Page Banner

United States Department of Agriculture

Agricultural Research Service


item Bakhsh, A
item Colvin, Thomas
item Jaynes, Dan
item Kanwar, R
item Tim, U

Submitted to: Transactions of the ASAE
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 5/1/2000
Publication Date: 7/5/2000
Citation: Bakhsh, A., Colvin, T.S., Jaynes, D.B., Kanwar, R.S., Tim, U.S. 2000. Using soil attributes and gis for interpretation of spatial variability in yield. Transactions of the ASAE. 43(4):819-828.

Interpretive Summary: This project was conducted in central Iowa to study the relationships between soil properties and yield across a field. Yields were measured for 4 years and compared to measurements of soil properties as well as comparing the patterns in yield among years. The analyses showed a strong relationship between soil properties and yield for two of the three soil types on the field. Statistical analyses showed that equations based on texture and strength of the soil would be most likely to predict yield for the two soils. Lower yield tended to come from the same locations within the field from year to year while higher yield locations were variable. The impact of this work will lie in the potential to predict crop response based on soil properties combined with management practices and weather.

Technical Abstract: Site specific farming has the potential to increase farmers' net returns while reducing the use of agro-chemicals by applying variable rate technology for areas showing stable yield patterns. This study was designed to investigate the yield patterns using variography, seek correlation among soil attributes and yield data using GIS, and simulate the impact of N-fertilizer application rates on NO3-N losses with subsurface drainage water and crop yield for a field in central Iowa. The analysis showed that the spatial correlation lengths were found to vary from 40 m for corn to about 90 m for soybean. The lack of temporal stability in either the large-scale deterministic structure or small-scale stochastic structure revealed that yield variability was not only controlled by intrinsic soil properties but also by other extrinsic factors including climate and management. GIS analysis showed that areas of lower yield in the vicinity of Ottosen and Okoboji soils for corn were consistent from year to year whereas areas of higher yield were variable. GIS and statistical analysis both concluded that interaction of soil type and topography has influence on yield variability patterns for this field.

Last Modified: 06/27/2017
Footer Content Back to Top of Page