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Endres, G
Bradford, J
Dobers, S.E
Farahmand, K
Runge, M
Bishop, T
Del Solar, D.E
Lovejoy, K
Dutilleul, P
Rejesus, R
Rennó, L.N
Bell, G.E
Lepoivre, B
Reitsma, K.D
Roberts, D
Bazzi, C
Roy, R
Levi, O
Lima, J.P
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Authors
Cohen, Y
Alchanatis, V
Levi, O
Cohen, S
Cox, M
Roberts, D
Samborski, S.M
Gozdowski, D
Dobers, S.E
Winstead, A.T
Norwood, S.H
Griffin, T
Adrian, A.M
Runge, M
Fulton, J.P
Reitsma, K.D
Schumacher, T.E
Moss, J.Q
Bell, G.E
Velandia, M
Mooney, D.F
Roberts, R.K
English, B.C
Larson, J.A
Lambert, D.M
Larkin, S.L
Marra, M.C
Rejesus, R
Martin, S.W
Paxton, K.W
Mishra, A
Wang, C
Segarra, E
Reeves, J.M
Moss, J.Q
Bell, G.E
Solie, J.B
Stone, M.L
Martin, D.L
Payton, M.E
Ortega, R.A
Del Solar, D.E
Acevedo, E
Sharma, L
Bu, H
Ashley, R
Endres, G
Teboh, J
Franzen, D.W
Jacquin, A
Sigel, G
Hagolle, O
Lepoivre, B
Roumiguié, A
Poilvé, H
Momsen, E
Xu, J
Franzen, D.W
Nowatzki, J.F
Farahmand, K
Denton, A.M
Adamchuk, V.I
Dhawale, N
Biswas, A
Lauzon‎, S
Dutilleul, P
Souza, E
Schenatto, K
Bazzi, C
Fadul-Pacheco, L
Bisson, G
Lacroix, R
Séguin, M
Roy, R
Vasseur, E
Lefebvre, D
de Azevedo, K.K
Figueiredo, D.M
de Sousa, M.G
Dallago, G.M
Silveira, R.R
da Silva, L.D
Rennó, L.N
Santos, R.A
de Azevedo, K.K
Figueiredo, D.M
Dallago, G.M
Vieira, J.A
Silveira, R.R
da Silva, L.D
Santos, R.A
Rennó, L.N
Pacheco, G.B
Erickson, B
Lowenberg-DeBoer, J
Bradford, J
Souza, E.G
Bazzi, C
Hachisuca, A
Sobjak, R
Gavioli, A
Betzek, N
Schenatto, K
Mercante, E
Rodrigues, M
Moreira, W
Aikes Junior, J
Souza, E.G
Bazzi, C
Sobjak, R
Hachisuca, A
Gavioli, A
Betzek, N
Schenatto, K
Moreira, W
Mercante, E
Rodrigues, M
Hachisuca, A
Souza, E.G
Mercante, E
Sobjak, R
Ganascini, D
Abdala, M
Mendes, I
Bazzi, C
Rodrigues, M
Hoffmann Silva Karp, F
Adamchuk, V
Melnitchouck, A
Dutilleul, P
Pereira, F.R
Lima, J.P
Freitas, R.G
Dos Reis, A.A
Amaral, L.R
Figueiredo, G.K
Lamparelli, R.A
Pereira, J.C
Magalhães, P.S
Tilse, M.J
Filippi, P
Bishop, T
Filippi, P
Bishop, T
Al-Shammari, D
McPherson, T
Leininger, A
Verhoff, K
Lovejoy, K
Thomas, A
Davis, G
Emmons, A
Fulton, J.P
Filippi, P
Bishop, T
Han, S
Hoffmann Silva Karp, F
Adamchuk, V
Dutilleul, P
Melnitchouck, A
Biswas, A
Topics
Machine Vision / Multispectral & Hyperspectral Imaging Applications to Precision Agriculture
Education and Training in Precision Agriculture
Remote Sensing Applications in Precision Agriculture
Precision A-Z for Practitioners
Precision Carbon Management
Precision Horticulture
Profitability, Sustainability, and Adoption
Spatial Variability in Crop, Soil and Natural Resources
Sensor Application in Managing In-season CropVariability
Remote Sensing Applications in Precision Agriculture
Big Data Mining & Statistical Issues in Precision Agriculture
Education and Outreach in Precision Agriculture
Precision Dairy and Livestock Management
In-Season Nitrogen Management
Farm Animals Health and Welfare Monitoring
Decision Support Systems
Geospatial Data
In-Season Nitrogen Management
Proximal and Remote Sensing of Soils and Crops (including Phenotyping)
Decision Support Systems
Drone Spraying
Big Data, Data Mining and Deep Learning
Type
Poster
Oral
Year
2012
2010
2014
2016
2018
2022
2024
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Authors

