The reference article of the r pakage metan
Multi-trait selection in biological experiments
Multi-environment trials (MET) are crucial steps in plant breeding programs that aim at increasing crop productivity to ensure global food security. The analysis of MET data requires the combination of several approaches including data manipulation, …
Multivariate data are common in biological experiments and using the information on multiple traits is crucial to make better decisions for treatment recommendations or genotype selection. However, identifying genotypes/treatments that combine high …
The cultivation of second-harvest with soybean crop after first-harvest with maize crop has become an alternative to aggregate income to farmers in the South region of Brazil. However, there is little information about this cropping system in this …
Additive main effect and multiplicative interaction (AMMI) and best linear unbiased prediction (BLUP) are popular methods for analyzing multi‐environment trials (MET). The AMMI has nice graphical tools for modeling genotype‐vs.‐environment …
Modeling the genotype × environment interaction (GEI) and quantifying genotypic stability are crucial steps for selecting/recommending genotypes in multi‐environment trials (METs). The efficiency in selection/recommendation could be greater if based …
textcopyright 2018 Embrapa. The objective of this work was to evaluate the consistency of the methods of Annicchiarico, Lin \& Binns, Wricke, and factor analysis in identifying eucalyptus clones with stability, adaptability, and high productive …