Advisor

Meng, Qingmin

Committee Member

Rodgers, John C., III

Committee Member

Cooke, William H., III

Committee Member

Brown, Michael E.

Date of Degree

1-1-2015

Document Type

Graduate Thesis - Open Access

Major

Geosciences

Degree Name

Master of Science

College

College of Arts and Sciences

Department

Department of Geosciences

Abstract

Agricultural soil properties exhibit variation over field plot scales that can ultimately effect the yield. This study performs multiple spatial pattern analyses in order to design spatially dependent regression models to better understand the interaction between these soil properties. The Cation Exchange Capacity (CEC) and Calcium-Magnesium Ratio (CaMgR) are analyzed with respect to Calcium, Magnesium, and soil moisture values. The CEC and CaMgR are then used to determine impact on the yield values present for the field. Results of this study show a significant measure of model parsimony (0.979) for the Geographically Weighted Regression (GWR) model of the CEC with free Ca, Mg, and soil moisture as explanatory variables. The model for CaMgR using the same explanatory variables has a much lower measure of model fit. The yield model using the CEC and CaMgR as explanatory variables is also low, which is representative of the underlying processes also impacting yield.

URI

https://hdl.handle.net/11668/18961

Comments

Cation Exchange Capacity||Calcium-Magnesium Ratio||agricultural soil||spatial pattern analysis||GIS

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