Spatial relationships of soil properties, crop indices, and nitrogen application pattern with wheat growth and yield in a field

Ole Wendroth, K. Christian Kersebaum, G. Schwab, L. Murdock

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

4 Scopus citations


Inherent spatial variability of agricultural fields causes spatial differences in crop growth and demand of resources. Efficient use of input and minimizing the risk of environmental hazard and economical losses require appropriate concepts and tools on which to base site-specific management decisions. The objective of this study was to identify how helpful site-specific soil and crop field sampling is for explaining crop growth and yield variability, how sensitive remotely sensed crop reflectance indices are to quantify site-specific crop N demand, and how sensitive an uncalibrated crop growth simulation model (DSSAT) is to site-specific soil input. A 27-m-wide and 645-m-long strip in a farmer's field in Kentucky was planted with winter wheat. Nitrogen fertilizer was applied in 43 cells each 27 m wide and 15 m long in a sinusoidal spatial pattern. Mineral soil N was sampled site-specifically as well as aboveground plant biomass. Optical reflectance indices were monitored with two active sensors, the GreenSeeker and the Yara-ALS. Crop indices derived from sensor measurements taken in the spring reflected the grain yield patterns very well. Thus, these integrated state variables are good choices to predict site-specific yield variability and as management decision aids. Cell-specific input was given to the crop growth simulation model DSSAT 4.0. Measured state variables were compared with simulated ones. On an absolute basis, model results deviated substantially from measurements. On a relative basis, among all simulation scenarios applied here, simulated grain yield based on average soil input resulted in the highest correlation with measured grain yield. Further research with an improved calibrated, validated crop model is needed to explore the advantages of site-specific inputs for modeling.

Original languageEnglish
Title of host publicationMethods of Introducing System Models into Agricultural Research
Number of pages31
ISBN (Electronic)9780891181965
StatePublished - Oct 26 2015

Bibliographical note

Publisher Copyright:
© 2011 by American Society of Agronomy, Inc. All rights reserved.


  • Crop indices
  • Crop reflectance indices
  • Grain yield
  • Nitrogen application pattern
  • Soil properties
  • Soil variation
  • Uncalibrated crop growth simulation model
  • Wheat growth

ASJC Scopus subject areas

  • Engineering (all)
  • Agricultural and Biological Sciences (all)


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