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Keresztes, B
Kovacs, A.J
Kipper, M
Kirkpatrick, T
Zhang, J
Kiel, A
Krol, C
Khosla, R
Zhang, F
Kim, H
Ziadi, N
Kidd, J
Zermas, D
Zhao, Y
Kana, I
Khosla, R
Jansky, T
Khosro Anjom, F
Kolar, P.R
Klein, R.N
Koundouras, S
Jensen, N
Zhang, Q
Karatay, Y
Zhang, Y
Kumpatla, S
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Authors
Gupta, M
Khosla, R
Klein, R.N
Wilson, R
Bazzi, C.L
Souza, E.G
Khosla, R
Reich, R.M
Naser, M.A
Khosla, R
Reich, R
Haley, S
Longchamps, L
Moragues, M
Buchleiter, G.W
McMaster, G.S
Khosla, R
Westfall, D.G
Longchamps, L
Khosla, R
Longchamps, L
Longchamps, L
Panneton, B
Westfall, D.G
Khosla, R
Shanwad, U.K
Patil, M.B
H, V
B.G , M
R, P
N.L. , R
S, S
Khosla, R
Patil, V.C
Zhao, G
Miao, Y
Zhang, F
Fan, M
Liu, Z
Griffin, T
Kirkpatrick, T
Monfort, S
Yao, Y
Miao, Y
Huang, S
Gnyp, M.L
Khosla, R
Jiang, R
Bareth, G
Cao, Q
Miao, Y
Feng, G
Gao, X
Liu, B
Khosla, R
Krol, C
Dempsey, D
Zhang, X
Streeter, C.R
Kim, H
Olsen, D.R
Miao, Y
Cao, Q
Cui, Z
Li, F
Dao, T.H
Khosla, R
Chen, X
Moshia, M.E
Khosla, R
Davis, J
Westfall, D
Krueger, E
Kurtener, D
Kurtener, D
Khosla, R
Mzuku, M
Khosla, R
Reich, R
http://icons.paqinteractive.com/16x16/ac, G
Smith, F
MacDonald, L
Shaver, T
Khosla, R
Westfall, D
LAK, M
Khosro Anjom, F
Tatge, J
Stromberger, M
Khosla, R
Shaner, D
Zach, D
Zhao, Y
Li, L
Ting, K.C
Tian, L.F
Ahamed, T
Anselmi, A.A
Molin, J.P
Khosla, R
Shibusawa, S
Kodaira, M
Kana, I
Baharom, S.N
Chen, M
Li, M
Qian, J
Li, W
Wang, Y
Zhang, Y
Yang, X
Vougioukas, S.G
Jimenez, F.J
Khosro Anjom, F
Elkins, R
Ingels, C
Arikapudi, R
Cao, Q
Miao, Y
Shen, J
Cheng, S
Khosla, R
Liu, F
Fountas, S
Kotseridis, Y
Balafoutis, A
Anastasiou, E
Koundouras, S
Kallithraka, S
Kyraleou, M
Siegfried, J
Khosla, R
Longchamps, L
Kizer, E
Upadhyaya, S.K
Rojo, F
Ozmen, S
Ko-Madden, C
Zhang, Q
Patto Pacheco, E
Liu, J
Longchamps, L
Khosla, R
Weckler, P
Morris, C
Arnall, B
Alderman, P
Kidd, J
Sutherland, A
Mulla, D
Zermas, D
Kaiser, D
Bazakos, M
Papanikolopoulos, N
Stanitsas, P
Morellas, V
Longchamps, L
Khosla, R
Reich, R
Kyveryga, P.M
Fey, S
Connor, J
Kiel, A
Muth, D
Nyeki, A
Milics, G
Kovacs, A.J
Neményi, M
Kalmar, J
Klein, R.N
Golus, J.A
Cox, A.S
Abdelghafour, F.Y
Rosu, R
Keresztes, B
Germain, C
Da Costa, J
Keresztes, B
Da Costa, J
Randriamanga, D
Germain, C
Abdelghafour, F
Rydahl, P
Jorgensen, R.N
Dyrmann, M
Jensen, N
Sorensen, M.D
Bojer, O.M
