. Rosburg

50. Evaluation of the Potential for Precision Agriculture and Soil Conservation at Farm and Watershed Scale: A Case Study

Precision agriculture and soil conservation have the potential to increase crop yield and economic return while reducing environmental impacts. Landform, spatial variability of soil processes, and temporal trends may affect crop N response and should be considered for precision agriculture. The objective of this research was to evaluate the viability of precision agriculture in improving N use efficiency and profitability at the farm and watershed level in western Canada. Two studies are desc... M. Khakbazan, A. Moulin, J. Huang, P. Michiels, R. Xie

51. Barriers to Adoption of Smart Farming Technologies in Germany

The number of smart farming technologies available on the market is growing rapidly. Recent surveys show that despite extensive research efforts and media coverage, adoption of smart farming technologies is still lower than expected in Germany. Media analysis, a multi stakeholder workshop, and the Adoption and Diffusion Outcome Prediction Tool (ADOPT) (Kuehne et al. 2017) were applied to analyze the underlying adoption barriers that explain the low to moderate adoption levels of smart farming... M. Gandorfer, S. Schleicher, K. Erdle

52. Akkerweb: A Platform for Precision Farming Data, Science, and Practice

The concept of precision farming (PF) was formulated about 40 years ago and the scientific knowledge for some applications of PF in The Netherlands has been available for almost 20 years. Also, in many cases equipment is available to implement PF in practice. In spite of all this PF uptake is still limited. An important reason for the limited uptake of PF is in the challenges that must be overcome to let data flow from sensors to data storage, to combine data sources and process them into rec... F.K. Van evert, T. Been, J.A. Booij, C. Kempenaar, G.J. Kessel, L.P. Molendijk

53. Using Profitability Map to Make Precision Farming Decisions: A Case Study in Mississippi

Recent development in precision agriculture technologies have generated massive amount of geospatial data of farming, such as yield mapping, seeding rates, input applications, and so on. However, producers are still struggling to convert those precision data into farm management decisions to improve productivity and profitability of farming.  Indeed, deriving accurate decisions at each site of the field requires complex and comprehensive modeling of crop yield responses to vari... X. Li, K. Coble

54. Toward a Precision Agricultural Implementation for Sugar Cane Plantations in Southwestern Region of Colombia, South America

The Colombian Sugar Cane Research Center, CENICAÑA, has initiated an ambitious project for the implementation of Precision Agriculture (PA) technologies in the Cauca river valley region, where one of its main objectives is to have the ability to collect large volumes of geospatial data. The main sugarcane growers in the country perform their work in the selected work area, which covers an area of ​​approximately 242,000 ha, characterized by diverse topographic and edaphic condition... J.A. Celades, J.H. Caicedo, C.E. García, H. Mora

55. Adoption of Precision Agriculture Technology: A Duration Analysis

Precision agriculture technologies have been available for adoption and utilization at the farm level for several decades. Some technologies have been readily adopted while others were adopted more slowly. An analysis of 621 Kansas Farm Management Association (KFMA) farmer members provided insights regarding adoption, upgrading, and abandonment of technology. The likelihood that farms adopt specific technology given that other technology had been adop... T.W. Griffin, E.A. Yeager

56. The Impact of Precision Agriculture Technologies on Farm Profitability in Kansas

Even with more than a decade long adoption of the precision agriculture (PA) technologies in the United States, its impact on farm profitability is still not clear. This paper uses farm level data from Kansas Farm Management Association (KFMA) to conduct the ex-post evaluation of PA technologies on farm profitability in Kansas. The analysis of the data using propensity score matching method indicates that there is on an average $60,000 difference in net returns of the farm with at least one P... S. Dhoubhadel, T.W. Griffin

57. Variable-Rate-Fertilization of Phosphorus and Lime – Economic Effects and Maximum Allowed Costs for Small-Scale Soil Analysis

The pH values and macro nutrient contents are characterised by considerable variance within a field. A constant-rate-fertilization, which is practiced at most farms, does not reduce this effect, it may even boost variance. Besides the suboptimal nutrient supply, the site-specific yield potential is not exploited. Constant-rate-fertilization and liming results in an inefficient utilisation by over- and undersupply of most of the areas within a field. Fertilization with lime and phosphorus caus... S. Schulte-ostermann, P. Wagner

