Advertisement

Precision Agriculture

, Volume 5, Issue 5, pp 435–444 | Cite as

Frequency Analysis of Yield for Delineating Yield Response Zones

  • K. Diker
  • D.F. Heermann
  • M.K. Brodahl
Article

Abstract

The yield in any given field or management zone is a product of interaction between many soil properties and production inputs. Therefore, multi-year yield maps may give better insight into determining potential management zones. This research was conducted to develop a methodology to delineate yield response zones by using two-state frequency analysis conducted on yield maps for 3 years on two commercial corn fields near Wiggins, Colorado. A zone was identified by the number of years that yield was equal and greater than the average yield in a given year. Classes producing statistically similar yield were combined resulting in three potential yield zones. Results indicated that the variability of yield over time and space could successfully be assessed at the same time without the drawbacks of averaging data from different years. Frequency analysis of multi-year yield data could be an effective way to establish yield response zones. Seventeen percent of the field #1 consistently produced lower yield than the mean while 43 of the field produced yield over the mean. Corresponding values for field #2 were 6% and 42%.The remainder of the fields produced fluctuating yields between years. These spatially and temporally sound yield response maps could be used to identify the yield-limiting factors in zones where yield is either low or fluctuating. Yield response maps could also be helpful to delineate potential management zones with the help of resource zones such as electrical conductivity and soil maps, along with the directed soil sampling results.

two-state frequency analysis management zones yield response zones corn 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Blackmore, S. 2000. The interpretation of trends from multiple yield maps. Computers and Electronics in Agriculture 26(1), 37-51.Google Scholar
  2. Blackmore, S., Godwin, R. J. and Fountas, S. 2003. The analysis of spatial and temporal trends in yield map data over six years. Biosystems Engineering 84(4), 455-466.Google Scholar
  3. Diker, K., Buchleiter, G. W., Farahani, H. J., Heermann, D. F. and Brodahl, M. K. 2002. Frequency analysis of yield for delineating management zones. In: CD Proceedings of the 6th International Conference on Precision Agriculture and Other Precision Resources Management, edited by P. C. Robert (ASA-CSSA-SSSA, Madison, WI, USA).Google Scholar
  4. ESRI, 1996. Working with the ArcView spatial analyst (Environmental System Research Institute, Redlands, California).Google Scholar
  5. Lark, R. M. and Stafford, J. V. 1996. Consistency and change in spatial variability of corn yield over successive seasons: methods of data analysis. In: Proceedings of the 3rd International Conference on Precision Agriculture, edited by P. C. Robert, R. H. Rust and W. E. Larson (ASA-CSSA-SSSA, Madison, WI, USA), pp. 141-149.Google Scholar
  6. Moore, S. H. and Wolcott, M. C. 2000. Using yield maps to create management zones in field crops. Louisiana Agriculture 43(3), 12-13.Google Scholar
  7. Nolan, S. C., Haverland, G. W., Goddard, T. W., Green, M., Penney, D.C., Henrikson, J. A. and Lachapelle, G. 1996. Building a yield map from geo-referenced harvest measurements. In: Proceedings of the 3rd International Conference on Precision Agriculture, edited by P. C. Robert, R. H. Rust and W. E. Larson (ASA-CSSA-SSSA, Madison, WI, USA), pp. 885-892.Google Scholar
  8. Panneton, B., Brouillard, M. and Pikutowski, T. 2001. Integration of yield data from several years into a single map. In: Proceedings of the 3rd European Conference on Precision Agriculture, edited by G. Grenier and S. Blackmore (Agro Montpellier, Montpellier, France) pp. 73-78.Google Scholar
  9. Soil Survey Staff, 1996. National Soil Survey Handbook. Title 430-VI. (USDA Natural Resources Conservation Service. U S Government Printing Office, Washington, DC. 20250).Google Scholar
  10. Stafford, J. V., Lark, R. M. and Bolam, H. C. 1999. Using yield maps to regionalize fields into potential management units. In: Proceedings of the 4th International Conference on Precision Agriculture, edited by P. C. Robert, R. H. Rust and W. E. Larson (ASA-CSSA-SSSA, Madison, WI, USA), pp. 225-237.Google Scholar
  11. Taylor, R. and Whitney, D. 2001. Using yield monitor data to direct soil sampling. http://www. oznet.ksu.edu/pr_prcag/yield-moniter.shtml. Accessed on March 13, 2001.Google Scholar
  12. Zimmerman, K. 2000. Two-State Markov chain. http//arcscripts.esri.com/details.asp?dbid= 11483. Accessed on January 20, 2002.Google Scholar

Copyright information

© Kluwer Academic Publishers 2004

Authors and Affiliations

  • K. Diker
    • 1
  • D.F. Heermann
    • 1
  • M.K. Brodahl
    • 1
  1. 1.USDA-ARS Water Manangement UnitCO

Personalised recommendations