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Samborski, S.M
Shi, L
Schaefer, M.T
Sisák, I
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Authors
Samborski, S.M
Gozdowski, D
Dobers, S.E
Zhang, X
Helgason, C
Seielstad, G
Shi, L
Sisák, I
Benő, A
Szabó, K
Kocsis, M
Abonyi, J
Lamb, D.W
Schaefer, M.T
Topics
Remote Sensing Applications in Precision Agriculture
Spatial and Temporal Variability in Crop, Soil and Natural Resources
Decision Support Systems
Precision Agriculture and Global Food Security
Type
Poster
Oral
Year
2010
2008
2018
2022
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1. The Use Of A Ground Based Remote Sensor For Winter Wheat Grain Yield Prediction In Northern Poland

  The aim of the research was to investigate if algorithms developed for winter wheat, cv. Trend, yield predictions, based on ground measured GNDVI, differ significantly between 2 sequent years. The research was conducted in Pomerania, northern Poland (54° 31' N 17° 18' E) on sandy loam soils. The strip-trial design was used to compare the effect of 6 N treatments: 0, 50, 100, 150, 200 and 250 kg ha-1, applied as one dose at the beginning... S.M. Samborski, D. Gozdowski, S.E. Dobers

2. Zone Mapping Application for Precision-farming: a Decision Support Tool for Variable Rate Application

We have developed a web-based decision support tool, Zone Mapping Application for Precision Farming (ZoneMAP, http://zonemap.umac.org), which can automatically determine the optimal number of management zones and delineate them using satellite imagery and field survey data provided by users. Application rates, say for fertilizer, can be prescribed for each zone and downloaded in a variety of formats to ensure compatibility with GPS-enabled farming applicators. ZoneMAP is linked to Digital Northern... X. Zhang, C. Helgason, G. Seielstad, L. Shi

3. Reverse Modelling of Yield-Influencing Soil Variables in Case of Few Soil Data

Our hypothesis was that simple models can be applied to predict yield by using only those yield data which spatially coincide with the soil data and the remaining yield data and the models can be used to test different sampling and interpolation approaches commonly applied in precision agriculture and to better predict soil variables at not observed locations. Three strategies for composite sample collection were compared in our study. Point samples were taken 1.) along lines within homogenous... I. Sisák, A. Benő, K. Szabó, M. Kocsis, J. Abonyi

4. Enhancing PA Adoption Through Value Connections

Despite an increase in breadth of precision agriculture over time, and the attendant elements of digital agriculture that either support PA or integrates the outputs of PA, the pace of adoption of digital agriculture in our farming systems remains slow. In assessing impediments to adoption of digital agriculture, much work to date has focused on the value proposition as considered by individual producers or value chain actors.  At this level, adoption remains constrained by perceptions of... D.W. Lamb, M.T. Schaefer