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Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/10159

Title: State-Space Approach to Spatial Variability of Crop Yield.
Authors: A. M. Al-Omran
D. R. Nielsen
K. Reichardt
C. Kirda
Issue Date: 1992
Abstract: Spatial crop yield variability complicates interpretation of field experiments if there is no information available about the spatial variability structure of the soil. Our objective was to determine, using a state-space approach, the underlying process in a soil that caused spatial yield variability of a N2-fixing crop and a nonfixing crop. On a heterogeneous soil, ryegrass (Lolium multiflorum L.) and alfalfa (Medicago sativa L.) were cropped on neighbouring transacts. Dinitrogen fixation, calculated with either the difference method or the 15N isotope dilution method and averaged across the transacts, did not differ. But, as we examined locations along the transact, differences in amount of fixed N calculated by each method became apparent. Yields of both crops showed different variability structures along the transacts. Local effective soil N content was related to local N uptake from soil and to soil symbiotic N2 fixation of alfalfa. In order to conclude this, the spatial distribution of the soil volume taken by stones in this partially rocky soil had to be considered. In stochastic (state-space) models based on spatial dependence between observations, crop yield, effective soil N, and N2 fixation were identified as first-order autoregressive processes moving through the transact. In other cases, state-space models were useful tools for spatial interpolation of plant yield, except for large yield alterations between neighbouring plots along a transact. This study showed that the spatial variability structure of yields could be explained from located field observations combined with state-space models.
URI: http://hdl.handle.net/123456789/10159
Appears in Collections:College of Foods And Agricultural Science

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