Filter results28 paper(s) found.

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

           Site-specific crop/soil management technologies have been available for over fifteen years. Consequently, there is a demand for classroom and laboratory education across a variety of agricultural disciplines in the University community. To meet this demand, a course was developed in 1998 to teach the basic concepts of site-specific crop/soil management. This class is designed as a upper level undergraduate and graduate class and generally has between 10... M. Cox, D. Roberts

2. The Use Of A Ground Based Remote Sensor For Winter Wheat Grain Yield Prediction In Northern Poland

  The aim of the research was to investigate if algorithms developed for winter wheat, cv. Trend, yield predictions, based on ground measured GNDVI, differ significantly between 2 sequent years. The research was conducted in Pomerania, northern Poland (54° 31' N 17° 18' E) on sandy loam soils. The strip-trial design was used to compare the effect of 6 N treatments: 0, 50, 100, 150, 200 and 250 kg ha-1, applied as one dose at the beginning... S.M. Samborski, D. Gozdowski, S.E. Dobers

3. Adoption And Use Of Precision Agriculture Technologies By Practitioners

A survey of farmers and farm service providers were initiated to ascertain the adoption and use of precision agriculture technologies as well as the barriers to and incentives for adoption. Farm-level data were collected via audience response system at the 2009 Alabama Precision Ag and Field Crops Conference and local winter production meetings across the six crop reporting districts in Alabama. Service provider data were collected using an online survey. Questions common to farmers and service... A.T. Winstead, S.H. Norwood, T. Griffin, A.M. Adrian, M. Runge, J.P. Fulton

4. Estimating Soil Productivity And Energy Efficiency Using Websoil Survey, Soil Productivity Index Calculator, And Biofuel Energy Systems Simulator

Soils have varying production capacities for a specific plant or sequence of plants under defined management strategies. The production capacity or “productivity” can be quantified as a mathematical function of a soils ability to sufficiently sustain plant growth... K.D. Reitsma, T.E. Schumacher

5. Indirect Measurement Of Creeping Bentgrass N, Chlorophyll, And Color For Precision Golf Green Management

Indirect measurement of turfgrass tissue through optical sensing may provide golf course managers with non-destructive and relatively simple real-time measurements of golf green N requirements. The objective of this study was to determine the effect of N rate on ‘Crenshaw’ creeping bentgrass (Agrostis stolonifera L.) tissue N, chlorophyll concentration, and color using the GreenSeeker (NTech Industries, Ukiah, CA) handheld sensor. Plots... J.Q. Moss, G.E. Bell

6. Cotton Precision Farming Adoption In The Southern United States: Findings From A 2009 Survey

The objectives of this study were 1) to determine the status of precision farming technology adoption by cotton producers in 12 states and 2) to evaluate changes in cotton precision farming technology adoption between 2000 and 2008. A mail survey of cotton producers located in Alabama, Arkansas, Florida, Georgia, Louisiana, Mississippi, Missouri, North Carolina, South Carolina, Tennessee, Texas and Virginia was conducted in February and March of 2009 to establish the use of precision farming technologies... M. Velandia, D.F. Mooney, R.K. Roberts, B.C. English, J.A. Larson, D.M. Lambert, S.L. Larkin, M.C. Marra, R. Rejesus, S.W. Martin, K.W. Paxton, A. Mishra, C. Wang, E. Segarra, J.M. Reeves

