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Yan, W. et Tinker, N. A. 2006. Biplot analysis of multi-environment trial data: Principles and applications. Can. J. Plant Sci. 86: 623–645. Biplot analysis has evolved into an important statistical tool in plant breeding and agricultural research. Here we review the basic principles of biplot analysis and recent developments in its application in analyzing(More)
Superior crop cultivars must be identified through multi-environment trials (MET) and on the basis of multiple traits. The objectives of this paper were to describe two types of biplots, the GGE biplot and the GT biplot, which graphically display genotype by environment data and genotype by trait data, respectively, and hence facilitate cultivar evaluation(More)
How many test locations and replications are needed in crop variety trials is a question every plant breeder has to ask. Simple formulas were developed to estimate the optimum number of replicates and test locations. The optimum number of replicates in a trial was estimated by the formula $$ {\text{N}}_{{\text{r}}} {\text{ = 3}}\left( {\sigma _{\epsilon(More)
Diallel crosses have been used in genetic research to determine the inheritance of important traits among a set of genotypes and to identify superior parents for hybrid or cultivar development. Conventional diallel analysis is limited to partitioning the total variation of the data into general combining ability (GCA) of each genotype and specific combining(More)
A physically anchored consensus map is foundational to modern genomics research; however, construction of such a map in oat (Avena sativa L., 2n = 6x = 42) has been hindered by the size and complexity of the genome, the scarcity of robust molecular markers, and the lack of aneuploid stocks. Resources developed in this study include a modified SNP discovery(More)
Due to the universal presence of genotype by environment interactions, understanding the pattern of quantitative trait loci (QTL)-by-environment interactions is a prerequisite for effective marker-assisted selection. In this report, we describe a biplot approach for investigating QTL-by-environment patterns. This approach involves two steps. It starts with(More)
Preliminary field observations in our maize breeding nurseries indicated that breeding for improved resistance to gibberella ear rot (Fusarium graminearum) in maize may indirectly select for resistance to another ear disease, common smut (Ustilago zeae). To investigate this, we compared the disease severity ratings obtained on 189 maize inbreds, eight of(More)
• To study adaptive variation and genotype × environment interactions (GE) of 30 populations from Portugal, Spain, France and Australia, we evaluated total height, diameter, stem form and survival in a multi-environment provenance trial in Portugal, 10 y after plantation, using the restricted maximum likelihood (REML) approach. • Significant differentiation(More)
Test environment evaluation has become an increasingly important issue in plant breeding. In the context of indirect selection, a test environment can be characterized by two parameters: the heritability in the test environment and its genetic correlation with the target environment. In the context of GGE biplot analysis, a test environment is similarly(More)
Six hundred thirty five oat ( L.) lines and 4561 single-nucleotide polymorphism (SNP) loci were used to evaluate population structure, linkage disequilibrium (LD), and genotype-phenotype association with heading date. The first five principal components (PCs) accounted for 25.3% of genetic variation. Neither the eigenvalues of the first 25 PCs nor the(More)