Andersen, P
Pomar, C
Andretta, I
Hauschild, L
Kipper, M
Pires, P.S
Phillippi, E
Khosla, R
Longchamps, L
Turk, P
Meyer-Aurich, A
Karatay, Y
Gandorfer, M
DuPont, E.M
Kolar, P.R
Rydahl, P
Boejer, O
Jensen, N
Hartmann, B
Jorgensen, R
Soerensen, M
Andersen, P
Paz, L
Nielsen, M.B
Yilma, W.A
Siegfried, J
Khosla, R
Yang, C
Suh, C
Guo, W
Zhao, H
Zhang, J
Eyster, R
Mandal, D
Siqueira, R.D
Longchamps, L
Khosla, R
Straw, C
Wyatt, B
Smith, A.P
Watkins, K
Hong, S
Floyd, W
Williams, D
Garza, C
Jansky, T
Sridharan, S
Sornapudi, S
Hu, Q
Kumpatla, S
Bier, J
Siegfried, J
Khosla, R
Mandal, D
Yilma, W
Nze Memiaghe, J
Cambouris, A.N
Ziadi, N
Duchemin, M
Karam, A
Cambouris, A
Duchemin, M
Ziadi, N
Topics
Precision Nutrient Management
Profitability, Sustainability and Adoption
Remote Sensing Applications in Precision Agriculture
Guidance, Robotics, Automation, and GPS Systems
Food Security and Precision Agriculture
Spatial Variability in Crop, Soil and Natural Resources
Sensor Application in Managing In-season Crop Variability
Proximal Sensing in Precision Agriculture
Precision A to Z for Practitioners
Remote Sensing Applications in Precision Agriculture
Precision Nutrient Management
Spatial Variability in Crop, Soil and Natural Resources
Sensor Application in Managing In-season Crop Variability
Profitability, Sustainability, and Adoption
Remote Sensing Applications in Precision Agriculture
Spatial Variability in Crop, Soil and Natural Resources
Sensor Application in Managing In-season CropVariability
Precision Horticulture
Engineering Technologies and Advances
Remote Sensing Applications in Precision Agriculture
Proximal Sensing in Precision Agriculture
Unmanned Aerial Systems
Precision Agriculture and Climate Change
Profitability, Sustainability and Adoption
Guidence, Auto steer, and Robotics
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Precision Crop Protection
Precision Dairy and Livestock Management
In-Season Nitrogen Management
Profitability and Success Stories in Precision Agriculture
Robotics, Guidance and Automation
Precision Crop Protection
Decision Support Systems
Applications of Unmanned Aerial Systems
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Geospatial Data
Big Data, Data Mining and Deep Learning
In-Season Nitrogen Management
Type
Poster
Oral
Year
2012
2010
2014
2016
2008
2018
2022
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Authors

