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Goswami, S
Lefsrud, M
Bernardi, A.C
Ramos-Tanchez, J
Krueger Shvetsova, E
Tuttle, G
Shrestha, R
Da Silva, M.L
Cardon, G.E
Olsen, D.R
Boatswain Jacques, A.A
Dukes, M
Rossi Neto, J
Srinivasagan, S
Burns, D
Sun, X
Seger, J
Jansen, M
Pawar, S.N
Souza, W.J
Raitz Persch, J
Sampath, N
Oliveira, L.P
Price, K
Postelmans, A
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Authors
Burns, D
Overstreet, D
Kruse, D
Frazier, R
Blanche, D
Goswami, S
Saha, S
Pawar, S.N
Gore, A.K
Shinde, G.U
Pendke, M.S
Zhang, X
Streeter, C.R
Kim, H
Olsen, D.R
Krueger Shvetsova, E
Kurtener, D
Kurtener, D
Torbert, H
Amakor, X
Jacobson, A.R
Cardon, G.E
Hawks, A
Barnes, W
Parajulee, M
Neupane, D
Wang, C
Carroll, S
Shrestha, R
Borghi, E
Luchiari Junior, A
Bortolon, L
Bortolon, E.S
Inamasu, R.Y
Bernardi, A.C
Avanzi, J.C
Fragalle, C.V
Silva, J.C
Fragalle, E.P
Inamasu, R.Y
Bernardi, A.C
Bernardi, A.C
Inamasu, R.Y
Bernardi, A.C
Kolln, O.T
Sanches, G.M
Rossi Neto, J
Castro, S.G
Mariano, E
Otto, R
Inamasu, R
Magalhães, P.S
Braunbeck, O.A
Franco, H.C
Zhang, X
Li, Y
Xu, K
Sun, X
Ciampitti, I.A
Shroyer, K
Prasad, V
Sharda, A
Stamm, M.J
Wang, H
Price, K
Mangus, D
Paulus, S
Dornbusch, T
Jansen, M
Morris, T
Tremblay, N
Kyveryga, P.M
Clay, D.E
Murrell, S
Ciampitti, I
Thompson, L
Mueller, D
Seger, J
Maja, J.M
Blocker, A.K
Stuckey, E.G
Sell, S.G
Tuttle, G
Mueller, J
Andrae, J
Dukes, M
Zamora, M
Rowland, D
Tikasz, P
Buelvas, R.M
Lefsrud, M
Adamchuk, V
Boatswain Jacques, A.A
Adamchuk, V.I
Cloutier, G
Clark, J.J
Miller, C
Tsibart, A
Postelmans, A
Dillen, J
Elsen, A
Van de Ven, G
Saeys, W
Oliveira, M.F
Carneiro, F.M
Thurmond, M
del Val, M.D
Oliveira, L.P
Ortiz, B
Sanz-Saez, A
Tedesco, D
Xiong, X
Myers, D
DeBruin, J
Gunzenhauser, B
Sampath, N
Ye, D
Underwood, H
Hensley, R
Da Silva, M.L
Alves de Lima, J.
Balbinot, A
Molin, J.P
Souza, W.J
Silva, A.N
Boatswain Jacques, A.A
Diallo, A.B
Cambouris, A
Lord, E
Fallon, E
Lord, E
Boatswain Jacques, A.A
Diallo, A.B
Khakbazan, M
Cambouris, A
Apolinário, E
Souza, W.J
Raitz Persch, J
Harsha Chepally, R
Piya, N.K
Marcaida, M
Zhang, X
Srinivasagan, S
Shajahan, S
Ketterings, Q
Srinivasagan, S
Ketterings, Q
Marcaida, M
Shajahan, S
Ramos-Tanchez, J
Cho, J
Thompson, L
Guinness, J
Goel, R
Topics
Profitability, Sustainability and Adoption
Precision Nutrient Management
Emerging Issues in Precision Agriculture (Energy, Biofuels, Climate Change)
Remote Sensing Applications in Precision Agriculture
Modeling and Geo-statistics
Precision Nutrient Management
Profitability, Sustainability and Adoption
Precision Dairy and Livestock Management
Precision Nutrient Management
Applications of UAVs (unmanned aircraft vehicle systems) in precision agriculture
Remote Sensing Applications in Precision Agriculture
Standards & Data Stewardship
Farm Animals Health and Welfare Monitoring
Drainage Optimization and Variable Rate Irrigation
Precision Horticulture
Robotics, Guidance and Automation
Site-Specific Nutrient, Lime and Seed Management
Big Data, Data Mining and Deep Learning
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Data Analytics for Production Ag
Geospatial Data
Artificial Intelligence (AI) in Agriculture
Big Data, Data Mining and Deep Learning
Robotics and Automation with Row and Horticultural Crops
Drivers and Barriers to Adoption of Precision Ag Technologies or Digital Agriculture
Type
Poster
Oral
Year
2012
2010
2014
2016
2018
2022
2024
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Filter results31 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. Evaluation Of Yield Maps Using Fuzzy Indicators