7. Development Of A Precision Sensing Sprayer For The Application Of Nitrogen Fertilizer To Turfgrass

  Normalized difference vegetation index (NDVI) may be very useful for turfgrass managers to measure turf quality and obtain an indirect measurement of turf N status. The objective of this research was to develop a Nitrogen Fertilization Optimization Algorithm (NFOA) for use in a turfgrass variable rate N applicator on bermudagrass [Cynodon dactylon (L.) Pers] fairways and creeping bentgrass (Agrostis stolonifera L.) greens in Oklahoma. Plots (0.9 X 1.5 m)... J.Q. Moss, G.E. Bell, J.B. Solie, M.L. Stone, D.L. Martin, M.E. Payton

8. Spatial Variability Of Spikelet Sterility In Temperate Rice In Chile

Spikelet sterility (blanking) causes large economic losses to rice farmers in Chile. The most common varieties are susceptible to low air and water temperatures during pollen formation and flowering, which is the main responsible for the large year to year variation observed in terms of blanking and, therefore, of grain yield. The present work had for objective to study the spatial variability of spikelet sterility within two rice fields, during two consecutive seasons, and relate it to water... R.A. Ortega, D.E. Del solar, E. Acevedo

9. A Method for Combining Spatial and Hyperspectral Information for Delineation of Homogenous Management Zones

Hyperspectral (HS) remote sensing is a constantly developing field. New remote sensing applications of different fields constantly appear. The possibility of acquisition information about an object without physical contact is spanning new opportunities in many fields and for precision agricultural in particular. These opportunities demand constant improvement and development of new analysis approaches and algorithms,... Y. Cohen, V. Alchanatis, O. Levi, S. Cohen

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

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

11. 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

12. Use Of Quality And Quantity Information Towards Evaluating The Importance Of Independent Variables In Yield Prediction

Yield predictions based on remotely sensed data are not always accurate.  Adding meteorological and other data can help, but may also result in over-fitting.  Working with American Crystal Sugar, we were able to demonstrate that the relevance of independent variables can be tested much more reliably when not only yield but also quality attributes are known, such as the sugar content and the sugar... E. Momsen, J. Xu, D.W. Franzen, J.F. Nowatzki, K. Farahmand, A.M. Denton

13. Integrated Analysis of Multilayer Proximal Soil Sensing Data

Data revealing spatial soil heterogeneity can be obtained in an economically feasible manner using on-the-go proximal soil sensing (PSS) platforms. Gathered georeferenced measurements demonstrate changes related to physical and chemical soil attributes across an agricultural field. However, since many PSS measurements are affected by multiple soil properties to different degrees, it is important to assess soil heterogeneity using a multilayer approach. Thus, analysis of multiple layers of geospatial... V.I. Adamchuk, N. Dhawale, A. Biswas, S. Lauzon‎, P. Dutilleul

14. Creating Thematic Maps and Management Zones for Agriculture Fields

Thematic maps (TMs) are maps that represent not only the land but also a topic associated with it, and they aim to inform through graphic symbols where a specific geographical phenomenon occurs. Development of TMs is linked to data collection, analysis, interpretation, and representation of the information on a map, facilitating the identification of similarities, and enabling the visualization of spatial correlations. Important issues associated with the creation of TMs are: selection of the... E. Souza, K. Schenatto, C. Bazzi

15. Usage of Milk Revenue Per Minute of Boxtime to Assess Cows Selection and Farm Profitability in Automatic Milking Systems

The number of farms implementing robotic milking systems, usually referred as automatic milking systems (AMS), is increasing rapidly. AMS efficiency is a priority to achieve high milk production and higher incomes from dairy herds. Recent studies suggested that milkability (i.e., amount of milk produced per total time spent in the AMS [kg milk/ minute of boxtime]) could be used for as a criteria for genetic evaluations. Therefore, an indicator of milkability was developed, which combines economical... L. Fadul-pacheco, G. Bisson, R. Lacroix, M. Séguin, R. Roy, E. Vasseur, D. Lefebvre

