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Reynolds, D.B
Johnson, D
Gimenez, L.M
Bui, M
Jonjak, A.K
Xu, K
Rydberg, A
Rydahl, P
Camberato, J
Cruse, R
Lepoivre, B
Jiang, J
Leese, S
Yore, A
Gritten, F
Johnson, R.M
Abbas, F
Krishnaswamy, K
Brorsen, B.W
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Authors
Viator, R.P
Johnson, R.M
Bernardi, A.C
Gimenez, L.M
Silva, C.A
Machado, P.L
Price, R
Johnson, R.M
Viator, R.P
Jonjak, A.K
Adamchuk, V.I
Wortmann, C.S
Shapiro, C.A
Fergugson, R.B
Sundström, B
Åström, H
Rydberg, A
Olsson, J
Jacquin, A
Sigel, G
Hagolle, O
Lepoivre, B
Roumiguié, A
Poilvé, H
Zhang, X
Li, Y
Xu, K
Sun, X
Khot, L
Sankaran, S
Johnson, D
Carter, A
Serra, S
Musacchi, S
Cummings, T
Destain, M
Leemans, V
Marlier, G
Goffart, J
Bodson, B
Mercatoris, B
Gritten, F
Prince Czarnecki, J.M
Reynolds, D.B
Moorhead, R.J
Bean, G
Kitchen, N.R
Franzen, D.W
Miles, R.J
Ransom, C
Scharf, P
Camberato, J
Carter, P
Ferguson, R.B
Fernandez, F.G
Laboski, C
Nafziger, E
Sawyer, J
Shanahan, J
Gelder, B.K
Cruse, R
James, D
Herzmann, D
Sandoval-Green, C
Sklenar, T
Cho, W
Kim, D
Kang, C
Kim, H
Son, J
Chung, S
Jiang, J
Yun, H
Brockgreitens, J
Bui, M
Abbas, A
Mulla, D
Johnson, R.M
Grisham, M.P
Roberts, D.C
Brorsen, B.W
Raun, W.R
Solie, J.B
Rydahl, P
Jorgensen, R.N
Dyrmann, M
Jensen, N
Sorensen, M.D
Bojer, O.M
Andersen, P
Price, R.R
Johnson, R.M
Viator, R.P
Taylor, J
Shahar, Y
James, P
Blacker, C
Leese, S
Sanderson, R
Kavanagh, R
Rydahl, P
Boejer, O
Torresen, K
Montull, J.M
Taberner, A
Bückmann, H
Verschwele, A
Rydahl, P
Boejer, O
Jensen, N
Hartmann, B
Jorgensen, R
Soerensen, M
Andersen, P
Paz, L
Nielsen, M.B
Esau, T.J
Farooque, A.A
Abbas, F
Johnson, R.M
Ramachandran, B
Cheema, S.J
Farooque, A.A
Abbas, F
Esau, T
Grewal, K
Khan, H
Esau, T
Farooque, A
Abbas, F
Lee, J
song, S
Oh, S
Krishnaswamy, K
Sun, C
Adu-Gyamfi, Y
Yore, A
Lanza, P
Longchamps, L
Topics
Spatial Variability in Crop, Soil and Natural Resources
Precision A-Z for Practitioners
Engineering Technologies and Advances
Spatial Variability in Crop, Soil and Natural Resources
Profitability, Sustainability and Adoption
Sensor Application in Managing In-season CropVariability
Precision Nutrient Management
Applications of UAVs (unmanned aircraft vehicle systems) in precision agriculture
Proximal Sensing in Precision Agriculture
Unmanned Aerial Systems
Precision Nutrient Management
Precision Conservation Management
Engineering Technologies and Advances
Spatial Variability in Crop, Soil and Natural Resources
Remote Sensing for Nitrogen Management
Precision Crop Protection
Geospatial Data
Decision Support Systems
Precision Crop Protection
Precision Horticulture
Applications of Unmanned Aerial Systems
Drainage Optimization and Variable Rate Irrigation
Precision Agriculture and Global Food Security
In-Season Nitrogen Management
Type
Poster
Oral
Year
2012
2010
2014
2016
2008
2018
2022
2024
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Filter results27 paper(s) found.

