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Fernando, H
Feng, G
Watkins, P
Fergugson, R.B
Figueiredo, D.M
Willness, C
Whiting, M.D
Federle , C
Watanabe, K
Fornale, M
Williams, J.D
Wehrle, R
Firozjaei, M.K
Follett, R
Feldhaus, J
Ferguson, R.B
Fountas, S
Wu, B
Ferraz, C
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Authors
Cao, Q
Miao, Y
Feng, G
Gao, X
Liu, B
Khosla, R
Liu, B
Miao, Y
Feng, G
Yue, S
Li, F
Gao, X
Roberts, D.F
Shanahan, J.F
Fergugson, R.B
Adamchuk, V.I
Kitchen, N.R
Jonjak, A.K
Adamchuk, V.I
Wortmann, C.S
Shapiro, C.A
Fergugson, R.B
Pan, L
Adamchuk, V.I
Martin, D.L
Schroeder, M.A
Fergugson, R.B
Fountas, S
Bochtis, D
Sorensen, C
Green, O
J, R
Bartzanas, T
Long, D.S
Wuest, S.B
Williams, J.D
Bailey, M.J
Follett, R
Short, E
Cao, Q
Miao, Y
Feng, G
Li, F
Liu, B
Gao, X
Liu, Y
Kleinhenz, B
Röhrig, M
Scheiber, M
Feldhaus, J
Hartmann, B
Golla, B
Federle , C
Martini, D
Li, Z
Wu, B
Meng, J
Zeng, H
Wu, B
Yan, N
Ampatzidis, Y.G
Whiting, M.D
Fountas, S
Kotseridis, Y
Balafoutis, A
Anastasiou, E
Koundouras, S
Kallithraka, S
Kyraleou, M
Vellidis, G
Lowrance, C
Fountas, S
Liakos, V
Arnall, D.B
Phillips, S
Penn, C
Watkins, P
Rutter, B
Warren, J
Tekin, A
Fornale, M
Bean, G.M
Kitchen, N.R
Camberato, J.J
Ferguson, R.B
Fernandez, F.G
Franzen, D.W
Laboski, C.A
Nafziger, E.D
Sawyer, J.E
Scharf, P.C
Ransom, C.J
Kitchen, N.R
Camberato, J.J
Carter, P.R
Ferguson, R.B
Fernandez, F.G
Franzen, D.W
Laboski, C.A
Nafziger, E.D
Shanahan, J
Sawyer, J.E
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
Tsoulias, N
Paraforos, D
Brandes, N
Fountas, S
Zude-Sasse, M
PÄTZOLD, S
Heggemann, T.W
Wehrle, R
Fathololoumi, S
Firozjaei, M.K
Biswas, A
Daggupati, P
Ferreyra, R
Hillyer, C.C
Fuller, H.D
Craker, B
Watanabe, K
Nketia, K
Ha, T
Fernando, H
Shirtliffe, S
van Steenbergen, S
Vitali, G.-
Ferraz, C
Psiroukis, V
Fountas, S
Uyar, H
Balafoutis, A
Kasimati, A
Asgedom, H
Hehar, G
Willness, C
Anderson, W
Duddu, H
Mooleki, P
Schoenau, J
Khakbazan, M
Lemke, R
Derdall, E
Shang, J
Liu, K
Sulik, J
Karppinen, E
Mbakwe, I
Topics
Proximal Sensing in Precision Agriculture
Precision Nutrient Management
Spatial Variability in Crop, Soil and Natural Resources
Modeling and Geo-statistics
Precision Conservation
Precision Carbon Management
Precision Nutrient Management
Precision Crop Protection
Remote Sensing Applications in Precision Agriculture
Spatial Variability in Crop, Soil and Natural Resources
Precision Horticulture
Decision Support Systems in Precision Agriculture
Spatial Variability in Crop, Soil and Natural Resources
Unmanned Aerial Systems
In-Season Nitrogen Management
Precision Horticulture
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Proximal and Remote Sensing of Soils and Crops (including Phenotyping)
Data Analytics for Production Ag
Decision Support Systems
Drone Spraying
Site-Specific Nutrient, Lime and Seed Management
Type
Poster
Oral
Year
2012
2010
2014
2016
2018
2022
2024
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Authors

Filter results28 paper(s) found.

