Login

Proceedings

Find matching any: Reset
ISPA Community: Nitrogen
Precision Conservation Management
Guidence, Auto steer, and Robotics
Decision Support Systems
Applications of UAVs (unmanned aircraft vehicle systems) in precision agriculture
Add filter to result:
Authors
Abonyi, J
Adamchuk, V
Ahmed, M
Al-Adawi, S
Al-Busaidi, A
Al-Hinai, K
Al-Wardy, M
Albarenque, S.M
Amaral, L.R
Anderson, V
Archontoulis, S
Baffaut, C
Bajwa, S
Bajwa, S
Batchelor, W.D
Bazzi, C.L
Bazzi, C.L
Bazzi, C.L
Bazzi, C.L
Bazzi, C.L
Bean, G.M
Beeri, O
Belec, C
Benő, A
Betzek, N.M
Bier, V
Bouroubi, M.Y
Bouroubi, Y
Bruce, A.E
Brungardt, J.J
Callegari, D
Camberato, J.J
Campos, L.B
Carter, A
Carter, P.R
Ciampitti, I.A
Colley III, R
Coonen, J
Cox, A.S
Cugnasca, C.E
Cummings, T
Dong, R
Dorado, J
Dosskey, M
Ellingson, J.L
Esau, K
Fajardo, M
Fallon, E
Farooque, A
Ferguson, R.B
Fernandes, B.B
Fernández, F.G
Franzen, D.W
Franzen, D.W
Franzen, D.W
Franzen, D.W
Fulton, J
Gadler, D.J
Gavioli, A
Golus, J.A
Guerra, S.P
Hamm, P.B
Harnisch, W
Helmers, M
Holub, B.K
Horneck, D.A
Hunt, E
Jayasuriya, H
Jayasuriya, H.P
Johnson, D
Kaur, G
Kemerer, A.C
Khot, L
Khot, L
Kitchen, N
Kitchen, N.R
Klein, R.N
Kocsis, M
Kremer, R
Kross, A
López-Granados, F
Laboski, C.A
Lacroix, R
Lanças, K.P
Lange, A
Lapen, D
Lee, J
Lerch, R
Li, D
Liakos, V
Liang, X
Lopez-Granados, F
MARASCA, I
Magalhaes, P.G
Mangus, D
Martello, M
Masiero, F.C
May-tal, S
McLendon, A
McNairn, H
Melchiori, R.J
Miao, Y
Miao, Y
Michelon, G.K
Morgan, S.E
Mostaço, G.M
Mueller, T
Mulla, D.J
Musacchi, S
Nafziger, E.D
Neelakantan, S
Nowatzki, J
Nowatzki, J
Pagani, A
Pauly, K
Peña, J
Peña, J.M
Perry, C
Port, K
Porter, W
Prasad, V
Price, K
Puntel, L
Quaderer, J
Quirós, J.J
Ransom, C.J
Raz, J
Rocha, D
Rodrigues, F
Rojo, F
Rud, R
Rudy, H
Sadler, J
Sanches, G.M
Sankaran, S
Sawyer, J.E
Schatz, B
Schenatto, K
Schenatto, K
Schenatto, K
Schenatto, K
Schumann, A
Serra, S
Shanahan, J.F
Sharda, A
Shinde, S
Shroyer, K
Sisák, I
Sivarajan, S
Souza, E
Souza, E
Souza, E.G
Souza, I.R
Spinelli, C.B
Stamm, M.J
Sudduth, K
Sunohara, M
Szabó, K
Torres-Sánchez, J
Torres-Sanchez, J
Tremblay, N
Tremblay, N
Tucker, M
Turner, R.W
Upadhyaya, S
Valente, I.Q
Vellidis, G
Veum, K
Vigneault, P
Wang, H
Wang, X
Werkmeister, B.K
Whelan, B
Wulfsohn, D
Zaman, Q
Zamora, I
de Castro, A
de Castro, A.I
de Menezes, P.L
van Vliet, L
Topics
Decision Support Systems
Precision Conservation Management
Applications of UAVs (unmanned aircraft vehicle systems) in precision agriculture
ISPA Community: Nitrogen
Guidence, Auto steer, and Robotics
Type
Poster
Oral
Year
2018
2014
2022
2008
Home » Topics » Results

Topics

Filter results36 paper(s) found.