  The ultimate goal of application of yield maps is profitable crop output in many farming systems. Yield maps are the starting point in the precision farming system, and provide the final record indicating the effectiveness of any management changes. Researches on yield mapping shown, that positions and boundaries of zones with different levels of... E. Krueger shvetsova, D. Kurtener, D. Kurtener, H. Torbert

3. Apparent Electrical Conductivity Calibration In Semiarid Soils: Ion-pair Correction

The electromagnetic induction sensor (EM38DD) is a field proven portable sensor for rapid measurement of the apparent electrical conductivity (ECa) of soils. Calibration with the electrical conductivity of saturation paste extracts is the most widely used method to correlate ECa with the effective electrical conductivity (ECe). A drawback of this method is the formation of ion pairs in the high ionic strength saturated paste extracts, which effectively decreases the measured ECe, leading to the... X. Amakor, A.R. Jacobson, G.E. Cardon, A. Hawks, W. Barnes

4. Effect Of Nitrogen Application Rate On Soil Residual N And Cotton Yield

A long-term study was conducted on nitrogen application rate and its impact on soil residual nitrogen and cotton (FM960B2RF) lint yield under a drip irrigation production system near Plainview, Texas. The experiment was a randomized complete block design with five nitrogen application rates (0, 56, 112, 168 and 224 kg per ha) and five replications. The soil nitrogen treatment was applied as side dressing. Cotton yield, leaf N, seed N, soil residual nitrate, amount of irrigation, and rainfall data... M. Parajulee, D. Neupane, C. Wang, S. Carroll, R. Shrestha

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

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

6. Effect of Urea Application through Drip Irrigation on Yield, Water and Nitrogen Use Efficiency of Summer Bitter Gourd

Bitter gourd (Momordica charantia L.) is one of the important vegetable crops grown during summer months in high lands of Lower Gangetic Plains.  Crop is very much responsive to water and nutrient but water is limiting in dry summer months.  Farmers generally adopt furrow irrigation and hand watering with pitcher for growing this crop.  Drip irrigation is... S. Goswami, S. Saha

7. Climatological Diagnostic Analysis: A Case Study for Parbhani District in Marathwada Region of India

... S.N. Pawar, A.K. Gore, G.U. Shinde, M.S. Pendke

8. Adoption Level Of Precision Agriculture For Brazilian Farmers - 2011/12 Crop Year

Although Precision Agriculture (PA) concepts and technologies are widespread in Brazil, its application still little used in some important crop production regions. The purpose of this study was to survey the current adoption level of PA by printed and online questionnaire. We started making a specific questionnaire to farmers and PA service companies using some technology related to PA. The questionnaires were developed based on the methodology of Whipker and Akridge (2009),... E. Borghi, A. Luchiari junior, L. Bortolon, E.S. Bortolon, R.Y. Inamasu, A.C. Bernardi, J.C. Avanzi

