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ARS Home » Southeast Area » Florence, South Carolina » Coastal Plain Soil, Water and Plant Conservation Research » Research » Publications at this Location » Publication #311162
Title: Using a spatially explicit analysis model to evaluate spatial variation of corn yield

Author
item Stone, Kenneth - Ken
item Sadler, Edward

Submitted to: Meeting Proceedings
Publication Type: Proceedings
Publication Acceptance Date: 10/1/2014
Publication Date: 11/19/2014
Citation: Stone, K.C., Sadler, E.J. 2014. Using a spatially explicit analysis model to evaluate spatial variation of corn yield. In: Proceedings of the Irrigation Association International Irrigation Technical Conference, November 19-20, 2014, Phoenix, Arizona. 2014 CDROM.

Interpretive Summary:

Technical Abstract: Spatial irrigation of agricultural crops using site-specific variable-rate irrigation (VRI) systems is beginning to have wide-spread acceptance. However, optimizing the management of these VRI systems to conserve natural resources and increase profitability requires an understanding of the spatial crop responses. In this research, we utilize a recently developed spatially explicit analysis model to analyze spatial corn yield data. The specific objectives of this research are 1) to calculate a suite of estimates needed for the types of analyses mentioned above and to provide credible intervals around these estimates and 2) to examine whether the conclusions from this rigorous re-analysis are different from the prior analysis and if the results force any modifications to the conclusions obtained with the prior analyses. The model simultaneously accounted for spatial correlation as well as relationships within the treatments and has the ability to contribute information to nearby neighbors. The model-based yield estimates were in excellent agreement with the observed spatial corn yields and were able to more accurately estimate the high and low yields. After calculating estimates of yield, we then calculated estimates of other response variables such as rainfed yield, maximum yield, and irrigation at maximum yield. These estimated response variables were then compared with previous results from a classical statistical analysis. Our conclusions supported the original analysis in identifying significant spatial differences in crop responses across and within soil map units. The major improvement in the 2014 re-analysis is that the model explicitly considered the spatial dependence in calculation of the estimated yields and other variables and, thus, should provide improved estimates of their impact in system design and management.