Proceedings :: International Society of Precision Agriculture

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Sunohara, M

Schmidt, K

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Authors

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

Pätzold, S

Heggemann, T

Leenen, M

Koszinski, S

Schmidt, K

Welp, G

Topics

Decision Support Systems

Proximal and Remote Sensing of Soil and Crop (including Phenotyping)

Type

Poster

Year

2018

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Filter results3 paper(s) found.
1. 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 Download paper
2. 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 Download paper
3. Towards Universal Applicability of On-the-Go Gamma-Spectrometry for Soil Texture Estimation in Precision Farming by Using Machine Learning Applications High resolution soil data are an essential prerequisite for the application of precision farming techniques. Sensor-based evaluation of soil properties may replace or at least reduce laborious, time-consuming and expensive soil sampling with subsequent measurements in the lab. Gamma spectrometry usually provides information that can be translated into topsoil texture data after calibration. This is because the natural content of the radioactive isotopes 40-K, 232-Th, and 238-U as well... S. Pätzold, T. heggemann, M. Leenen, S. Koszinski, K. Schmidt, G. Welp Download paper

Filter results3 paper(s) found.

1. 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

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2. 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

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3. Towards Universal Applicability of On-the-Go Gamma-Spectrometry for Soil Texture Estimation in Precision Farming by Using Machine Learning Applications

High resolution soil data are an essential prerequisite for the application of precision farming techniques. Sensor-based evaluation of soil properties may replace or at least reduce laborious, time-consuming and expensive soil sampling with subsequent measurements in the lab. Gamma spectrometry usually provides information that can be translated into topsoil texture data after calibration. This is because the natural content of the radioactive isotopes 40-K, 232-Th, and 238-U as well... S. Pätzold, T. heggemann, M. Leenen, S. Koszinski, K. Schmidt, G. Welp

Download paper