16. Levels of Inclusion of Crambe Meal (Crambe Abyssinica Hochst) in Sheep Diet on the Balance of Nitrogen and Ureic Nitrogen in the Blood Serum

Crambe meal, which is a co-product of biodiesel production, is a potential substitute for conventional protein sources in ruminant diets. The objective of this study was to evaluate the effect of the substitution of crude protein of the concentrate by crude protein of crambe meal with increasing levels (0, 25, 50, and 75%) on nitrogen balance and blood plasma urea nitrogen concentration in sheep. Four male sheep, rumen fistulated, were placed in metabolic crates and distributed in a 4 x 4 Latin... K.K. De azevedo, D.M. Figueiredo, M.G. De sousa, G.M. Dallago, R.R. Silveira, L.D. Da silva, L.N. Rennó, R.A. Santos

17. Efficiency of Microbial Synthesis and the Flow of Nitrogen Compounds in Sheep Receiving Crambe Meal (Crambe Abyssinica Hochst) Replacing the Concentrade Crude Protein

The objective of this study was to evaluate the effect of increasing levels (0, 25, 50, 75%) of crude protein substitution of the concentrate by crude protein of crambe meal on microbial protein synthesis and the flow of microbial nitrogen compounds in sheep. Four rumen fistulated sheep (18 months and initial average body weight of 50 kg) were distributed in a 4 x 4 Latin square design. Diets were balanced to meet the requirements for minimum gains, containing approximately 14% crude protein and... K.K. De azevedo, D.M. Figueiredo, G.M. Dallago, J.A. Vieira, R.R. Silveira, L.D. Da silva, R.A. Santos, L.N. Rennó, G.B. Pacheco

18. Tracking Two Decades of Precision Agriculture Through the Croplife Purdue Survey

The CropLife/Purdue University precision dealer survey is the longest-running continuous survey of precision farming adoption.  The 2017 survey is the 18th, conducted every year from 1997 to 2009, and then every other year following.  For individuals working in agriculture there is great value in knowing who is doing what and why, to get a better understanding of the utilities and applications, and to guide investments.  A major revision in survey questions was made... B. Erickson, J. Lowenberg-deboer, J. Bradford

19. AgDataBox: Web Platform of Data Integration, Software, and Methodologies for Digital Agriculture

Agriculture is challenging to produce more profitably, with the world population expected to reach some 10 billion people by 2050. Such a challenge can be achieved by adopting precision agriculture and digital agriculture (Agriculture 4.0). Digital agriculture has become a reality with the availability of cheaper and more powerful sensors, actuators and microprocessors, high-bandwidth cellular communication, cloud communication, and Big Data. Digital agriculture enables the flow of information... E.G. Souza, C. Bazzi, A. Hachisuca, R. Sobjak, A. Gavioli, N. Betzek, K. Schenatto, E. Mercante, M. Rodrigues, W. Moreira

20. Web Application for Automatic Creation of Thematic Maps and Management Zones - AgDataBox-Fast Track

Agriculture is challenging to produce more profitably, with the world population expected to reach some 10 billion people by 2050. Such a challenge can be achieved by adopting precision agriculture and digital agriculture (Agriculture 4.0). Digital agriculture (DA) has become a reality with the availability of cheaper and more powerful sensors, actuators and microprocessors, high-bandwidth cellular communication, cloud communication, and Big Data. DA enables information to flow from used agricultural... J. Aikes junior, E.G. Souza, C. Bazzi, R. Sobjak, A. Hachisuca, A. Gavioli, N. Betzek, K. Schenatto, W. Moreira, E. Mercante, M. Rodrigues