1. A Crop And Soil Strategy For Sensor-based Variable-rate Nitrogen Management

Crop-based active canopy sensors and soil-based management zones (MZ) are currently being studied as tools to direct in-season variable-rate N application. Some have suggested the integration of these tools as a more robust decision tool for guiding spatially variable N rates. The objectives of this study were to identify (1) soil variables useful for MZ delineation and (2) determine if MZ could be useful in identifying field areas with... D.F. Roberts, J.F. Shanahan, R.B. Fergugson, V.I. Adamchuk, N.R. Kitchen

2. 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

3. Analysis Of Water Use Efficiency Using On-the-go Soil Sensing And A Wireless Network

An efficient irrigation system should meet the demands of the growing crops. While limited water supply may result in yield reduction, excess irrigation is a waste of resources. To investigate water use efficiency, on-the-go sensing technology was used to reveal soil spatial variability relevant to water holding capacity (in this example, field elevation and apparent electrical conductivity). These high-density data layers were used to identify strategic sites where monitoring water availability... L. Pan, V.I. Adamchuk, D.L. Martin, M.A. Schroeder, R.B. Fergugson

4. Spatial-temporal Management Zones For Biomass Moisture

 Biomass handling operations (harvesting, raking, collection, and transportation) are critical operations within the agricultural production system since they constitute the first link in the biomass supply chain, a fact of substantial importance considering the increasingly involvement of biomass in bio-refinery and bio-energy procedures. Nevertheless, the inherent uncertainty, imposed by the interaction between environmental, biological, and machinery factors, makes the available scheduling... S. Fountas, D. Bochtis, C. Sorensen, O. Green, R. J, T. Bartzanas

5. Contour Planting: A Strategy To Reduce Soil Erosion On Steep Slopes

  Practices that combine GPS-based guidance for terrain contouring and tillage for runoff detention have potential to increase water infiltration and reduce runoff.  The objective of this study was to investigate contour planting as a means to reduce soil erosion on steep slopes of the Columbia Plateau dryland wheat region.  An exploratory field study was conducted on a Ritzville... D.S. Long, S.B. Wuest, J.D. Williams, M.J. Bailey,

6. An Overview of Soil Carbon, Management, and Agricultural Systems

  Topics to be covered include a discussion of what soil carbon sequestration is, how and where in the soil it occurs, and its role in maintaining important soil properties. The author draws upon his experience and that of others about practices for various parts of the US to describe on-farm and experimental agricultural systems and their degree of success to sequester carbon and improve soil quality. Included is an overview of carbon sequestration strategies and possible... R. Follett, E. Short

7. 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

8. Different Leaf Sensing Approaches for the Estimation of Winter Wheat Nitrogen Status

Nondestructive real time diagnosis of crop N status is crucial to the development of precision nitrogen (N) management strategies. Chlorophyll meter has been a popular sensor for such purposes and different approaches to use this sensor has been developed using a threshold value, nitrogen sufficiency index (NSI) or ratio of... B. Liu, Y. Miao, G. Feng, S. Yue, F. Li, X. Gao

9. Evaluating Different Nitrogen Management Strategies For The Intensive Wheat-Maize System In North China Plain

The sustainable agricultural development involves both environmental challenges and production goals to meet growing food demand. However, excessive nitrogen (N) applications are threatening the sustainability of intensive agriculture in the North China Plain (NCP). Improved N management should result in greater N use efficiency (NUE) and producer profit while reducing the risk of environmental contamination. Therefore, developing and disseminating feasible N management strategies... Q. Cao, Y. Miao, G. Feng, F. Li, B. Liu, X. Gao, Y. Liu

10. Pesticide Application Manager (PAM) - Decision Support In Crop Protection Based On Terrain-, Machine-, Business- And Public Data

Introduction   Pesticide Application Manager (PAM) is a project, co-financed by the German Federal Office for Agriculture and Food (BLE) that aims to develop solutions for automating important processes in crop protection.   Due to a series of rules and legal requirements for planning, implementation and documentation, crop protection is one of the most... B. Kleinhenz, M. Röhrig, M. Scheiber, J. Feldhaus, B. Hartmann, B. Golla, C. Federle , D. Martini

11. Design, Development And Application Of A Satellite-Based Field Monitoring System To Support Precision Farming

The factual base of precision agriculture (PA) - the spatial and temporal variability of soil and crop factors within or between different fields has been recognized for centuries. Field information on seeding suitability, soil & crop nutrition status and crop mature date is needed to optimize field management. How to acquire the spatially and temporally varied field parameters accurately, efficiently and at affordable cost has always been the focus of the researches in the field.... Z. Li, B. Wu, J. Meng

