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Borůvka, L
Elmore, R
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Authors
Gholizadeh, A
Saberioon, M
Borůvka, L
Licht, M.A
Lenssen, A
Elmore, R
Topics
Proximal Sensing in Precision Agriculture
Profitability, Sustainability and Adoption
Type
Oral
Year
2016
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1. Memory Based Learning: A New Data Mining Approach to Model and Interpret Soil Texture Diffuse Reflectance Spectra

Successful estimation of spectrally active soil texture with Visible and Near-Infrared (VNIR, 400-1200 nm) and Short-Wave-Infrared (SWIR, 1200-2500 nm) spectroscopy depends mostly on the selection of an appropriate data mining algorithm. The aims of this paper were: to compare different data mining algorithms including Partial Least Squares Regression (PLSR), which is the most common technique in soil spectroscopy, Support Vector Machine Regression (SVMR), Boosted Regression Trees (BRT), and Memory... A. Gholizadeh, M. Saberioon, L. Borůvka

2. Maize Seeding Rate Optimization in Iowa Using Soil and Topographic Characteristics.

The ability to collect soil, topography, and productivity information at spatial scales has become more feasible and more reliable with many advancement in precision technologies. This ability, combined with precision services and the accessibility farmers have to equipment capable implementing precision practices, has led to continued interest in making site-specific crop management decisions. The objective of this research was to utilize soil and topographic parameters to optimize seeding rates... M.A. Licht, A. Lenssen, R. Elmore