21. AgDataBox-IoT Application Development for Agrometeorogical Stations in Smart Farm

Currently, Brazil is one of the world’s largest grain producers and exporters. Brazil produced 125 million tons of soybean in the 2019/2020 growing season, becoming the world’s largest soybean producer in 2020. Brazil’s economic dependence on agribusiness makes investments and research necessary to increase yield and profitability. Agriculture has already entered its 4.0 version, also known as digital agriculture, when the industry has entered the 4.0 era. This new paradigm uses... A. Hachisuca, E.G. Souza, E. Mercante, R. Sobjak, D. Ganascini, M. Abdala, I. Mendes, C. Bazzi, M. Rodrigues

22. Optimization of Batch Processing of High-density Anisotropic Distributed Proximal Soil Sensing Data for Precision Agriculture Purposes

The amount of spatial data collected in agricultural fields has been increasing over the last decade. Advances in computer processing capacity have resulted in data analytics and artificial intelligence becoming hot topics in agriculture. Nevertheless, the proper processing of spatial data is often neglected, and the evaluation of methods that efficiently process agricultural spatial data remains limited. Yield monitor data is a good example of a well-established methodology for data processing... F. Hoffmann silva karp, V. Adamchuk, A. Melnitchouck, P. Dutilleul

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

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

24. Predicting, Mapping, and Understanding the Drivers of Grain Protein Content Variability – Utilising John Deere’s New Harvestlab 3000 Grain Sensing System

Grain protein content (GPC) is a key determinant of the prices that grain growers receive, and the rising cost of production is shifting management focus towards optimising this to maximise return on investment. In 2023, John Deere released the HarvestLab 3000TM Grain Sensing system in Australia for real-time, on-the-go measurement of protein, starch, and oil values for wheat, barley, and canola. However, while the uptake of these sensors is increasing, GPC maps are not available for... M.J. Tilse, P. Filippi, T. Bishop

25. Are Pulses Really More Variable Than Cereals? a Country-wide Analysis of Within-field Variability

In Australia, pulses are underutilised by growers relative to cereal crops. There is significant global interest in growing pulses to provide more plant protein, and they also provide a string of agronomic and environmental benefits, such as their ability to fix nitrogen, and provide a pest and disease break for cereal crops. Many studies attribute this underutilisation to pulses exhibiting greater within-field yield variability than cereals. However, this has never been comprehensively examined... P. Filippi, T. Bishop, D. Al-shammari, T. Mcpherson

26. Deposition Characteristics of Different Style Spray Tips at Varying Speeds and Altitudes from an Unmanned Aerial System

The application of pesticides with a UAS has become a popular practice over the past few years within crop production. The ability to carry larger volumes of liquid i onboard, reduced costs, and simple operation has attributed to the increased popularity. Additionally, the increased number of fungicide applications in corn due to the tar spot disease has shown that the demand for aerial applications of all types has increased with UAS pesticide application technology providing the opportunity... A. Leininger, K. Verhoff, K. Lovejoy, A. Thomas, G. Davis, A. Emmons, J.P. Fulton

27. On Data-driven Crop Yield Modelling, Predicting, and Forecasting and the Common Flaws in Published Studies

There has been a recent surge in the number of studies that aim to model crop yield using data-driven approaches. This has largely come about due to the increasing amounts of remote sensing (e.g. satellite imagery) and precision agriculture data available (e.g. high-resolution crop yield monitor data), and abundance of machine learning modelling approaches. This is a particular problem in the field of Precision Agriculture, where many studies will take a crop yield map (or a small number), create... P. Filippi, T. Bishop, S. Han, I. Rund

28. Predicting Soil Chemical Properties Using Proximal Soil Sensing Technologies and Topography Data: a Case Study

Using proximal soil sensors (PSS) is widely recognized as a strategy to improve the quality of agricultural soil maps. Nevertheless, the signals captured by PSS are complex and usually relate to a combination of processes in the soil. Consequently, there is a need to explore further the interactions at the source of the information provided by PSS. The objectives of this study were to examine the relationship between proximal sensing techniques and soil properties and evaluate the feasibility... F. Hoffmann silva karp, V. Adamchuk, P. Dutilleul, A. Melnitchouck, A. Biswas