264-6 Relating Crop Yield Tosoil Functional Properties Created by Data Mining and Knowledge-Based Inference Soil Mapping Techniques.

Poster Number 220

See more from this Division: S05 Pedology
See more from this Session: Spatial Predictions In Soils, Crops and Agro/Forest/Urban/Wetland Ecosystems: III (Includes Graduate Student Competition)
Tuesday, October 18, 2011
Henry Gonzalez Convention Center, Hall C
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Jenette Goodman, Department of Agronomy, Purdue University, West Lafayette, IN, Phillip Owens, 915 W. State St., Purdue University, West Lafayette, IN, James J. Camberato, Agronomy, Purdue University, West Lafayette, IN and Brad Joern, Agronomy, Purdue University, W. Lafayette, IN
Available maps created by the USDA-NRCS Soil Survey illustrate soil variability based on morphologic and taxonomic variability. The mapped soil variability may not relate to a functional variability such as yield potential. The objective of this research was to 1) develop soil maps based on properties which would relate to crop growth and 2) compare the soil maps with yield data. This project involved disaggregating SSURGO soil polygons and reaggregating the data using knowledge based inference modeling (ArcSIE) to create soil property maps. These property maps included available water holding capacity, soil organic matter and depth to water table. Yield monitor data was compared to soil property maps in three locations. Including landscape properties with soil functional properties provides a better indication of water movement and availability.
See more from this Division: S05 Pedology
See more from this Session: Spatial Predictions In Soils, Crops and Agro/Forest/Urban/Wetland Ecosystems: III (Includes Graduate Student Competition)