1. Precision Design Of Vegetative Buffers

Precision agriculture techniques can be applied at field margins to improve performance of water quality protection practices. Effectiveness of vegetative buffers, conventionally designed to have uniform width along field margins, is limited by spatially non-uniform runoff from fields. Effectiveness can be improved by placing relatively wider buffer at locations where loads are greater. A GIS tool was developed that accounts for non-uniform flow and produces more-effective, vari... T. Mueller, S. Neelakantan, M. Helmers, M. Dosskey

2. 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

3. 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

4. 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

5. 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

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

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

7. 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

8. Comparison Of Management Zones Generated By The K-Means And Fuzzy C-Means Methods

The generation of Management Zones (MZ) is an economic alternative to make viable the precision agriculture (RODRIGUES & ZIMBACK, 2002) because they work as operation units for the inputs localized application and as soil and culture sample indicators. For the field division in... E. Souza, K. Schenatto, F. Rodrigues, D. Rocha, C. Bazzi

9. The Influence Of The Interpolation Method In The Management Zones Generation

The definition of management zones (MZ) allows the concepts of precision agriculture (PA) to be used even in small producers. Methods for defining these MZ were created and are being used, obtaining satisfactory results with different crops and parameters (FLEMING & WESTFALL, 2000; ORTEGA & SANTIBÁÑEZ, 2007; MILANI et al., 2006). Through methodologies, the attributes that are influencing the productivity are selected and thematic maps are generated with the... K. Schenatto, C. Bazzi, V. Bier, E. Souza

10. Production And Conservation Results From A Decade-Long Field-Scale Precision Agriculture System

Research is needed that simultaneously evaluates production and conservation outcomes of precision agriculture practices.  From over a decade (1993-2003) of yield and soil mapping and water quality assessment, a multi-faceted, “precision agriculture system” (PAS) was developed and initiated in 2004 on a 36-ha field in Central Missouri. The PAS assessment was accomplished by comparing it to the previous decade of conventional corn-soyb... C. Baffaut, K. Sudduth, J. Sadler, R. Kremer, R. Lerch, N. Kitchen, K. Veum

11. GIS Mapping of Soil Compaction and Moisture Distribution for Precision Tillage and Irrigation Management

Soil compaction is one of the forms of physical change of soil structure which has positive and negative effects, in agriculture considered to make soil degradation. The undisciplined use of heavy load traffic or machinery in modern agriculture causes substantial soil compaction, counteracted by soil tillage that loosens the soil. Higher soil bulk densities affect resistance to root penetration, soil pore volume and permeability to air, and thus, finally the pore space habitable... H.P. Jayasuriya, M. Al-wardy, S. Al-adawi, K. Al-hinai

12. Spatial Variability Of Soil Compaction In Annual Cycle Of Different Culture Of Cane Sugar Land Clay Sandy

The assessment of soil compaction levels and choosing the best management system are very important in modern agriculture, aiming to prevent or at least restore their physical conditions to a satisfactory level. The renewal of sugar cane plantation happens on average every 5 or 6 years. The current way repeats a sequence compaction and decompaction events during successive cycles of sugarcane, which promotes breakdown of soil structure. During the harvesting and transportation, ... F.C. Masiero, B.B. Fernandes, S.P. Guerra, K.P. Lanças, I. Marasca

13. 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

14. 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

15. 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

16. 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

17. 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

18. 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

19. 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... R.N. Klein, J.A. Golus, A.S. Cox

20. Effective Use of a Debris Cleaning Brush for Mechanical Wild Blueberry Harvesting

Wild blueberries are an important horticultural crop native to northeastern North America. Management of wild blueberry fields has improved over the past decade causing increased plant density and leaf foliage. The majority of wild blueberry fields are picked mechanically using tractor mounted harvesters with 16 rotating rakes that gently comb through the plants. The extra foliage has made it more difficult for the cleaning brush to remove unwanted debris (leaf, stems, weeds, etc.) from the p... K. Esau, Q. Zaman, A. Farooque, A. Schumann