Filter results53 paper(s) found.

1. Near Real-time Meter-resolution Airborne Imagery For Precision Agriculture: Aerocam

Precision agriculture often relies on high resolution imagery to delineate the variability within a field. Airborne Environmental Research Observational Camera (AEROCam) was designed to meet the needs of agriculture producers, ranchers, and researchers, who require meter-solution imagery in a near real-time environment for rapid decision support. AEROCam was developed and operated through a unique collaboration... X. Zhang, C.R. Streeter, H. Kim, D.R. Olsen

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

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

3. Precision Manure Management: It Matters Where You Put Your Manure

“Precision fertilizer management” has been around for more than a decade and is practiced widely in Colorado and elsewhere. By precision, we mean application of fertilizer at the right time, in the right place, and in the right amount. However, “Precision Manure Management” is a relatively new concept that converge the best manure management practices with precision nutrient management practices, such as variable rate nutrient application across site-specific management... M.E. Moshia, R. Khosla, J. Davis, D. Westfall

4. Evaluation Of Different N Management Strategies Using A Tool For Fuzzy Multi Attributive Comparison Of Alternatives

Application of precision agriculture is related with choosing of optimal agrotechnilogy and, in particular, with definition of the best alternative of N management strategy. A potential satisfactory solution of this decision analysis problem could be the uses of multi attribute decision-making analysis based on fuzzy set theory and fuzzy logic (FMADA). This technique provides a means to achieve an optimal decision for real world problems which involve multiple alternatives and criteria... E. Krueger, D. Kurtener, D. Kurtener, R. Khosla

5. Spatial Variability Of Measured Soil Properties Across Site- Specific Management Zones

The spatial variation of productivity across farm fields can be classified by delineating site-specific management zones. Since productivity is influenced by soil characteristics, the spatial pattern of productivity could be caused by a corresponding variation in certain soil properties. Determining the source of variation in productivity can help achieve more effective site-specific management, the objectives of this study were (i) to characterize the spatial variability of soil physical properties... M. Mzuku, R. Khosla, R. Reich, G. Http://icons.paqinteractive.com/16x16/ac, F. Smith, L. Macdonald

6. Development Of A Nitrogen Requirement Algorithm Using Ground-based Active Remote Sensors In Irrigated Maize

Studies have shown that normalized difference vegetation index (NDVI) from ground-based active remote sensors is highly related with leaf N content in maize (Zea mays). Remotely sensed NDVI imagery can provide valuable information about in-field N variability in maize and significant linear relationships between sensor NDVI and maize grain yield have been found suggesting that an N recommendation algorithm based on NDVI could optimize N application. Therefore, a study was conducted using the two... T. Shaver, R. Khosla, D. Westfall

7. Economics Of Precision Agriculture For Wheat And Barley Cultivation In Hamedan, Western Iran

    Precision agriculture can influence agricultural operation economics. In this study, minimum economical farm sizes for producing irrigated/dry wheat and barley in... M. Lak, F. Khosro anjom, J. Tatge

8. Spatio-temporal Analysis Of Atrazine Degradation And Associated Attributes In Eastern Colorado Soils

Atrazine catabolism is an example of a rapidly evolved soil microbial adaptation. In the last 20 years, atrazine-degrading bacteria have become globally distributed, and many soils have developed enhanced capacities to degrade atrazine, reducing its half-life from 60 to a few days or less. While the presence of atrazine-degrading bacteria determine a soil's potential to catabolize atrazine,... M. Stromberger, R. Khosla, D. Shaner, D. Zach

9. Precision Nitrogen Management and Global Nitrogen Use Efficiency

Traditionally, nitrogen (N) fertilizers have been applied uniformly across entire field while ignoring inherent spatial variation in crop N needs across crop fields. This results in either too little or too much application of N in various parts of the fields.... M. Gupta, R. Khosla

10. 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

11. A Statistical and an Agronomic Approach for Definition of Management Zones in Corn and Soybean

The use of productivity level management zones (MZ) has demonstrated good potential for the site-specific management of crop inputs in traditional row crops. The objectives of this research were to analyze the process of defining MZs and develop methods to evaluate the quality of MZ maps. Two approaches were used to select the layers to be used in the MZ definition: 1) Statistical Approach (SA_MZ) and 2) Agronomic Approach (AA_MZ). The difference is that in the AA_MZ approach all non stable variables... C.L. Bazzi, E.G. Souza, R. Khosla, R.M. Reich

12. Variation in Nitrogen Use Efficiency for Multiple Wheat Genotypes across Dryland and Irrigated Cropping Systems

ABSTRACT ... M.A. Naser, R. Khosla, R. Reich, S. Haley, L. longchamps, M. Moragues, G.W. buchleiter, G.S. Mcmaster

13. Early Detection of Corn N-Deficiency by Active Fluorescence Sensing in Maize

Globally, the agricultural nitrogen use efficiency (NUE) is no more than 40 %. This low efficiency comes with an agronomic, economic and environmental cost. By better management of spatial and temporal variability of crop nitrogen need, NUE can be improved. Currently available crop canopy sensors based on reflectance are capable... R. Khosla, D.G. Westfall, L. Longchamps