1. Variable Rate Application Of Potassium Fertilizer For Soybean Crop Growth In A No-till System

Variable rate application of fertilizer has the potential to improve nutrient use efficiency, improve economic returns, and reduce negative environmental impacts. The objective of this study was to evaluate the variable rate application of potassium fertilizer to soybean crop in a no-till system. The study was conducted on a 13-ha soybean grain field in Carambeí, State of Paraná, Brazil in a Typic Hapludox. The area has been under no-tillage for more than 10 years growing grains... A.C. Bernardi, L.M. Gimenez, C.A. Silva, P.L. Machado

2. Optical Based Sugarcane Yield Monitors

Several different optical sensors were investigated to detect sugarcane yield on a billet type sugarcane harvester. These sensors included an over-head optical sensor and a below-the-conveyor sensor. Both sensors indicated mass flow rate from a volume measurement of the cane on the conveyor slats. Both systems gave good results with linear line calibration equations and adjusted R-square values from 0.96 to 0.97. Weight wagon weights in the 0.6 to 1.6 metric ton range were estimated to 7.5% on... R. Price, R.M. Johnson, R.P. Viator

3. A Comparison Of Conventional And Sensor-based Lime Requirement Maps

Successful variable-rate applications of agricultural inputs, such as lime, rely on quality of input data. Systematic soil sampling is... A.K. Jonjak, V.I. Adamchuk, C.S. Wortmann, C.A. Shapiro, R.B. Fergugson

4. Spatial Variability of Sugarcane Yields in Relation to Soil Salinity in Louisiana

High soil salinity levels have been documented to negatively impact sugarcane yields.  Tests were conducted in commercial sugarcane fields in South Louisiana in 2009-2010 to determine if elevated soil salinity levels... R.P. Viator, R.M. Johnson

5. Sustainable Grain Production With Continuous Improvements And Lean Production

Few farmers are dedicated to critically examine their production processes. When something needs to be improved, the focus is on production with a concentration on the biological. But the profitability of a company is created by the production (what I do) and organization (how I do it). Agricultural advisory services are well developed in Sweden with services related to biological production (crop production planning, soil mapping, etc.) but there are no corresponding activities... B. Sundström, H. Åström, A. Rydberg, J. Olsson

6. 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 as... A. Jacquin, G. Sigel, O. Hagolle, B. Lepoivre, A. Roumiguié, H. Poilvé

7. Research On Measurement Device For NO3- Ion Concentration Of Nutrient Solution

The management of water and ion concentration in nutrient solution is crucial in precision agriculture. Poor management may leads to the increasing of energy consumption and cost as well as low efficiency. The measurement of ion concentration in nutrient solution is prerequisite for optimal control and management of nutrient solution. Real-time detection of NO3-, as an important component of nitrogenous fertilizer, is always a big problem over the world. The... X. Zhang, Y. Li, K. Xu, X. Sun

8. 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 application,... L. Khot, S. Sankaran, D. Johnson, A. Carter, S. Serra, S. Musacchi, T. Cummings

9. 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

10. Use of Unmanned Aerial Vehicles to Inform Herbicide Drift Analysis

A primary advantage of unmanned aerial vehicle-based imaging systems is responsiveness.  Herbicide drift events require prompt attention from a flexible collection system, making unmanned aerial vehicles a good option for drift analysis.  In April 2015, a drift event was documented on a Mississippi farm.  A combination of corn and rice fields exhibited symptomology consist with non-target injury from a tank mix of glyphosate and clethodim.  An interesting observation was the... J.M. Prince czarnecki, D.B. Reynolds, R.J. Moorhead

