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McNairn, H
Mahjoub, O.A
Wilde, P
Waine, D
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Authors
Mahjoub, O.A
Modaihsh, A.S
Whattoff, D
Mouazen, D
Waine, D
Lilienthal, H
Wilde, P
Schnug, E
Kross, A
Kaur, G
Callegari, D
Lapen, D
Sunohara, M
McNairn, H
Rudy, H
van Vliet, L
Kross, A
Kaur, G
Znoj, E
Callegari, D
Sunohara, M
McNairn, H
Lapen, D
Rudy, H
van Vliet, L
Topics
Precision Conservation and Carbon Management
Proximal Sensing in Precision Agriculture
Decision Support Systems
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Type
Poster
Oral
Year
2012
2016
2018
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Filter results5 paper(s) found.

1. Soil Salinity, Sand Encroachment and Erosion as Indicators of Land Degradation in Harad Center, Saudi Arabia

This study presents the main results of a thorough evaluation of land degradation in Saudi Arabia (Harad Centre). The study was carried out in 2006-2007 as part of a project aimed to study features and causes of land degradation in Saudi Arabia. The study area occupies... O.A. Mahjoub, A.S. Modaihsh

2. A Multi Sensor Data Fusion Approach for Creating Variable Depth Tillage Zones.

Efficiency of tillage depends largely on the nature of the field, soil type, spatial distribution of soil properties and the correct setting of the tillage implement.  However, current tillage practice is often implemented without full understanding of machine design and capability leading to lowered efficiency and further potential damage to the soil structure. By modifying the physical properties of soil only where the tillage is needed for optimum crop growth, variable depth tillage (VDT)... D. Whattoff, D. Mouazen, D. Waine

3. Proximal Hyperspectral Sensing in Plant Breeding

The use of remote sensing in plant breeding is challenging due to the large number of small parcels which at least actually cannot be measured with conventional techniques like air- or spaceborne sensors. On the one hand crop monitoring needs to be performed frequently, which demands reliable data availability. On the other hand hyperspectral remote sensing offers new methods for the detection of vegetation parameters in crop production, especially since methods for safe and efficient detection... H. Lilienthal, P. Wilde, E. Schnug

4. Spatial Decision Support System: Controlled Tile Drainage – Calculate Your Benefits

Climate projection studies suggest that extreme heat waves and floods will become more frequent, affecting future crop yields by 20%-30%, globally. Managing vulnerability and risk begins at the farm level where best management practices can reduce the impacts associated with extreme weather events. A practice that can assist in mitigating the impact of some extreme events is controlled tile drainage (CTD). With CTD, producers use water flow control structures to manage the drainage of water from... A. Kross, G. Kaur, D. Callegari, D. Lapen, M. Sunohara, H. Mcnairn, H. Rudy, L. Van vliet

5. Evaluation of an Artificial Neural Network Approach for Prediction of Corn and Soybean Yield

The ability to predict crop yield during the growing season is important for crop income, insurance projections and for evaluating food security. Yet, modeling crop yield is challenging because of the complexity of the relationships between crop growth and the interrelated predictor variables. Artificial neural networks (ANNs) are useful for such complex systems as they can capture non-linear relationships of data without explicitly knowing the underlying processes. In this study, an ANN-based... A. Kross, G. Kaur, E. Znoj, D. Callegari, M. Sunohara, H. Mcnairn, D. Lapen, H. Rudy, L. Van vliet