Multiple-trait, random regression, and compound symmetry models for analyzing multi-environment trials in maize breeding.

An efficient and informative statistical method to analyze genotype-by-environment interaction (GxE) is needed in maize breeding programs. Thus, the objective of this study was to compare the effectiveness of multiple-trait models (MTM), random regression models (RRM), and compound symmetry models (CSM) in the analysis of multi-environment trials (MET) in maize breeding. For this, a data set with 84 maize hybrids evaluated across four environments for the trait grain yield (GY) was used.

Isolation, prevalence, and risk factors for infection by shiga toxin-producing Escherichia coli (STEC) in dairy cattle.

Rectal swabs of 198 Holstein × Gir crossbred beef cattle from 34 milk farms in the central west of Brazil were analyzed from August 2010 to February 2011. Strains of shiga toxin-producing Escherichia coli (STEC) were isolated from 72.73% (144/198) of the animals, on over 97% of the surveyed properties.