Genotype environment interaction in wheat including weather covariates using singular value decomposition

ABSTRACT: Wheat is a crop of significant global and Brazilian economic importance. The success of cultivation depends on several factors. Studying genotype by environment (G x E) interaction is fundamental for developing more productive and resilient varieties. Due to the climatic diversity, it is important to understand how weather covariates (WC) interact with the environments under study. To understand the complex relationships between WC and environments, it is possible to perform a graphical analysis based on the singular value decomposition (SVD) of the matrix composed by the values of the WC evaluated in the environments under study. This study proposed graphical analysis to understand the interaction between WC and evaluated environments. We used data from a randomized block design (four replications) assessed 42 wheat genotypes across 10 environments (2 years and 5 Rio Grande do Sul locations). Temperature (°C), relative humidity (%), and precipitation (mm) data were obtained from the NASA POWER project, using the experiment’s years and coordinates. The visualization of the interaction between weather covariates and environments revealed the WC that most influenced the performance of the genotypes. The environment E6 and E8 stood out for their high productivity, mainly associated with precipitation and relative humidity. This tool allows breeders to visualize the interconnection between different cultivation scenarios, obtaining valuable information for more accurate and effective decisions.