title: Nearest neighbour adjustment and linear variance models in plant breeding trials.
abstract: This paper reviews methods for nearest neighbour analysis that adjust for local trend in one dimension. Such methods are commonly used in plant breeding and variety testing. The focus is on simple differencing methods, including first differences and the Papadakis method. We discuss mixed model representations of these methods on the scale of the observed data. Modelling observed data has a number of practical advantages compared to differencing, for example the facility to conveniently compute adjusted cultivar means. Most models considered involve a linear variance-covariance structure and can be represented as state-space models. The reviewed methods and models are exemplified using three datasets.
authors.affiliation: Institut für Pflanzenbau und Grünland, Universität Hohenheim, Fruwirthstr. 23, Institutgebäude 211, 70593 Stuttgart, Germany. piepho@uni-hohenheim.de
authors.forename: Hans-Peter
authors.initials: HP
authors.lastname: Piepho
authors.forename: Christel
authors.initials: C
authors.lastname: Richter
authors.forename: Emlyn
authors.initials: E
authors.lastname: Williams
mesh_terms: D003627:Data Interpretation, Statistical; D008957:Models, Genetic; D015233:Models, Statistical; D010944:Plants / Q000235:genetics*