21. Three Years of On-Farm Evaluation of Dynamic Variable Rate Irrigation: What Have We Learned?

This paper will present a dynamic Variable Rate Irrigation System developed by the University of Georgia. The system consists of the EZZone management zone delineation tool, the UGA Smart Sensor Array (UGA SSA) and an irrigation scheduling decision support tool. An experiment was conducted in 2015, 2016 and 2017 in two different peanut fields to evaluate the performance of using the UGA SSA to dynamically schedule Variable Rate Irrigation (VRI). For comparison reasons strips were designed wit... V. Liakos, W. Porter, X. Liang, M. Tucker, A. Mclendon, C. Perry, G. Vellidis

22. Reverse Modelling of Yield-Influencing Soil Variables in Case of Few Soil Data

Our hypothesis was that simple models can be applied to predict yield by using only those yield data which spatially coincide with the soil data and the remaining yield data and the models can be used to test different sampling and interpolation approaches commonly applied in precision agriculture and to better predict soil variables at not observed locations. Three strategies for composite sample collection were compared in our study. Point samples were taken 1.) along lines within homogenou... I. Sisák, A. Benő, K. Szabó, M. Kocsis, J. Abonyi

23. Optimized Soil Sampling Location in Management Zones Based on Apparent Electrical Conductivity and Landscape Attributes

One of the limiting factors to characterize the soil spatial variability is the need for a dense soil sampling, which prevents the mapping due to the high demand of time and costs. A technique that minimizes the number of samples needed is the use of maps that have prior information on the spatial variability of the soil, allowing the identification of representative sampling points in the field. Management Zones (MZs), a sub-area delineated in the field, where there is relative homogeneity i... G.K. Michelon, G.M. Sanches, I.Q. Valente, C.L. Bazzi, P.L. De menezes, L.R. Amaral, P.G. Magalhaes

24. Optimal Placement of Proximal Sensors for Precision Irrigation in Tree Crops

In agriculture, use of sensors and controllers to apply only the quantity of water required, where and when it is needed (i.e., precision irrigation), is growing in importance. The goal of this study was to generate relatively homogeneous management zones and determine optimal placement of just a few sensors within each management zone so that reliable estimation of plant water status could be obtained to implement precision irrigation in a 2.0 ha almond orchard located in California, USA. Fi... C.L. Bazzi, K. Schenatto, S. Upadhyaya, F. Rojo

25. Prediction of Corn Economic Optimum Nitrogen Rate in Argentina

Static (i.e. texture and soil depth) and dynamic (i.e. soil water, temperature) factors play a role in determining field or subfield economically optimal N rates (EONR). We used 50 nitrogen (N) trials from Argentina at contrasting landscape positions and soil types, various soil-crop measurements from 2012 to 2017, and statistical techniques to address the following objectives: a) characterize corn yield and EONR variability across a multi-landscape-year study in central west Buenos Aire... L. Puntel, A. Pagani, S. Archontoulis

26. Field Test of a Satellite-Based Model for Irrigation Scheduling in Cotton

Cotton irrigation in Israel began in the mid-1950s. It is based on an irrigation protocol developed over dozens of years of cotton farming in Israel, and proved to provide among the world's best cotton yield results. In this experiment, we examined the use of an irrigation recommendation system that is based on satellite imagery and hyper-local meteorological data, "Manna treatment", compared to the common irrigation protocols in Israel, which use a crop coefficient (Kc) table a... O. Beeri, S. May-tal, J. Raz, R. Rud

27. Variable Selection and Data Clustering Methods for Agricultural Management Zones Delineation

Delineation of agricultural management zones (MZs) is the delimitation, within a field, of a number of sub-areas with high internal similarity in the topographic, soil and/or crop characteristics. This approach can contribute significantly to enable precision agriculture (PA) benefits for a larger number of producers, mainly due to the possibility of reducing costs related to the field management. Two fundamental tasks for the delineation of MZs are the variable selection and the cluster anal... A. Gavioli, E.G. Souza, C.L. Bazzi, N.M. Betzek, K. Schenatto

