Identifying and Accounting for Spatial Variability in Agricultural Experiments.

Traditionally, experiments are divided into blocks of land that are relatively uniform, treatments of interest are laid out in each block to analyze treatment differences among them.  Heterogeneity among plots within a block causes treatment differences to vary across blocks, the greater the heterogeneity within blocks, the greater the variation affects treatment estimations and therefore the poorer the precision of the study. There are many statistical methods utilized to compensate for spatial variation across the experimental region.  These methods are used to increase the precision of field experiments by adjusting yield data for spatial variability. This talk will discuss current methods to identifying and account for spatial variability in agricultural Experiments.