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Andales, A
Kopanja, M
Kinder, T
Hammond, K
Li, M
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Authors
Ruckelshausen, A
Dzinaj, T
Kinder, T
Bosse, D
Klose, R
Kerry, R
Shumate, S
Ingram, B
Hammond, K
Gunther, D
Jensen, R
Schill, S
Hansen, N
Hopkins, B
van Evert, F
Van Oort, P
Maestrini, B
Pronk, A
Boersma, S
Kopanja, M
Mimić, G
Muller, I
Czarnecki, J
Li, M
Smith, B.K
Andales, A
Brown, A.J
Topics
Education and Training in Precision Agriculture
Drainage Optimization and Variable Rate Irrigation
In-Season Nitrogen Management
Proximal and Remote Sensing of Soils and Crops (including Phenotyping)
Drainage Optimization and Variable Rate Irrigation
Type
Oral
Poster
Year
2010
2022
2024
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Filter results5 paper(s) found.

1. Isobus Demonstrator And Working Environment For Agricultural Engineering Education

ISOBUS is the international standard for communication on agricultural equipment. In practice, however, a manufacturer independent tractor-implement communication is still a significant problem. This aspect has been identified as a major hindrance for the transfer of research results into products for precision farming.  As a consequence the ISOBUS standard should strongly be included in education and research, which is the focus of this work.   In... A. Ruckelshausen, T. Dzinaj, T. Kinder, D. Bosse, R. Klose

2. Spatial Analysis of Soil Moisture and Turfgrass Health to Determine Zones for Spatially Variable Irrigation Management

The Western United States is currently experiencing a “Mega Drought”. This makes efficient water use more important than ever. Turfgrass is a major vegetation type in urban areas and performs many ecosystem services such as cooling through evapotranspiration, fixing carbon from the atmosphere and reducing wild-fire risk. There are now more acres of irrigated turfgrass (>40 million) in the USA than irrigated corn, wheat and fruit trees combined (Milesi et al., 2005). It has been... R. Kerry, S. Shumate, B. Ingram, K. Hammond, D. Gunther, R. Jensen, S. Schill, N. Hansen, B. Hopkins

3. A Digital Twin for Arable Crops and for Grass

There is an opportunity to use process-based cropping systems models (CSMs) to support tactical farm management decisions, by monitoring the status of the farm, by predicting what will happen in the next few weeks, and by exploring scenarios. In practice, the responses of a CSM will deviate more and more from reality as time progresses because the model is an abstraction of the real system and only approximates the responses of the real system. This limitation may be overcome by using the CSM... F. Van evert, P. Van oort, B. Maestrini, A. Pronk, S. Boersma, M. Kopanja, G. Mimić

4. Predicting Soil Cation Exchange Capacity from Satellite Imagery Using Random Forest Models

Crop yield variability is often attributed to spatial variation in soil properties. Remote sensing offers a practical approach to capture soil surface properties over large areas, enabling the development of detailed soil maps. This study aimed to predict cation exchange capacity (CEC), a key indicator of soil quality, in the agricultural fields of the Lower Mississippi Alluvial Valley using digital soil mapping techniques. A total of 15,586 soil samples were collected from agricultural fields... I. Muller, J. Czarnecki, M. Li, B.K. Smith

5. Apparent Soil Electrical Conductivity As an Indicator of Failed Subsurface Drains

It is estimated that 2,000 ha of cropland are taken out of production daily worldwide due to salinization and sodification. Salinity is estimated to result in economic losses of $27.3 billion U.S. dollars annually. Our project aimed to develop techniques for quantifying the severity of soil-water salinity and impacts on crop production in the Lower Arkansas River Valley (LARV) in Colorado. The Fairmont Drainage District (FDD) study site in the LARV is a furrow-irrigated, tile-drained area of about... A. Andales, A.J. Brown