11. Modifying the University of Missouri Corn Canopy Sensor Algorithm Using Soil and Weather Information

Corn production across the U.S. Corn belt can be often limited by the loss of nitrogen (N) due to leaching, volatilization and denitrification. The use of canopy sensors for making in-season N fertilizer applications has been proven effective in matching plant N requirements with periods of rapid N uptake (V7-V11), reducing the amount of N lost to these processes. However, N recommendation algorithms used in conjunction with canopy sensor measurements have not proven accurate in making N recommendations... G. Bean, N.R. Kitchen, D.W. Franzen, R.J. Miles, C. Ransom, P. Scharf, J. Camberato, P. Carter, R.B. Ferguson, F. Fernandez, C. Laboski, E. Nafziger, J. Sawyer, J. Shanahan

12. The Daily Erosion Project - High Resolution, Daily Estimates of Runoff, Detachment, Erosion, and Soil Moisture

Runoff and sediment transport from agricultural uplands are substantial threats to water quality and sustained crop production. Farmers, conservationists, and policy makers must understand how landforms, soil types, farming practices, and rainfall affect soil erosion and runoff in order to improve management of soil and water resources. A system was designed and implemented a decade ago to inventory precipitation, runoff, and soil erosion across the state of Iowa, United States. That system utilized... B.K. Gelder, R. Cruse, D. James, D. Herzmann, C. Sandoval-green, T. Sklenar

13. Precision Nutrient Management System Based on Ion and Crop Growth Sensing

Automated sensing and variable-rate supply of nutrients in hydroponic solutions according to the status of crop growth would allow more efficient nutrient management for crop growth in closed systems. The Structure from Motion (SfM) method has risen as a new image sensing method to obtain 3D images of plants that can be used to estimate their growth, such as leaf cover area (LCA), plant height, and fresh weight. In this sense, sensor fusion technology combining ion-selective electrodes (ISEs)... W. Cho, D. Kim, C. Kang, H. Kim, J. Son, S. Chung, J. Jiang, H. Yun

14. Field Sampling and Electrochemical Detection of Nitrate in Agricultural Soils

Nitrate is an essential plant nutrient and is added to farm fields to increase crop yields. While the addition of nitrate is important for production, over-fertilization with nitrate can lead to leaching and contamination of water bodies. Increased nitrate loading in water sources then leads to eutrophication and hypoxia in downstream regions. Many efforts are being made to accurately control nitrate fertilizer additions to fields. Here, we present a soil sampling device that directly samples... J. Brockgreitens, M. Bui, A. Abbas, D. Mulla

15. Assessing the Variability of Red Stripe Disease in Louisiana Sugarcane Using Precision Agriculture Methods

Symptoms of red stripe disease caused by Acidovorax avenae subsp. avenae in Louisiana between 1985 and 2010 were limited to the leaf stripe form which caused no apparent yield loss.  During 2010, the more severe top rot form was observed, and a study was initiated to investigate the distribution of red stripe in the field and determine its effects on cane and sugar yields. Two fields of cultivar HoCP 00-950, one plant-cane (PC) crop and one first-ratoon (FR) crop, affected by top rot were... R.M. Johnson, M.P. Grisham

16. Prediction of Nitrogen Needs with Nitrogen-rich Strips and Ramped Nitrogen Strips

Both nitrogen rich strips and ramped nitrogen strips have been used to estimate topdress nitrogen needs for winter wheat based on in-season optical reflectance data. The ramped strip system places a series of small plots in each field with increasing levels of nitrogen to determine the application rate at which predicted yield response to nitrogen reaches a plateau. The nitrogen-rich strip system uses a nitrogen fertilizer optimization algorithm based on optical reflectance measures from the nitrogen-rich... D.C. Roberts, B.W. Brorsen, W.R. Raun, J.B. Solie

17. 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

18. Development of an Overhead Optical Yield Monitor for a Sugarcane Harvester in Louisiana

A yield monitor is a device used to measure harvested crop weight per unit area for a specific location within a field.  The device documents yield variability in harvested fields and ultimately can be used to create a geographical-referenced yield map. Yield maps can be used to identify low yielding areas where poor soil fertility, disease, or pests may adversely affect yield.  Management practices can then be adjusted to correct these issues, resulting in an increase in yields and... R.R. Price, R.M. Johnson, R.P. Viator

