Theoretical and Applied Genetics

, Volume 88, Issue 1, pp 33-41

First online:

Geostatistics for spatial genetic structures: study of wild populations of perennial ryegrass

  • P. MonestiezAffiliated withINRA Biométrie
  • , M. GoulardAffiliated withINRA Biométrie
  • , G. CharmetAffiliated withINRA Amélioration des Plantes

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Methods based on geostatistics were applied to quantitative traits of agricultural interest measured on a collection of 547 wild populations of perennial ryegrass in France. The mathematical background of these methods, which resembles spatial autocorrelation analysis, is briefly described. When a single variable is studied, the spatial structure analysis is similar to spatial autocorrelation analysis, and a spatial prediction method, called “kriging”, gives a filtered map of the spatial pattern over all the sampled area. When complex interactions of agronomic traits with different evaluation sites define a multivariate structure for the spatial analysis, geostatistical methods allow the spatial variations to be broken down into two main spatial structures with ranges of 120 km and 300 km, respectively. The predicted maps that corresponded to each range were interpreted as a result of the isolation-by-distance model and as a consequence of selection by environmental factors. Practical collecting methodology for breeders may be derived from such spatial structures.

Key words

Perennial ryegrass Population genetics Geostatistics Spatial autocorrelation