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Borchert, A
Millett, B
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Authors
Borchert, A
Trautz, D
Olfs, H
Borchert, A
Recke, G
Dabbelt, D
Trautz, D
Olfs, H
Olfs, H
Trautz, D
Borchert, A
Kovacs, P
Maimaitijiang, M
Millett, B
Dorissant, L
Acharya, I
Janjua, U.U
Dilmurat, K
Topics
Precision Nutrient Management
Spatial Variability in Crop, Soil and Natural Resources
Big Data, Data Mining and Deep Learning
Type
Poster
Year
2012
2010
2024
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Filter results4 paper(s) found.

1. Soil pH maps Derived from On-the-Go pH-Measurements as Basis for Variable Lime Application under German Conditions: Concept Development and Evaluation in Field Trials

... A. Borchert, D. Trautz, H. Olfs

2. Economic Evaluation of a Variable Lime Application Strategy Based on Soil pH Maps Derived from On-The-Go pH-Measurements under German Conditions

... A. Borchert, G. Recke, D. Dabbelt, D. Trautz, H. Olfs

3. Validation Of On-the-go Soil Ph-measurements – Primary Results From Germany

Until recently in-field variability for soil pH could not be considered for agronomic decisions (e.g. liming rates) because reliable spatial information was hardly available. The required density of soil pH-measurements could not be achieved by manual soil sampling due to time constraints and analysis costs for the vast number of samples. A comprehensive... H. Olfs, D. Trautz, A. Borchert

4. Simultaneously Estimating Crop Biomass and Nutrient Parameters Using UAS Remote Sensing and Multitask Learning

Rapid and accurate estimation of crop growth status and nutrient levels such as aboveground biomass, nitrogen, phosphorus, and potassium concentrations and uptake is critical with respect to precision agriculture and field-based crop monitoring. Recent developments in Uncrewed Aircraft Systems (UAS) and sensor technologies have enabled the collection of high spatial, spectral, and temporal remote sensing data over large areas at a lower cost. Coupled deep learning-based modeling approaches with... P. Kovacs, M. Maimaitijiang, B. Millett, L. Dorissant, I. Acharya, U.U. Janjua, K. Dilmurat