14. Comparing Sensing Platforms for Crop Remote Sensing

Remote sensing offers the possibility to obtain a rapid and non-destructive diagnosis of crop health status. This gives the opportunity to apply variable rates of fertilizers to meet the actual crop needs at every locations of the field. However, the commonly used normalized difference vegetation index (NDVI)... R. Khosla, L. Longchamps

15. Testing The Author Sequence - Finalize

This is just a test to verify the bug with the authors sequence. ... L. Longchamps, B. Panneton, D.G. Westfall, R. Khosla

16. Precision Agriculture Initiative for Karnataka – A New Direction for Strengthening Farming Community

Strengthening agriculture is crucial to meet the myriad challenges of rural poverty, food security, unemployment, and sustainability of natural resources and it also needs strengthening at technical, financial and management levels. In this context... U.K. Shanwad, M.B. Patil, V. H, M. B.g , P. R, R. N.l. , S. S, R. Khosla, V.C. Patil

17. Developing an Integrated Rice Management System for Improved Yield and Nitrogen Use Efficiency in Northeast China

... G. Zhao, Y. Miao, F. Zhang, M. Fan

18. Spatial Econometric Approaches to Develop Site-Specific Nematode Management Strategies in Cotton Production

Root-knot nematode infestations tend to be spatially clustered within agricultural... Z. Liu, T. Griffin, T. Kirkpatrick, S. Monfort

19. In-season Diagnosis of Rice Nitrogen Status Using an Active Canopy Sensor

... Y. Yao, Y. Miao, S. Huang, M. Gnyp, R. Khosla, R. Jiang, G. Bareth

20. Performance of Two Active Canopy Sensors for Estimating Winter Wheat Nitrogen Status in North China Plain

... Q. Cao, Y. Miao, G. Feng, X. Gao, B. Liu, R. Khosla

21. AMMO Ag: Agricultural Marketing & Merchandising Optimizer

EHedger provides an integrated risk management solution for farm operations utilizing our proprietary AMMO platform combined with proven hedging strategies, first-hand market insight, effective trade execution and farming expertise. AMMO software enables real-time analysis of crop/livestock production. Farmers can set profit margins, evaluate variable profit scenarios, understand production costs and risks, and create sustainable marketing programs to maximize their... C. Krol, D. Dempsey

22. Near-Real-Time Remote Sensing And Yield Monitoring Of Biomass Crops

The demand for bioenergy crops production has increased tremendously by the biofuel industry for substitution of traditional fuels due to the economic availability and environmental benefits. Pre-Harvest monitoring of biomass production is necessary to develop optimized instrumentation and data processing systems for crop growth, health and stress monitoring; and to develop algorithms for field operation scheduling. To cope with the problems of missing critical... Y. Zhao, L. Li, K.C. Ting, L.F. Tian, T. Ahamed

23. Optimization Of Maize Yield: Relationship Between Management Zones, Hybrids And Plant Population

Corn is highly sensitive to variations in plant population and it is one of the most important practices influencing in grain yield. Knowledge about plant physiology and morphology allow understanding how the crop interacts with plant population variation. Considering that for each production system there is a population that optimizes the use of available resources it is necessary to manage plant population to reach maximum grain yield on each particular environment. This study... A.A. Anselmi, J.P. Molin, R. Khosla

24. 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 minimize... S. Shibusawa, M. Kodaira, I. Kana, S.N. Baharom

25. Study On The Automatic Monitoring Technology For Fuji Fruit Color Based On Machine Vision

  Fruit color is one of the important indicators of quality and commodities. Three kinds of the traditional methods are used to evaluate fruit color, including artificial visual identification, fruit standard color cards and color measurement instrument. These methods are needed to be conducted in the field by persons, which are time-consuming and labored, and also difficult to obtain the dynamic color information of the target fruits in the growth process. This study developed... M. Chen, M. Li, J. Qian, W. Li, Y. Wang, Y. Zhang, X. Yang