9. Strategies For Scientific Communication Of Precision Agriculture In Brazil

Scientific knowledge popularization is the way to the society access technical scientific advances. The challenge is to increase the means, channels and processes of information and relationship with society and decode scientific issues into a format that makes knowledge accessible. The Embrapa Precision Agriculture Network has been used scientific communication strategies at the traditional and new media, as a way of approach with various stakeholders, contributing to the construction... C.V. fragalle, J.C. Silva, E.P. fragalle, R.Y. Inamasu, A.C. Bernardi

10. Spatial Variability Of Soil Properties And Yield Of An Alfalfa Pasture Under Grazing In Brazil

Alfalfa is extremely demanding in fertility, and an adequate supply of nutrients is important for forage production and is essential to maintain high forage quality and profitable yields. Tropical acid soils are naturally poor in plant nutrients, therefore, soil liming and balanced nutrient supply essential to ensure high yields and high alfalfa forage quality. The knowledge of soil properties spatial variability and forage yield is useful for the rational use of inputs, as in the variable... A. Bernardi

11. Precision Agriculture Use In Selected Agricultural Regions In Brazil

Investment in technology brought Brazil to the position among the top agricultural producers in the world. Brazilian agricultural production has increased drastically as a result of productivity growth instead expansion in area. In this scenario the use of Precision Agriculture (PA) in the farm management, considering the spatial variability for maximizing economic return and minimizing the risk of damage to the environment can be decisive. However, the adoption of PA by Brazilian... R.Y. Inamasu, A.C. Bernardi

12. Optical Sensors To Predict Nitrogen Demand By Sugarcane

The low effectiveness of nitrogen (N) from fertilizer is a substantial concern in worldwide which has been threatening the sustainability of sugarcane production. The increment of nitrogen use efficiency (NUE) by sugarcane genotypes associated to the best practices of fertilizer management and nutritional diagnosis methods have higher potential to reduce environment impacts of nitrogen fertilization. Due to the difficult to determine N status in soil test as well as there is not... O.T. Kolln, G.M. Sanches, J. Rossi neto, S.G. Castro, E. Mariano, R. Otto, R. Inamasu, P.S. Magalhães, O.A. Braunbeck, H.C. Franco

13. 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

14. 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

15. Intuitive Image Analysing on Plant Data - High Throughput Plant Analysis with Lemnatec Image Processing

For digital plant phenotyping huge amounts of 2D images are acquired. This is known as one part of the phenotyping bottleneck. This bottleneck can be addressed by well-educated plant analysts, huge experience and an adapted analysis software. Automated tools that only cover specific parts of this analysis pipeline are provided. During the last years this could be changed by the image processing toolbox of LemnaTec GmbH. An automated and intuitive tool for the automated analysis of huge amounts... S. Paulus, T. Dornbusch, M. Jansen

16. Rationale for and Benefits of a Community for On-Farm Data Sharing

Most data sets for evaluating crop production practices have too few locations and years to create reliable probabilities from predictive analytical analyses for the success of the practices. Yield monitors on combines have the potential to enable networks of farmers in collaboration with scientists and farm advisors to collect sufficient data for calculation of more reliable guidelines for crop production showing the probabilities that new or existing practices will improve the efficiency of... T. Morris, N. Tremblay, P.M. Kyveryga, D.E. Clay, S. Murrell, I. Ciampitti, L. Thompson, D. Mueller, J. Seger

17. Development of a Small Tracking Device for Cattle Using IoT Technology

The US is the largest producer of beef in the world. Last year alone, it produces nearly 19% of the world’s beef.  This translate to about almost $90 billion in economic impact in the country. Aside from being a producer, the US also consumed more than 26 billion pounds of beef which have a retail value of the entire beef industry to more than $74B. For this level of production and consumption, each rancher in the US must produce a herd size of at least 100 or more to sustain the current... J.M. Maja, A.K. Blocker, E.G. Stuckey, S.G. Sell, G. Tuttle, J. Mueller, J. Andrae

