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Baresel, P
Taylor, J.A
Alderman, P.D
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Authors
Baresel, P
Mistele, B
Yuncai, H
Schmidhalter, U
Hackl, H
Pasquel, D
Roux, S
Tisseyre, B
Taylor, J.A
Evers, B
Rekhi, M
Hettiarachchi, G
Welch, S
Fritz, A
Alderman, P.D
Poland, J
Topics
Sensor Application in Managing In-season Crop Variability
Geospatial Data
Type
Poster
Oral
Year
2012
2022
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Filter results3 paper(s) found.

1. A Comparison of Plant Temperatures as Measured By Thermal Imaging and Infrared Thermometry

... P. Baresel, B. Mistele, H. Yuncai, U. Schmidhalter, H. Hackl

2. Comparison of Different Aspatial and Spatial Indicators to Assess Performance of Spatialized Crop Models at Different Within-field Scales

Most current crop models are point-based models, i.e. they simulate agronomic variables on a spatial footprint on which they were initially designed (e.g. plant, field, region scale). To assess their performances, many indicators based on the comparison of estimated vs observed data, can be used such as root mean square error (RMSE) or Willmott index of agreement (D-index) among others. However, shifting model use from a strategic objective to tactical in-season management is becoming a significant... D. Pasquel, S. Roux, B. Tisseyre, J.A. Taylor

3. Using On-the-Go Soil Sensors to Assess Spatial Variability within the KS Wheat Breeding Program

In plant breeding the impacts of genotype by environment interactions and the challenges to quantify these interactions has long been recognized. Both macro and microenvironment variations in precipitation, temperature and soil nutrient availability have been shown to impact breeder selections. Traditionally, breeders mitigate these interactions by evaluating genotype performance across varying environments over multiple years. However, limitations in labor, equipment and seed availably can limit... B. Evers, M. Rekhi, G. Hettiarachchi, S. Welch, A. Fritz, P.D. Alderman, J. Poland