28. Field Grown Apple Nursery Tree Plant Counting Based on Small UAS Imagery Derived Elevation Maps

In recent years, growers in the state are transitioning to new high yielding, pest and disease resistant cultivars. Such transition has created high demand for new tree fruit cultivars. Nursery growers have committed their incoming production of the next few years to meet such high demands. Though an opportunity, tree fruit nursery growers must grow and keep the pre-sold quantity of plants to supply the amount promised to the customers. Moreover, to keep the production economical amidst risin... M. Martello, J.J. Quirós, L. Khot

29. Optimising Nitrogen Use in Cereal Crops Using Site-Specific Management Classes and Crop Reflectance Sensors

The relative cost of Nitrogen (N) fertilisers in a cropping input budget, the 33% Nitrogen use efficiency (NUE) seen in global cereal grain production and the potential environmental costs of over-application are leading to changes in the application rates and timing of N fertiliser. Precision agriculture (PA) provides tools for producers to achieve greater synchrony between N supply and crop N demand. To help achieve these goals this research has explored the use of management classes derive... B. Whelan, M. Fajardo

30. AgronomoBot: A Smart Answering Chatbot Applied to Agricultural Sensor Networks

Mobile devices advanced adoption has fostered the creation of various messaging applications providing convenience and practicality in general communication. In this sense, new technologies arise bringing automatic, continuous and intelligent features for communication through messaging applications by using web robots, also called Chatbots. Those are computer programs that simulate a real conversation between humans to answer questions or do tasks, giving the impression that the person is ta... G.M. Mostaço, L.B. Campos, C.E. Cugnasca, I.R. Souza

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

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

32. Spatial Decision Support System: Controlled Tile Drainage – Calculate Your Benefits

Climate projection studies suggest that extreme heat waves and floods will become more frequent, affecting future crop yields by 20%-30%, globally. Managing vulnerability and risk begins at the farm level where best management practices can reduce the impacts associated with extreme weather events. A practice that can assist in mitigating the impact of some extreme events is controlled tile drainage (CTD). With CTD, producers use water flow control structures to manage the drainage of water f... A. Kross, G. Kaur, D. Callegari, D. Lapen, M. Sunohara, H. Mcnairn, H. Rudy, L. Van vliet

33. Precision Irrigation Management Through Conjunctive Use of Treated Wastewater and Groundwater in Oman

Agriculture under arid environment is always become a challenge due to water scarcity and salinity problems.  With average rainfall of 100 mm, agriculture in Oman is limited due to the arid climate and limited arable lands. More than 50 percent of the arable lands are located in the 300 km northern coastal belt of Al-Batinah region. In addition, country is facing severe problem of sea water intrusion into the groundwater aquifers due to undisciplined excessive groundwater (GW) abstractio... H. Jayasuriya, A. Al-busaidi, M. Ahmed

34. Overview and Value of Digital Technologies for North American Soybean Producers

In the current state of digital agriculture, many digital technologies and services are offered to assist North American soybean producers.  Opportunities for capturing and analyzing information related to soybean production methods are made available through the adoption of these technologies.  However, often it is difficult for producers to know which digital tools and services are available to them or understand the value they can provide.  The objective of th... J. Lee, J. Fulton, K. Port, R. Colley iii

35. Development of an Online Decision-Support Infrastructure for Optimized Fertilizer Management

Determination of an optimum fertilizer application rate involves various influential factors, such as past management, soil characteristics, weather, commodity prices, cost of input materials and risk preference. Spatial and temporal variations in these factors constitute sources of uncertainties in selecting the most profitableapplication rate. Therefore, a decision support system (DSS) that could help to minimize production risks in the context of uncertain crop performance is needed. ... S. Shinde, V. Adamchuk, R. Lacroix, N. Tremblay, Y. Bouroubi

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

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