Proceedings

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Butts, C
Martello, L.S
Karatay, Y
Mahmood, S.A
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Authors
Murdoch, A.J
Mahmood, S.A
Martello, L.S
Canata, T.F
Sousa, R.V
Meyer-Aurich, A
Karatay, Y
Gandorfer, M
Gallios, I
Vellidis, G
Butts, C
Topics
Spatial Variability in Crop, Soil and Natural Resources
Precision Dairy and Livestock Management
Profitability and Success Stories in Precision Agriculture
Decision Support Systems
Type
Oral
Poster
Year
2014
2018
2022
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Filter results4 paper(s) found.

1. 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

2. Application Of Infrared Thermography For Assessing Beef Cattle Comfort Using A Fuzzy Logic Classifier

... L.S. Martello, T.F. Canata, R.V. Sousa

3. 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

4. Making Irrigator Pro an Adaptive Irrigation Decision Support System

Irrigator Pro is a public domain irrigation scheduling model developed by the USDA-ARS National Peanut Research Laboratory. The latest version of the model uses either matric potential sensors to estimate the plant’s available soil water or manual data input. In this project, a new algorithm is developed, which will provide growers and consultants with much more flexibility in how they can feed data to the model. The new version will also run with Volumetric Water Content sensors, giving... I. Gallios, G. Vellidis, C. Butts