26. Design, Error Characterization And Testing Of A System To Measure Locations Of Fruits In Tree Canopies

Mapping the variability of fruit size and quality within tree canopies in commercial orchards is an important tool for implementing precision horticulture. To do so at a reasonably fast rate requires localization technologies that offer sufficient speed and accuracy, at a range long enough to cover entire trees – or several trees at a time. Existing approaches for measuring fruit locations include: manual (centimeter accuracy and measurement time in the order of minutes per... S.G. Vougioukas, F.J. Jimenez, F. Khosro anjom, R. Elkins, C. Ingels, R. Arikapudi

27. 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 normalized... Q. Cao, Y. Miao, J. Shen, S. Cheng, R. Khosla, F. Liu

28. Site-Specific Variability Of Grape Composition And Wine Quality

Precision Viticulture (PV) is the application of site-specific tools to delineate management zones in vineyards for either targeting inputs or harvesting blocks according to grape maturity status. For the creation of management zones, soil properties, topography, canopy characteristics and grape yield are commonly measured during the growing season. The majority of PV studies in winegrapes have focused on the relation of soil and vine-related spatial data with grape composition... S. Fountas, Y. Kotseridis, A. Balafoutis, E. Anastasiou, S. Koundouras, S. Kallithraka, M. Kyraleou

29. Spectral Vegetation Indices to Quantify In-field Soil Moisture Variability

Agriculture is the largest consumer of water globally. As pressure on available water resources increases, the need to exploit technology in order to produce more food with less water becomes crucial. The technological hardware requisite for precise water delivery methods such as variable rate irrigation is commercially available. Despite that, techniques to formulate a timely, accurate prescription for those systems are inadequate. Spectral vegetation indices, especially Normalized Difference... J. Siegfried, R. Khosla, L. Longchamps

30. Proximal Sensing of Leaf Temperature and Microclimatic Variables to Implement Precision Irrigation in Almond and Grape Crops

Irrigation decisions based on traditional soil moisture sensing often leads to uncertainty regarding the true amount of water available to the plant. Plant based sensing of water stress decreases this uncertainty. In specialty crops grown in California’s Central Valley, precision deficit irrigation based on plant water stress could be used to decrease water use and increase water use efficiency by supplying the necessary quantity of water only when it is needed by the plant. However, there... E. Kizer, S.K. Upadhyaya, F. Rojo, S. Ozmen, C. Ko-madden, Q. Zhang

31. Detecting Nitrogen Variability at Early Growth Stages of Wheat by Active Fluorescence and NDVI

Low efficiency in the use of nitrogen fertilizer, has been reported around the world which often times result in high production costs and environmental damage. Today, unmanned aerial vehicles (UAV) cameras are being used to obtain conditions of crops, and can cover large areas in a short time. The objectives of this study were (i) to investigate N-variability in wheat at early growth stages using induced fluorescence indices, NDVI measured by active sensor and NDVI obtained by digital imagery;... E. Patto pacheco, J. Liu, L. Longchamps, R. Khosla

32. Weather Impacts on UAV Flight Availability for Agricultural Purposes in Oklahoma

This research project analyzed 21 years of historical weather data from the Oklahoma Mesonet system.  The data examined the practicality of flying unmanned aircraft for various agricultural purposes in Oklahoma.  Fixed-wing and rotary wing (quad copter, octocopter) flight parameters were determined and their performance envelope was verified as a function of weather conditions.  The project explored Oklahoma’s Mesonet data in order to find days that are acceptable for flying... P. Weckler, C. Morris, B. Arnall, P. Alderman, J. Kidd, A. Sutherland

33. Early Detection of Nitrogen Deficiency in Corn Using High Resolution Remote Sensing and Computer Vision

The continuously growing need for increasing the production of food and reducing the degradation of water supplies, has led to the development of several precision agriculture systems over the past decade so as to meet the needs of modern societies. The present study describes a methodology for the detection and characterization of Nitrogen (N) deficiencies in corn fields. Current methods of field surveillance are either completed manually or with the assistance of satellite imaging, which offer... D. Mulla, D. Zermas, D. Kaiser, M. Bazakos, N. Papanikolopoulos, P. Stanitsas, V. Morellas

