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Article
Using Soil Attributes and GIS for Interpretation of Spatial Variability in Yield
Transactions of the ASAE
  • Allah Bakhsh, Iowa State University
  • Thomas S. Colvin, United States Department of Agriculture
  • Dan B. Jaynes, United States Department of Agriculture
  • Rameshwar S. Kanwar, Iowa State University
  • U. Sunday Tim, Iowa State University
Document Type
Article
Publication Date
1-1-2000
DOI
10.13031/2013.2976
Abstract

Precision farming application requires better understanding of variability in yield patterns in order to determine the cause-effect relationships. This field study was conducted to investigate the relationship between soil attributes and corn (Zea mays L.)-soybean (Glycine max L.) yield variability using four years (1995-98) yield data from a 22-ha field located in central Iowa. Corn was grown in this field during 1995, 1996, and 1998, and soybean was grown in 1997. Yield data were collected on nine east-west transects, consisting of 25-yield blocks per transect. To compare yield variability among crops and years, yield data were normalized based on N-fertilizer treatments. The soil attributes of bulk density, cone index, organic matter, aggregate uniformity coefficient, and plasticity index were determined from data collected at 42 soil sampling sites in the field. Correlation and stepwise regression analyses over all soil types in the field revealed that Tilth Index, based upon soil attributes, did not show a significant relationship with the yield data for any year and may need modifications. The regression analysis showed a significant relationship of soil attributes to yield data for areas of the field with Harps and Ottosen soils. From a geographic information system (GIS) analysis performed with ARC/INFO, it was concluded that yield may be influenced partly by management practices and partly by topography for Okoboji and Ottosen soils. Map overlay analysis showed that areas of lower yield for corn, at higher elevation, in the vicinity of Ottosen and Okoboji soils were consistent from year to year; whereas, areas of higher yield were variable. From GIS and statistical analyses, it was concluded that interaction of soil type and topography influenced yield variability of this field. These results suggest that map overlay analysis of yield data and soil attributes over longer duration can be a useful approach to delineate subareas within a field for site specific agricultural inputs by defining the appropriate yield classes.

Comments

This article is from Transactions of the ASAE 43 (2000): 819–828, doi:10.13031/2013.2976..

Rights
Works produced by employees of the U.S. Government as part of their official duties are not copyrighted within the U.S. The content of this document is not copyrighted.
Language
en
File Format
application/pdf
Citation Information
Allah Bakhsh, Thomas S. Colvin, Dan B. Jaynes, Rameshwar S. Kanwar, et al.. "Using Soil Attributes and GIS for Interpretation of Spatial Variability in Yield" Transactions of the ASAE Vol. 43 Iss. 4 (2000) p. 819 - 828
Available at: http://works.bepress.com/tim/1/