Biplot analysis has been used for studying genotype× environment interaction (GE) or any
two‐way table. Its descriptive and visualization capabilities along with the availability of user …

Germplasm from the spring wheat (Triticum aestivum L.) breeding program at the
International Center for Improvement of Maize and Wheat (CIMMYT) has had a major impact …

Recent advances in plant genomics and molecular biology have revolutionized our
understanding of plant genetics, providing new opportunities for more efficient and …

Previous papers have developed the shifted multiplicative model with one multiplieative
term (SHMM1) as a model for clustering yield trial sites or cultivars into groups in which …

Linear‐bilinear models, such as the Shifted Multiplicative Model (SHMM) and Sites
Regression Model (SREG), have been used to develop clustering procedures for finding …

Multi-environment trials (METs) in West Africa have demonstrated the existence of
genotype× environment interactions (G× E), which complicate the selection of superior …

The objective of this study was the interpretation of the genotype–environment interaction of
46 maritime pine (Pinus pinaster Ait.) provenances tested at five sites in central Spain …

Genotype× environment interaction variability can be due to crossover interaction (COI) or to
non‐COI. Statistical methods for detecting and quantifying COI and for forming subsets of …

In agriculture and plant breeding the most important genotype× environment interaction
pattern is crossover genotype× environment interaction. Procedures using linearbilinear …

Understanding the relationship among yield testing locations is important if plant breeders
are to target germplasm better to different production environments or regions. To examine …