18. Effect of Irrigation Scheduling Technique and Fertility Level on Corn Yield and Nitrogen Movement

Florida has more first magnitude springs that anywhere in the world. Most of these are located in north Florida where agricultural production is the primary basis for the economy. Irrigated corn has become a popular part of the crop rotation in recent years. This project is a study of a corn and peanut rotation investigating Best Management Practices (BMPs) of nitrogen fertility level (336, 246, 157 kg/ha) and irrigation strategies as follows:  (i) GROW, mimicking grower’s practices,... M. Dukes, M. Zamora, D. Rowland

19. Implementation of a CAN Bus System to Monitor Hydroponic Systems

Controlled Area Network (CAN) bus systems designed for greenhouse monitoring have been proposed to measure soil moisture content, yet they are still absent from hydroponic systems. In this study, irrigation control, monitoring of substrate moisture levels and temperature were achieved using a CAN bus system connected to hydroponic beds. In total, five nodes were mounted on five hydroponic beds and two irrigation methods were compared on lettuce and kale: first, where a pre-set timer activated... P. Tikasz, R.M. Buelvas, M. Lefsrud, V. Adamchuk

20. Development of a Machine Vision Yield Monitor for Shallot Onion Harvesters

Crop yield estimation and mapping are important tools that can help growers efficiently use their available resources and have access to detailed representations of their farm. Technical advancements in computer vision have improved the detection, quality assessment and yield estimation processes for crops, including apples, citrus, mangoes, maize, figs and many other fruits. However, similar methods capable of exporting a detailed yield map for vegetable crops have not yet been fully developed.... A.A. Boatswain jacques, V.I. Adamchuk, G. Cloutier, J.J. Clark, C. Miller

21. Should We Increase or Decrease the Fertilization in the Zones with the Highest Crop Productivity Potential?

Introduction. In traditional farming, fertilizers are applied homogeneously on the agricultural fields taking into account the average crop recommendation. As most fields are not homogeneous, this results in overfertilization of certain zones and underfertilization of other zones. The excess of nitrate leaches to the surface and groundwaters which causes problems with the water quality. Precision fertilizer management has been proposed to reduce these negative effects.... A. Tsibart, A. Postelmans, J. Dillen, A. Elsen, G. Van de ven, W. Saeys

22. Predicting Below and Above Ground Peanut Biomass and Maturity Using Multi-target Regression

Peanut growth and maturity prediction can help farmers and breeding programs improving crop management. Remote sensing images collected by satellites and drones make possible and accurate crop monitoring. Today, empirical relations between crop biomass and spectral reflectance could be used for prediction of single variables such as aboveground crop biomass, pod weight (PW), or peanut maturity. Robust algorithms such as multioutput regression (MTR) implemented through multioutput random forest... M.F. Oliveira, F.M. Carneiro, M. Thurmond, M.D. Del val, L.P. Oliveira, B. Ortiz, A. Sanz-saez, D. Tedesco

23. Functional Soil Property Mapping with Electrical Conductivity, Spectral and Satellite Remote Sensors

Proximal electrical conductivity (EC) and spectral sensing has been widely used as a cost-effective tool for soil mapping at field scale. The traditional method of calibrating proximal sensors for functional soil property prediction (e.g., soil organic matter, sand, silt, and clay contents) requires the local soil sample data, which results in a field-specific calibration. In this large-scale study consisting of 126 fields, we found that the traditional local calibration method had suffered weak... X. Xiong, D. Myers, J. Debruin, B. Gunzenhauser, N. Sampath, D. Ye, H. Underwood, R. Hensley

24. Yield Analysis in Sugarcane Harvesters Using Design of Experiments (DoE) Methodology

The sugarcane crop is highlighted in national agribusiness, Brazil is the world’s largest producer of the plant, and the prospection of specialists is of strong growth for the next years. However, in order to increase productivity, technological interventions through of precision agriculture must be implemented. Among them, the management of inputs guided by yield spatial variability for otmizing production and income. This project approaches the implementation of the methodology of analysis... M.L. Da silva, J. . Alves de lima, A. Balbinot, J.P. Molin

