EnvRtype - Envirotyping for Quantitative Genetics and Plant Breeding

An enviromics toolkit for genotype-by-environment analysis and envirotype-informed genomic prediction. Collects worldwide daily and hourly weather from 'NASA POWER', soil profiles from 'SoilGrids', elevation and bioclimatic layers from 'WorldClim', agro-ecological zones from 'FAO GAEZ', and downscaled 'CMIP6' climate scenarios, with checkpointed retrieval that can resume after an interrupted run. Derives agro-meteorological parameters (solar radiation, evapotranspiration, thermal time, atmospheric demand), runs a FAO-56 single crop coefficient soil water balance, and maps daily weather onto crop developmental stages. Builds environmental covariable matrices, envirotype typologies and frequency matrices, mega-environment clusters, historical risk profiles and target population of environments weights. Reduces interval-resolved envirotypes by principal component analysis, delineates soil zones with Gaussian mixture models, and constructs linear, Gaussian and arc-cosine environmental relatedness kernels. Fits Bayesian reaction-norm kernel models and predicts trained genotypes at untested locations and planting dates, with coverage diagnostics, spatial mapping and planting-window optimisation. Simulation functions generate multi-environment trials and enviromes with known architecture for power analysis. Methods are described in Costa-Neto, Galli, Carvalho, Crossa and Fritsche-Neto (2021) <doi:10.1093/g3journal/jkab040>, and build on the Bayesian genotype-by-environment kernel sampler of Granato, Cuevas, Luna-Vazquez, Crossa, Montesinos-Lopez, Burgueno and Fritsche-Neto (2018) <doi:10.1534/g3.118.200435>.