58. Risk Efficiency of Site-Specific Nitrogen Management with Respect to Grain Quality

Profitability analyses of site-specific nitrogen management strategies have often failed to provide reasons for adoption of precision farming implements. However, often effects of precision farming on product quality and price premiums were not taken into account. This study aims to evaluate comparative advantages of site-specific nitrogen management over uniform nitrogen management with respect to aspects of risk, considering fertilizer effects on grain quality and price premiums. We develop... A. Meyer-aurich, Y. Karatay, M. Gandorfer

59. Use Cases for Real Time Data in Agriculture

Agricultural data of many types (yield, weather, soil moisture, field operations, topography, etc.) comes in varied geospatial aggregation levels and time increments. For much of this data, consumption and utilization is not time sensitive. For other data elements, time is of the essence. We hypothesize that better quality data (for those later analyses) will also follow from real-time presentation and application of data for it is during the time that data is being collected that errors can ... J. Krogmeier, D. Buckmaster, A. Ault, Y. Wang, Y. Zhang, A. Layton, S. Noel, A. Balmos

60. A Gap Analysis of Broadband Connectivity and Precision Agriculture Adoption in Southwestern Ontario, Canada

In Southwestern Ontario (Canada), the availability of broadband, or high-speed internet, likely influences the adoption of precision agriculture (PA) technologies and functions of these technologies which enable real-time data sharing between the field and the digital cloud, and back again to the farm-level user. This paper examines the reasons why PA technologies are, or are not adopted, and adoption in relation to varying levels of broadband access. Broadband access is defined here with var... H. Hambly, M. Chowdury

61. Soil and Crop Factors to Site-specific Nitrogen Management on Sugarcane Fields

Nitrogen (N) is one of the most widely used fertilizers in crops and the most harmful to the environment. The increase fertilizers consumption, mainly N sources (one of the most widely fertilizer used in sugarcane fields), is one of the main factors underlying the sustainability of the entire production process. Currently, N recommendations in sugarcane are based only on the expected yield. However, there is little agronomic support for nitrogen (N) recommendations based on expected yield, de... G.M. Sanches, R. Otto, F.R. Pereira

62. A Passive-RFID Wireless Sensor Node for Precision Agriculture

Accurate soil data is crucial for precision agriculture.  While existing optical methods can correlate soil health to the gasses emitted from the field, in-soil electronic sensors enable real-time measurements of soil conditions at the effective root zone of a crop. Unfortunately, modern soil sensor systems are limited in what signals they can measure and are generally too expensive to reasonably distribute the sensors in the density required for spatially accurate feedback.  In thi... P.J. Goodrich, C. Baumbauer, A.C. Arias

63. Spatial and Temporal Factors Impacting Incremental Corn Nitrogen Fertilier Use Efficiency

Current tools for making crop N fertilizer recommendations are primarily based on plot and field studies that relate the recommendation to the economic optional N rate (EONR).  Some tools rely entirely on localized EONR (e.g., MRTN). In recent years, tools have been developed or adapted to  account for within-field variation in crop N need or variable within season factors. Separately, attention continues to elevate for how N fertilizer recommendations might account for environmenta... N.R. Kitchen, C.J. Ransom, J.S. Schepters, J.L. Hatfield, R. Massey

64. Evaluating a Satellite Remote Sensing and Calibration Strip-based Precision Nitrogen Management Strategy for Corn in Minnesota and Indiana

Precision nitrogen (N) management (PNM) aims to match N supply with crop N demand in both space and time and has the potential to improve N use efficiency (NUE), increase farmer profitability, and reduce N losses and negative environmental impacts. However, current PNM adoption rate is still quite low. A remote sensing and calibration strip-based PNM strategy (RS-CS-PNM) has been developed by the Precision Agriculture Center at the University of Minne... K. Mizuta, Y. Miao, A.C. Morales, L.N. Lacerda, D. Cammarano, R.L. Nielsen, R. Gunzenhauser, K. Kuehner, S. Wakahara, J.A. Coulter, D.J. Mulla, D. . Quinn, B. Mcartor

