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Mueller, T.G
Meyer-Aurich, A
Bellenguez, R
Mahmood, S.A
Dhal, S
Moreira, B
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Authors
Dosskey, M.G
Mueller, T.G
Meyer-Aurich, A
Gandorfer, M
Weersink, A
Wagner, P
McNeill, D
Bishop-Hurley, G.J
Irvine, L
Freeman, M
Bellenguez, R
Murdoch, A.J
Mahmood, S.A
Meyer-Aurich, A
Karatay, Y
Gandorfer, M
Dhal, S
Louis, J
O'Sullivan, N
Gumero, J
Soetan, M
Kalafatis, S
Lusher, J
Mahanta, S
Barbosa, M
Duron, D
Rontani, F
Bortolon, G
Moreira, B
Oliveira, L
Setiyono, T
Shiratsuchi, L
Silva, R.P
Holland, K.H
Matavel, C
Meyer-Aurich, A
Piepho, H
Topics
Precision Conservation
Optimizing Farm-level use of Spatial Technologies
Precision Livestock Management
Spatial Variability in Crop, Soil and Natural Resources
Profitability and Success Stories in Precision Agriculture
Decision Support Systems
Artificial Intelligence (AI) in Agriculture
On Farm Experimentation with Site-Specific Technologies
Type
Oral
Year
2010
2014
2018
2022
2024
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Authors

Filter results8 paper(s) found.

1. Designing Variable-width Filter Strips Using GIS And Terrain Analysis

Filter strips are a widely-used practice for reducing the load of pollutants that leave agricultural fields in overland runoff. They are typically designed to intercept uniformly-distributed runoff with a constant width strip along a field margin. Non-uniform runoff flow, however, can reduce the effectiveness of a constant-width filter strip. Non-uniform flow is created by topographic undulations and swales in fields that concentrate runoff into certain locations... M.G. Dosskey, T.G. Mueller

2. Economic Potential Of Monitoring Protein Content At Harvest And Blending Wheat Grain

  Precision agriculture has been primarily focused on the management of inputs but recently developed technologies that monitor grain quality at harvest create the opportunity to manage outputs spatially.  Provided specific product qualities achieve higher prices, monitoring, separation and blending may be economically justified. This paper analyzes the potential economic effects of blending different grain qualities at the farm level. We estimated sub-field specific... A. Meyer-aurich, M. Gandorfer, A. Weersink, P. Wagner

3. A Preliminary Evaluation Of Proximity Loggers To Detect Oestrus Behaviour In Grazing Dairy Cows

... D. Mcneill, G.J. Bishop-hurley, L. Irvine, M. Freeman, R. Bellenguez

4. Toward More Precise Sugar Beet Management Based On Geostatistical Analysis Of Spatial Variabilty Within Fields

Abstract: Sugar beet (Beta vulgaris L.) yields in England are predicted to increase in the future, due to the advances in plant breeding and agronomic progress, but the intra-field variations in yield due to the variability in soil properties is considerable. This paper explores the within-field spatial variation in environmental variables and crop development during the growing season and their link to spatial variation in sugar beet yield.... A.J. Murdoch, S.A. Mahmood

5. Risk Efficiency of Site-Specific Nitrogen Management with Respect to Grain Quality

Profitability analyses of site-specific nitrogen management strategies have often failed to provide reasons for adoption of precision farming implements. However, often effects of precision farming on product quality and price premiums were not taken into account. This study aims to evaluate comparative advantages of site-specific nitrogen management over uniform nitrogen management with respect to aspects of risk, considering fertilizer effects on grain quality and price premiums. We developed... A. Meyer-aurich, Y. Karatay, M. Gandorfer

6. An IoT-based Smart Real Time Sensing and Control of Heavy Metals to Ensure Optimal Growth of Plants in an Aquaponic Set-up

The concentration of heavy metals that needs to be maintained in aquaponic environments for habitable growth of plants has been a cause of concern for many decades now as it is not possible to eliminate them completely in a commercial set-up. Our goal is to design a cost-effective real-time smart sensing and actuation system in order to control the concentration of heavy metals in aquaponic solutions. Our solution consists of sensing the nutrient concentrations in the aquaponic solution, namely... S. Dhal, J. Louis, N. O'sullivan, J. Gumero, M. Soetan, S. Kalafatis, J. Lusher, S. Mahanta

7. Multi-sensor Remote Sensing: an AI-driven Framework for Predicting Sugarcane Feedstock

Predicting saccharine and bioenergy feedstocks in sugarcane enables stakeholders to determine the precise time and location for harvesting a better product in the field. Consequently, it can streamline workflows while enhancing the cost-effectiveness of full-scale production. On one hand, Brix, Purity, and total reducing sugars (TRS) can provide meaningful and reliable indicators of high-quality raw materials for industrial food and fuel processing. On the other hand, Cellulose, Hemicellulose,... M. Barbosa, D. Duron, F. Rontani, G. Bortolon, B. Moreira, L. Oliveira, T. Setiyono, L. Shiratsuchi, R.P. Silva, K.H. Holland

8. Optimizing Experimental Design for Determining Economic Nitrogen Levels: Insights on the Use of Monte Carlo Simulations

The determination of economic nitrogen levels is a pivotal element in the quest for sustainable agricultural practices. Designing experiments to accurately identify these levels, especially in contexts constrained by limited plot availability, poses a significant challenge. In response to these challenges, this study endeavors to demonstrate  an approach to optimize the experimental design for identifying economic nitrogen levels, even under such constraints. We employed statistical... C. Matavel, A. Meyer-aurich, H. Piepho