12. A Method To Estimate Irrigation Efficiency With Evapotranspiration Data

Irrigation efficiency is defined as the ratio of irrigation water consumed by the crops to the water diverted (Wg) from a river or reservoir or wells. This terminology serves for better irrigation systems designation and irrigation management practices improvement. But it is hard or high cost with labor intensity to estimate irrigation efficiency from field measurement. This paper proposes an estimating method of irrigation efficiency at the scale of irrigation... H. Zeng, B. Wu, N. Yan

13. A Novel Portable System For Improving Accuracy Of Reimbursement For Fruit Picking

Various methods for reimbursing pickers have been employed worldwide, with most fruit growers now paying a piece-rate to small picking teams for bins (e.g. for pome fruit) or for buckets (e.g. for sweet cherries, blueberries).  Regardless, paying piece-rate is beset with inaccuracies that cause significant financial losses. Our tests in commercial sweet cherry and apple orchards revealed variability of 25 – 30% of final weight among bins and buckets. For example, in sweet... Y.G. Ampatzidis, M.D. Whiting

14. 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

15. EZZone - An Online Tool for Delineating Management Zones

Management zones are a pillar of Precision Agriculture research.  Spatial variability is apparent in all fields, and assessing this variability through measurement devices can lead to better management decisions.  The use of Geographic Information Systems for agricultural management is common, especially with management zones.  Although many algorithms have been produced in research settings, no online software for management zone delineation exists.  This research used a common... G. Vellidis, C. Lowrance, S. Fountas, V. Liakos

16. Should One Phosphorus Extraction Method Be Used for VRT Phosphorus Recommendation in the Southern Great Plains?

Winter Wheat has been produced throughout the southern Great Plains for over 100 years.  In most cases this continuous production of mono-culture lower value wheat crop has led to the neglect of the soils, one such soil property is soil pH. In an area dominated by eroded soils and short term leases, Land-Grant University wheat breeders have created lines of winter wheat which are aluminum tolerant to increase production in low productive soils.  Now the fields in this region can have... D.B. Arnall, S. Phillips, C. Penn, P. Watkins, B. Rutter, J. Warren

17. Developing UAV Image Acquisition System and Processing Steps for Quantitative Use of the Data in Precision Agriculture

Mapping natural variability of crops and land is first step of the management cycle in terms of crop production. Several methods have been developed and engaged for data recording and analyzing that generate prescription maps such as yield monitoring, soil mapping, remote sensing etc. Although conventional remote sensing by capturing images via satellites has been very popular tool to monitor the earth surface, it has several drawbacks such as orbital period, unattended capture, investment cost.... A. Tekin, M. Fornale

18. Corn Nitrogen Fertilizer Recommendation Models Based on Soil Hydrologic Groups Aid in Predicting Economically Optimal Nitrogen Rates

Nitrogen (N) fertilizer recommendations that match corn (Zea mays L.) N needs maximize grower profits and minimize water quality consequences. However, spatial and temporal variability makes determining future N requirements difficult. Studies have shown no single soil or weather measurement is consistently increases accuracy, especially when applied over a regional scale, in predicting economically optimal N rate (EONR). Basing site N response on soil hydrological group could help account for... G.M. Bean, N.R. Kitchen, J.J. Camberato, R.B. Ferguson, F.G. Fernandez, D.W. Franzen, C.A. Laboski, E.D. Nafziger, J.E. Sawyer, P.C. Scharf

19. Improving Corn Nitrogen Rate Recommendations Through Tool Fusion

 Improving corn (Zea maysL,) nitrogen (N) fertilizer rate recommendation tools can improve farmer’s profits and help mitigate N pollution. One way to improve N recommendation methods is to not rely on a single tool, but to employ two or more tools. Thiscould be thoughtof as “tool fusion”.The objective of this analysis was to improve N management by combining N recommendation tools used for guiding rates for an in-seasonN application. This evaluation was... C.J. Ransom, N.R. Kitchen, J.J. Camberato, P.R. Carter, R.B. Ferguson, F.G. Fernandez, D.W. Franzen, C.A. Laboski, E.D. Nafziger, J. Shanahan, J.E. Sawyer

20. 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

21. Calculating the Water Deficit of Apple Orchard by Means of Spatially Resolved Approach

In semi-humid climate, spatially resolved analysis of water deficit was carried out in apple orchard (Malus x domestica 'Pinova'). The meteorological data were recorded daily by a weather station. The apparent soil electrical conductivity (ECa) was measured at field capacity, and twenty soil samples in 30 cm were gathered for texture, bulk density, and gravimetric soil water content analyses. Furthermore, ten trees were defoliated in different ECa regions in order to estimate the leaf... N. Tsoulias, D. Paraforos, N. Brandes, S. Fountas, M. Zude-sasse

22. On-the-go Gamma Spectrometry and Its Evaluation Via Support Vector Machines: Really a Valuable Tool for Site-independent Soil Texture Prediction?