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

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

20. Economic Potential of IPMwise – a Generic Decision Support System for Integrated Weed Management in 4 Countries

Reducing use and dependency on pesticides in Denmark has been driven by political action plans since the 1980ies, and a series of nationally funded accompanying R&D programs were completed in the period 1989-2006. One result of these programs was a decision support system (DSS) for integrated weed management. The 4th generation (2016) of the agro-biological models and IT-tools in this DSS, named IPMwise. The concept of IPMwise is to systematically exploit that: occurrence... P. Rydahl, O. Boejer, K. Torresen, J.M. Montull, A. Taberner, H. Bückmann, A. Verschwele

21. 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

22. Temperature Effect on Wild Blueberry Fruit Quality During Mechanical Harvest

Mechanical harvesters, utilizing a range of technologies, have been developed for timely operations and remain the most cost-effective means of picking the wild blueberry crop. Approximately 95% of wild blueberries in Atlantic Canada are immediately frozen and processed, while only a small percentage is sold in the fresh market. However, the producers can benefit by increasing the value of their harvested crop through fresh market sales. The objective of this study was to determine the optimum... T.J. Esau, A.A. Farooque, F. Abbas

23. Utilization of UASs to Predict Sugarcane Yields in Louisiana Prior to Harvest

One of the most difficult tasks that both sugarcane producers and processors face every year is estimating the yields of sugarcane fields prior to the start of harvest. This information is needed by processors to determine when the harvest season is to be initiated each year and by producers to decide when each field should be harvested. This is particularly important in Louisiana because the end of the harvest season is often affected by freeze events. These events can severely damage the crop... R.M. Johnson, B. Ramachandran

24. Establishing the First Soil Water Characteristics Curve for the Soils of Prince Edward Island, Canada

Soil water characteristics curve (SWCC), for Prince Edward Island (PEI), is much more needed currently for the sustainable production of agriculture yields. It will not only fulfil the requirements of the province’s farmers for irrigation scheduling but also help the government to decide about permitting the use of groundwater for supplemental irrigation on the island.  A soil water characteristics curve in PEI does not exist to support precision agriculture practices. Precision irrigation... S.J. Cheema, A.A. Farooque, F. Abbas, T. Esau, K. Grewal

25. Suitability of ML Algorithms to Predict Wild Blueberry Harvesting Losses

The production of wild blueberries (Vaccinium angustifolium.) is contributing 112.2 million dollars to the Canada’s revenue which can be further increased through controlling harvest losses. A precise prediction of blueberry harvesting losses is necessary to mitigate such losses. In this study, the performance of three machine learning (ML) models was evaluated to predict the wild blueberry harvest losses on the ground. The data from four commercial fields in Atlantic Canada were... H. Khan, T. Esau, A. Farooque, F. Abbas

26. Smart Food Oases: Development of a Distributed Point-to-point Urban Food Ecosystem in Food Desert Areas

Urban agriculture has been getting much attention in the past decade as a solution to overcome food insecurity and accessibility of food for urban residents and to have better green environments in cities. Urban agriculture is expected to provide better nutrients to residents, reduce transportation and environmental costs, and help urban dwellers access food efficiently. The present study is to build a collaborative ecosystem among urban growers/producers and create bridges from these farmers... J. Lee, S. Song, S. Oh, K. Krishnaswamy, C. Sun, Y. Adu-gyamfi

27. Using Dynamic Crop Growth Data to Assess Early Season N Status in Maize

Nitrogen (N) is perhaps the most important mineral nutrient determining crop growth and yield. Fertilizer sources can vary, but it is used in practically all cropping systems, and accounts for one of the highest input costs. Farmers often overapply N to their fields as a simple "insurance policy" to guarantee maximum yields. This can be problematic due to the volatile nature of N in the environment, as well reducing potential profits by not optimizing the rates. There... A. Yore, P. Lanza, L. Longchamps