34. Climate Smart Precision Nitrogen Management

Climate Smart Agriculture (CSA) aims at improving farm productivity and profitability in a sustainable way while building resilience to climate change and mitigating the impacts of agriculture on greenhouse gas emissions. The idea behind this concept is that informed management decision can help achieve these goals. In that matter, Precision Agriculture goes hand-in-hand with CSA. The Colorado State University Laboratory of Precision Agriculture (CSU-PA) is conducting research on CSA practices... L. Longchamps, R. Khosla, R. Reich

35. Within-field Profitability Assessment: Impact of Weather, Field Management and Soils

Profitability in crop production is largely driven by crop yield, production costs and commodity prices. The objective of this study was to quantify the often substantial yet somewhat illusive impact of weather, management, and soil spatial variability on within-field profitability in corn and soybean crop production using profitability indices for profit (net return) and return-on-investment (ROI) to produce estimates. We analyzed yield and cropping system data provided by 42 farmers within Central... P.M. Kyveryga, S. Fey, J. Connor, A. Kiel, D. Muth

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

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

37. Seeding and Planting Plots for Crop Performance Evaluation Using Gps-rtk Auto Steering

Crop performance evaluation plots are seeded both on and off the University of Nebraska West Central Research and Extension Center. Plots off the Center must match the producer’s rows for pesticide application, cultivation, ditching, irrigation, fertilization and any other operations performed in the fields. With row crops the producer blank-plants the plot area before we can follow up with planting the plots. This means that we have to wait for the producer to plant in the field. Blank-planting... R.N. Klein, J.A. Golus, A.S. Cox

38. Joint Structure and Colour Based Parametric Classification of Grapevine Organs from Proximal Images Through Several Critical Phenological Stages

Proximal colour imaging is the most time and cost-effective automated technology to acquire high-resolution data describing accurately the trellising plane of grapevine. The available textural information is meaningful enough to provide altogether the assessment of additional agronomic parameters that are still estimated either manually or with dedicated and expensive instrumentations. This paper proposes a new framework for the classification of the different organs visible in the trellising... F.Y. Abdelghafour, R. Rosu, B. Keresztes, C. Germain, J. Da costa

39. Real-Time Fruit Detection Using Deep Neural Networks

Proximal imaging using tractor-mounted cameras is a simple and cost-effective method to acquire large quantities of data in orchards and vineyards. It can be used for the monitoring of vegetation and for the management of field operations such as the guidance of smart spraying systems for instance. One of the most prolific research subjects in arboriculture is fruit detection during the growing season. Estimations of fruit-load can be used for early yield assessments and for the monitoring of... B. Keresztes, J. Da costa, D. Randriamanga, C. Germain, F. Abdelghafour

40. Spatial Variability of Optimized Herbicide Mixtures and Dosages

Driven by 25 years of Danish, political 'pesticide action plans', aiming at reducing the use of pesticides, a Danish Decision Support System (DSS) for Integrated Weed Management (IWM) has been constructed. This online tool, called ‘IPMwise’ is now in its 4th generation. It integrates the 8 general IPM-principles as defined by the EU. In Denmark, this DSS includes 30 crops, 105 weeds and full assortments of herbicides. Due to generic qualities in both the integrated... P. Rydahl, R.N. Jorgensen, M. Dyrmann, N. Jensen, M.D. Sorensen, O.M. Bojer, P. Andersen

41. Environmental Impacts of Precision Feeding Programs Applied in Brazilian Pig Production

This study was undertaken to evaluate the effect that switching from conventional to precision feeding systems during the growing-finishing phase would have on the potential environmental impact of Brazilian pig production. Standard life-cycle assessment procedures were used, with a cradle-to-farm gate boundary. The inputs and outputs of each interface of the life cycle were organized in a model. Grain production was independently characterized in the Central-West and South regions of Brazil,... C. Pomar, I. Andretta, L. Hauschild, M. Kipper, P.S. Pires