65. Nitrogen Fertilization of Potato Using Management Zone in Prince Edward Island, Canada

Potato is sensible to nitrogen (N) and optimal N fertilization improve the tuber yield and its quality. Potato crop N response varies widely within fields. It is also well recognized that significant spatial and temporal variation in soil N availability occurs within crop fields. However, uniform application of N fertilizer is still the most common practice under potato production. Management zone (MZ) approach can help growers to achieve a part of this. The goal of the project is to compare ... A. Cambouris, M. Duchemin, N. Ziadi

66. Evaluating the Potential of Improving In-season Nitrogen Status Diagnosis of Potato Using Leaf Fluorescence Sensors and Machine Learning

Precision nitrogen (N) management is particularly important for potato crops due to their high N fertilizer demand and high N leaching potential caused by their shallow root systems and preference for coarse-textured soils. Potato farmers have been using a standard lab analysis called petiole nitrate-N (PNN) test as a tool to diagnose potato N status and guide in-season N management. However, the PNN test suffers from many disadvantages including time constraints, labor, and cost of analysis.... S. Wakahara, Y. Miao, S. Gupta, C. Rosen, K. Mizuta, J. Zhang, D. Li

67. Nitrogen Status Prediction on Pasture Fields Can Be Reached Using Visible Light UAV Data Combined with Sentinel-2 Imagery

Pasture fields under integrated crop-livestock system usually receive low or no nitrogen fertilization rates, since the expectation is that nitrogen demand will be provided by the soybean remaining straw cropped previously. However, keeping nitrogen at suitable levels in the entire field is the key to achieving sustainability in agricultural production systems. In this sense, remote sensing technologies play an essential role in nitrogen monitoring in pastures and crops. With the launch of th... F.R. Pereira, J.P. Lima, R.G. Freitas, A.A. Dos reis, L.R. Amaral, G.K. Figueiredo, R.A. Lamparelli, J.C. Pereira, P.S. Magalhães

68. Variable Rate Nitrogen Approach in a Potato-wheat-wheat Cropping System

Nitrogen application in agriculture is a vital process for optimal plant growth and yield outcomes. Different factors such as topography, soil properties, historical yield, and crop stress affect nitrogen (N) needs within a field. Applying variable N within a field could improve precision agriculture. Optimal N management is a system that involves applying a conservative variable base rate at or shortly after planting followed by in-season assessment and, if needed, variable rate application&... E.A. Flint, M. Yost, B.G. Hopkins

69. Evaluation of Nitrogen Recommendation Tools for Winter Wheat in Nebraska

Attaining both high yield and high nitrogen (N) use efficiency (NUE) simultaneously remains a current research challenge in crop production. Digital ag technologies for site-specific N management have been demonstrated to improve NUE. This is due to the ability of digital technologies to account for the spatial and temporal distribution of crop N demand and available soil N in the field which varies greatly according t... J. Cesario pereira pinto, L. Thompson, N. Mueller, T. Mieno, G. Balboa, L. Puntel

70. 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

71. 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

72. Assessment of Active Crop Canopy Sensor As a Tool for Optimal Nitrogen Management in Dryland Winter Wheat

Optimum nitrogen (N) fertilizer application is important for agronomic, economic, and environmental reasons. Among different N management tools, active crop canopy sensors are a recent and promising tool widely evaluated for use in corn but still under-evaluated for use in winter wheat. The objective of this study was to determine whether vegetation indices derived from in-season active crop canopy sensor data can be used to predict winter wheat grain yield and protein content and subsequentl... D. Ghimire

73. In-season Diagnosis of Winter Wheat Nitrogen Status Based on Rapidscan Sensor Using Machine Learning Coupled with Weather Data

Nitrogen nutrient index (NNI) is widely used as a good indicator to evaluate the N status of crops in precision farming. However, interannual variation in weather may affect vegetation indices from sensors used to estimate NNI and reduce the accuracy of N diagnostic models. Machine learning has been applied to precision N management with unique advantages in various variables analysis and processing. The objective of this study is to improve the N status diagnostic model for winter wheat by c... J. Lu, Z. Chen, Y. Miao, Y. Li, Y. Zhang, X. Zhao, M. Jia