Factor analytic mixed models for the provision of grower information from national crop variety testing programs

Abstract

V × E interaction, and the reporting of information at a regional level often masks important local V × E interaction. In contrast, the factor analytic mixed model approach that is widely used in Australian plant breeding programs, has regularly been found to provide a parsimonious and informative model for V × E effects, and accurate predictions. In this paper we develop an approach for the analysis of crop variety evaluation data that is based on a factor analytic mixed model. The information obtained from such an analysis may well be superior, but will only enhance industry productivity if mechanisms exist for successful technology transfer. With this in mind, we offer a suggested reporting format that is user-friendly and contains far greater local information for individual growers than is currently the case.

Genotype by environment interactions in forest tree breeding: review of methodology and perspectives on research and application

“…Factor analytic (FA) models can provide a reliable, parsimonious and holistic approach for estimation of genetic correlations between all pairs of trials (Cullis et al 2014;Smith et al 2015) and provide a natural framework for modelling G×E patterns in complex multi-environment experiments (Meyer 2009). The FA model is the most useful for making decisions of selection for breeding populations and decisions of deployment for production populations.…”

“…The FA models outlined above are equivalent to the extended factor analytic models specified by Meyer (2009). Latent regression plots were used to show genetic responses to trial loadings, indicating the magnitude of G×E (or stability) of selection candidates across multiple environments in the FA models (Chen et al 2017;Cullis et al 2014;Smith et al 2015; Table 1). A latent regression of a selection candidate with a higher slope means that the candidate is more sensitive to the environment.…”

Maize hybrid stability in environments under water restriction using mixed models and factor analysis

“…Figueiredo et al (2014) also found that the AF methodology can safely be used in studies of adaptability and stability in trials with a high degree of unbalanced data. Moreover, we can highlight the study of Smith et al (2015) who emphasized the superiority of this methodology for evaluation of trials in multi-environments over several years.…”

“…These measures fitted in the second step serve as parameters to evaluate the adaptability and stability (Stefanova and Buirchell, 2010) of the genotypes evaluated for recommendations (Smith et al, 2015).…”

“…Thus, it could be verified that in this study the experiments had good precision since the accuracy estimates had values of high magnitude for the characteristics evaluated (Table 1). Smith et al (2015) showed the utility of the AF models for analysis of VCU data, and although this approach is quite widespread in Australia and the United Kingdom for analysis of such data, this methodology could be more highly used in other locations.…”