25. Precision Agriculture: Forage Chopper Noise Level As an Estimator of Corn Silage Production in Small Farms

The objective of the work carried out in the Registro County, SP, Brazil, in the year 2021, was to study the forage chopper noise level as an estimator of corn silage production in small farms. The corn crop study and characterization were measured plant height (PH), height of first ear insertion (HEI) and green mass production of plants (GM) were studied. The noise (NO) produced by the forage machine during ensiling was collected by recording, considering it as a potential yield estimator during... W.J. Souza, A.N. Silva

26. Incorporating Return on Investment for Profit-driven Management Zones

Adopting site-specific management practices such as profitability zones can help to stabilize long-term profit while also favoring the environment. Profitability maps are used to standardize data by converting variables into economic values ($/ha) for different cropping systems within a field. Thus, profitability maps can be used to define management zones from several years of data and show the regions within a field which are more profitable to invest in for production, or those that can be... A.A. Boatswain jacques, A.B. Diallo, A. Cambouris, E. Lord, E. Fallon

27. Deep Learning for Predicting Yield Temporal Stability from Short Crop Rotations

Investigating the temporal stability of yield in management zones is crucial for both producers and researchers, as it helps in mitigating the adverse impacts of unpredictable disruptions and weather events. The diversification of cropping systems is an approach which leads to reduced variability in yield while improving overall field resilience. In this six-year study spanning from 2016 to 2021, we monitored 40 distinct fields owned by 10 producers situated in Quebec, Canada. These... E. Lord, A.A. Boatswain jacques, A.B. Diallo, M. Khakbazan, A. Cambouris

28. Soybean Production Components As Indicators of Soil Variability As a Subsidy for Precision Agriculture

The soil variability in its physical, chemical and biological parameters can be analyzed using direct methods applicable to each variable studied. Plant responses, manifested in the establishment of the final population, biomass production and grain productivity can reflect the soil conditions, associating them with the variability observed in the area. Localized soil management and the use of machines with variable rate applications, including drones for applications in specific sites, depend... E. Apolinário, W.J. Souza

29. Real Time Application of Neural Networks and Hardware Accelerated Image Processing Pipeline for Precise Autonomous Agricultural Systems

Modern agriculture is increasingly turning to automation and precision technology to optimize crop management. In this context, our research addresses the development of an autonomous pesticide spraying rover equipped with advanced technology for precision agriculture. The primary goal is to use a neural network for real-time aphid detection in Sorghum crops, enabling targeted pesticide application only to infested plants. To accomplish this, we've integrated cutting-edge technologies and... J. Raitz persch, R. Harsha chepally, N.K. Piya

30. Can Soil Fertility Data and Topography Predict Yield Stability Zones for Corn Fields in New York?

Yield monitor systems play a vital role in precision agriculture given their ability to capture and map within-field yield variability. When three or more years of yield data are available, yield stability zone maps can be generated to show both the spatial and temporal variability of yield within a field. Based on the farm’s overall temporal mean and standard deviation for a specific crop, we can classify areas in the field as consistently high- (Q1) or low-yielding (Q4), and variably high-... M. Marcaida, X. Zhang, S. Srinivasagan, S. Shajahan, Q. Ketterings

31. Single-strip Spatial Evaluation Approach: a Simplified Method for Enhanced Sustainable Farm Management

On-farm experimentation (OFE) plays a pivotal role in evaluating and validating the effectiveness of agricultural practices and products. The results of OFE enable farmers to act and make changes that can enhance the farm’s economic and environmental sustainability. Experimental designs can be a barrier to the adoption of OFE. The conventional approach often involves randomized complete block designs with 3 to 5 replications in the field, which can be space-intensive and disrupt workflow... S. Srinivasagan, Q. Ketterings, M. Marcaida, S. Shajahan, J. Ramos-tanchez, J. Cho, , L. Thompson, J. Guinness, R. Goel