42. Precision Nitrogen and Water Management for Enhancing Efficiency and Productivity in Irrigated Maize

Nitrogen and water continue to be the most limiting factors for profitable maize production in the western Great Plains. The objective of this research was to determine the most productive and efficient nitrogen and water management strategies for irrigated maize.  This study was conducted in 2016 at Colorado State University’s Agricultural Research Development and Educational Center, in Fort Collins, Colorado. The experiment included a completely randomized block design with five... E. Phillippi, R. Khosla, L. Longchamps, P. Turk

43. 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 developed... A. Meyer-aurich, Y. Karatay, M. Gandorfer

44. Synchronized Windrow Intelligent Perception System (SWIPE)

The practice of bale production, in forage agriculture, involves various machines that include tractors, tedders, rakers, and balers. As part of the baling process, silage material is placed in windrows, linearly raked mounds, to drive over with a baler for easy collection into bales. Traditionally, a baler is an implement that is attached on the back of a tractor to generate bales of a specific shape. Forage agricultural equipment manufacturers have recently released an operator driven, self-propelled... E.M. Dupont, P.R. Kolar

45. 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

46. 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

47. 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

48. Machine Learning Techniques for Early Identification of Nitrogen Variability in Maize

Characterizing and managing nutrient variability has been the focus of precision agriculture research for decades. Previous research has indicated that in-situ fluorescence sensor measurements can be used as a proxy for nitrogen (N) status in plants in greenhouse conditions employing static sensor measurements. Indeed, practitioners of precision N management require determination of in-season plant N status in real-time at field scale to enable the most efficient N fertilizer... D. Mandal, R.D. Siqueira, L. Longchamps, R. Khosla

49. Investigating Spatial Relationship of Apparent Electrical Conductivity with Turfgrass and Soil Characteristics in Sand-capped Golf Course Fairways

Turfgrass quality decreases when grown on fine textured soils that are irrigated with poor quality water. As a result, sand-capping (i.e., a sand layer above existing native soil) is now considered during golf course fairway renovation and construction. Mapping spatial variability of soil apparent electrical conductivity (ECa) has recently been suggested to have applications for precision turfgrass management (PTM) in native soil fairways, but sand-capped fairways have received less... C. Straw, B. Wyatt, A.P. Smith, K. Watkins, S. Hong, W. Floyd, D. Williams, C. Garza, T. Jansky

50. A Generative Adversarial Network-based Method for High Fidelity Synthetic Data Augmentation

Digital Agriculture has led to new phenotyping methods that use artificial intelligence and machine learning solutions on image and video data collected from lab, greenhouse, and field environments. The availability of accurately annotated image and video data remains a bottleneck for developing most machine learning and deep learning models. Typically, deep learning models require thousands of unique samples to accurately learn a given task. However, manual annotation of a large dataset will... S. Sridharan, S. Sornapudi, Q. Hu, S. Kumpatla, J. Bier

51. Enhancing Spatial Resolution of Maize Grain Yield Data

Grain yield data is frequently used for precision agriculture management purposes and as a parameter for evaluating agronomy experiments, but unexpected challenges sometimes interfere with harvest plans or cause total losses. The spatial detail of modern grain yield monitoring data is also limited by combine header width, which could be nearly 14 m in some crops.  Remote sensing data, such as multispectral imagery collected via satellite and unmanned aerial systems (UAS), could be used to... J. Siegfried, R. Khosla, D. Mandal, W. Yilma

52. Impacts of Interpolating Methods on Soil Agri-environmental Phosphorus Maps Under Corn Production

Phosphorus (P) is an essential nutrient for crops production including corn. However, the excessive P application, tends to P accumulation at the soil surface under crops systems. This may contribute to increase water and groundwater pollution by surface runoff. To prevent this, an agri-environmental P index, (P/Al)M3, was developed in Eastern Canada and USA. This index aims to estimate soil P saturation for accurate P fertilizer recommendations, while integrating agronomical aspects... J. Nze memiaghe, A.N. Cambouris, N. Ziadi, M. Duchemin, A. Karam

53. 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 the... A. Cambouris, M. Duchemin, N. Ziadi