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Geographical Analysis of Maize Rough Dwarf Disease in the North China Plain: A Comparison of Four Spatial Regression Models

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Abstract:

Information on how maize rough dwarf disease (MRDD) is spatially concentrated by different characteristics is a key means of guiding agronomic arrangement. In particular, to reduce the spread of MRDD, it is necessary to understand the characteristics of contributors in terms of environment and their geographical structure. Here, we used 179 survey plots to investigate the spatial distributions and heterogeneity in the model residuals from four regression models with the ordinary least squares (OLS) as the benchmark. The results demonstrated that MRDD had the spatial dependency and spatial heterogeneity, and the geographically weighted regression (GWR) was the most of reliable regression models and performed well in three types of cartograms. Eight environmental factors had dissimilar influence on each county's MRDD.

Keywords: GENERALIZED LEAST SQUARES MODEL; GEOGRAPHICALLY WEIGHTED REGRESSION; MAIZE ROUGH DWARF DISEASE; ORDINARY LEAST SQUARES; SIMULTANEOUS AUTOREGRESSIVE MODEL

Document Type: Research Article

DOI: http://dx.doi.org/10.1166/sl.2012.1861

Publication date: January 1, 2012

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