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This article in AJ

  1. Vol. 96 No. 1, p. 77-90
    Received: Nov 19, 2002

    * Corresponding author(s): replant@ucdavis.edu


Spatiotemporal Analysis of Rice Yield Variability in Two California Fields

  1. Alvaro Roelac and
  2. Richard E. Plant *b
  1. a Graduate Group in Ecol., Univ. of California, Davis, CA 95616, USA
    c Instituto Nacional de Investigaciones Agropecuarias, Treinta y Tres, Uruguay
    b Dep. of Agron. and Range Sci. and Dep. of Biol. and Agric. Eng., Univ. of California, Davis, CA 95616, USA


Currently, little is known about the spatial and temporal variability of rice (Oryza sativa L.) yield patterns. This information is needed before implementing any site-specific management strategy. The objective of this research was to characterize the spatial and temporal yield variability of rice grown in commercial fields in California. Rice cultivars M-202 and Koshihikari were grown and managed by a cooperating farmer, who collected yield monitor data over a 4-yr period. Alternative methods of data quality analysis were applied to the data. To evaluate temporal variability, yields from different years must be placed on a common grid. The appropriate size for these grids was tested. Large-scale spatial structure was determined using median polish while small-scale spatial structure was evaluated by computing variograms of the yield residuals after subtracting the trends. Temporal variability was determined using two approaches: (i) computation of the variance among years of the original, trend, and residual yield values at fixed points in the field and (ii) cluster analysis of the standardized trend yield values. Results from the study showed that the grid density necessary to capture the spatial variability depended on site and year. Trend surface spatial behaviors depended on year, indicating a lack of temporal stability. Variograms showed strong spatial structure of yield residuals. Cluster analysis reduced the considerable complexity in a sequence of yield maps of these fields to a few general patterns of variations among years.

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