With progressive implementation of precision agriculture (PA) techniques in current agricultural/ viticultural practice, the need for high-resolution information on soil properties at low effort and cost is increasing. Moreover, climate change and extended drought periods do even increase this demand. Evaluating soil fertility and carbon storage potential of arable fields and vineyards, e.g. for future economic assessment of ecosystem services, requires spatially resolved soil data. Soil texture... S. PÄtzold, T.W. Heggemann, R. Wehrle

23. A Fusion Strategy to Map Corn Crop Residues

Access to post-harvest residue coverage information is crucial for agricultural management and soil conservation. The purpose of this study was to present a new approach based on an ensemble at the decision level for mapping the corn residue. To this end, a set of Landsat 8 imagery and field data including the Residue Cover Fraction (RCF) of corn (149 samples), were used. Firstly, a map of common spectral indices for RCF modeling was prepared based on the spectral bands. Then, the efficiency of... S. Fathololoumi, M.K. Firozjaei, A. Biswas, P. Daggupati

24. Interoperability As an Enabler for Principled Decision-making in Irrigation: the Precision Agriculture Irrigation Language (PAIL)

Fresh water is a scarce resource, and agriculture consumes a high fraction of it worldwide. As climate change increases the likelihood of high temperatures and droughts, irrigation becomes an increasingly attractive option for managing crop production risks. Unfortunately, and despite decades of efforts by professional associations to promote the use of a principled, data-driven approach to irrigation scheduling often called scientific irrigation scheduling (SIS), the fraction of farmers... R. Ferreyra, C.C. Hillyer, H.D. Fuller, B. Craker, K. Watanabe

25. Digital Agriculture Driven by Big Data Analytics: a Focus on Spatio-temporal Crop Yield Stability and Land Productivity

In the ever-evolving landscape of agriculture, the adoption of digital technologies and big data analytics has ushered in a transformative era known as digital agriculture. This paradigm shift is primarily motivated by the pressing imperative to address the growing global population's food requirements, mitigate the adverse effects of climate change, and promote sustainable land management. Canada, a significant player in global food production, has made a substantial commitment to reducing... K. Nketia, T. Ha, H. Fernando, S. Shirtliffe, S. Van steenbergen

26. AI Tools in Agri DSS Pipeline - the Case of Irrigated Sugarbeet

A general pipeline that can be associated to a DSS includes several steps. Data Collectionn includes Acquisition, extraction, and aggregation of data from previously identified and selected sources. Data Cleaning and preparation make data available for exploratory analysis that make them usable. Data Analysis is then applied to extract meaningful information e.g. by statistical and/or simulation models. Data are successively synthesized and visualized to make them clear to the decision-maker to... G.-. Vitali, C. Ferraz

27. Optimizing Vineyard Crop Protection: an In-depth Study of Spraying Drone Operational Parameters

In modern agriculture, the precise and efficient application of agrochemicals is essential to ensure crop health and increase productivity while minimizing adverse environmental impacts. While traditional spraying methods have long been the cornerstone of crop protection, the introduction of unmanned aerial vehicles (UAVs), commonly known as drones), has led to a revolutionary era in agriculture. UAVs offer novel opportunities to improve agricultural practices by providing precision, efficiency,... V. Psiroukis, S. Fountas, H. Uyar, A. Balafoutis, A. Kasimati

28. Response of Canola and Wheat to Application of Enhanced Efficiency Nitrogen Fertilizers on Contrasting Management Zones

Investment on nitrogen (N) fertilizers is a major cost of growers, and variable rate (VR) application of N fertilizers could help optimize its usage. In the growing season of 2023, field experiments were conducted at four sites (i.e., Watrous – Saskatchewan SK and two fields in the vicinity of Strathmore, Alberta AB, Canada). The main objectives were to (i) determine performance of Enhanced Efficiency N Fertilizers - EENF (i.e., Coated urea, urea with double inhibitors - DI, urea mixed with... H. Asgedom, G. Hehar, C. Willness, W. Anderson, H. Duddu, P. Mooleki, J. Schoenau, M. Khakbazan, R. Lemke, E. derdall, J. Shang, K. Liu, J. Sulik, E. Karppinen, I. Mbakwe