The analysis of crop cultivar breeding and evaluation trials: an overview of current mixed model approaches

TLDR

Crop variety trial analysis has evolved from early ANOVA approaches to modern mixed‑model methods that handle incomplete data and model within‑trial error, as outlined by Kempton and subsequent developments. This paper aims to present a general formulation that unifies all existing mixed‑model methods for series of variety trials and to examine each method in detail. The authors develop a comprehensive mixed‑model framework and then analyze individual methods within this framework.

Abstract

The analysis of series of crop variety trials has a long history with the earliest approaches being based on ANOVA methods. Kempton (1984) discussed the inadequacies of this approach, summarized the alternatives available at that time and noted that all of these approaches could be classified as multiplicative models. Recently, mixed model approaches have become popular for the analysis of series of variety trials. There are numerous reasons for their use, including the ease with which incomplete data (not all varieties in all trials) can be handled and the ability to appropriately model within-trial error variation. Currently, the most common mixed model approaches for series of variety trials are mixed model versions of the methods summarized by Kempton (1984). In the present paper a general formulation that encompasses all of these methods is described, then individual methods are considered in detail.