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Stenberg, M
Li, C
Wehrle, R
Ransom, C.J
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Authors
Wang, C
Chen, T
Dong, J
Li, C
Söderström, M
Stadig, H
Martinsson, J
Stenberg, M
Piikki, K
Ransom, C.J
Bean, M
Kitchen, N
Camberato, J
Carter, P
Ferguson, R.B
Fernandez, F.G
Franzen, D.W
Laboski, C
Nafziger, E
Sawyer, J
Shanahan, J
Ransom, C.J
Kitchen, N.R
Camberato, J.J
Carter, P.R
Ferguson, R.B
Fernandez, F.G
Franzen, D.W
Laboski, C.A
Nafziger, E.D
Shanahan, J
Sawyer, J.E
PÄTZOLD, S
Heggemann, T.W
Wehrle, R
Topics
Spatial Variability in Crop, Soil and Natural Resources
Remote Sensing Applications in Precision Agriculture
Sensor Application in Managing In-season Crop Variability
In-Season Nitrogen Management
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Type
Oral
Poster
Year
2014
2016
2018
2022
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1. Study Of Spatio-Temporal Variation Of Soil Nutrients In Paddy Rice Planting Farm

It is significant to analysis the spatial and temporal variation of soil nutrients for precision agriculture especially in large-scale farms. For the data size of soil nutrients grows once after sampling which mostly by the frequency of one year or months, to discover the changing trends of exact nutrient would be instructive for the fertilization in the future. In this study, theories of GIS and geostatistics were used to characterize the spatial and temporal variability of soil... C. Wang, T. Chen, J. Dong, C. Li

2. CropSAT - a Public Satellite-based Decision Support System for Variable-rate Nitrogen Fertilization in Scandinavia

CropSAT is a free-to-use web application for satellite-based production of variable-rate application (VRA) files of e.g. nitrogen (N) and fungicides currently available in Sweden and Denmark. Even in areas frequently covered by clouds, vegetation index maps from data derived from low-cost or freely available optical satellites can be used in practice as a cost-efficient tool in time-critical applications such as optimized nitrogen use. During the very cloudy year 2015, or more useable images... M. Söderström, H. Stadig, J. Martinsson, M. Stenberg, K. Piikki

3. Field-scale Nitrogen Recommendation Tools for Improving a Canopy Reflectance Sensor Algorithm

Nitrogen (N) rate recommendation tools are utilized to help producers maximize grain yield production. Many of these tools provide recommendations at field scales but often fail when corn N requirements are variable across the field. This may result in excess N being lost to the environment or producers receiving decreased economic returns on yield. Canopy reflectance sensors are capable of capturing within-field variability, although the sensor algorithm recommendations may not always be as accurate... C.J. Ransom, M. Bean, N. Kitchen, J. Camberato, P. Carter, R. Ferguson, F. Fernandez, D. Franzen, C. Laboski, E. Nafziger, J. Sawyer, J. Shanahan

4. Improving Corn Nitrogen Rate Recommendations Through Tool Fusion

 Improving corn (Zea maysL,) nitrogen (N) fertilizer rate recommendation tools can improve farmer’s profits and help mitigate N pollution. One way to improve N recommendation methods is to not rely on a single tool, but to employ two or more tools. Thiscould be thoughtof as “tool fusion”.The objective of this analysis was to improve N management by combining N recommendation tools used for guiding rates for an in-seasonN application. This evaluation was... C.J. Ransom, N.R. Kitchen, J.J. Camberato, P.R. Carter, R.B. Ferguson, F.G. Fernandez, D.W. Franzen, C.A. Laboski, E.D. Nafziger, J. Shanahan, J.E. Sawyer

5. On-the-go Gamma Spectrometry and Its Evaluation Via Support Vector Machines: Really a Valuable Tool for Site-independent Soil Texture Prediction?

With progressive implementation of precision agriculture (PA) techniques in current agricultural/ viticultural practice, the need for high-resolution information on soil properties at low effort and cost is increasing. Moreover, climate change and extended drought periods do even increase this demand. Evaluating soil fertility and carbon storage potential of arable fields and vineyards, e.g. for future economic assessment of ecosystem services, requires spatially resolved soil data. Soil texture... S. PÄtzold, T.W. Heggemann, R. Wehrle