Why envirotyping | From covariables to kernels | Why the growing season must be partitioned | How the package is organised | 1 · Data acquisition | Daily weather | Hourly weather, day/night partitioned | Resumable downloads | Soil, elevation, bioclimate and zones | 2 · Processing | Agro-meteorological parameters | Summarising by environment or stage | Phenology | FAO-56 water balance | 3 · Characterisation | The environmental covariable matrix | Environmental typologies | The envirotype frequency matrix | Clustering environments into mega-environments | Which environmental factors drive a grouping | Multi-year risk profiles and TPE weights | Copula-based indices | Interval-resolved dissection and PCA | Soil zoning by Gaussian mixture | 4 · Prediction | Environmental relatedness kernels | Assembling the model | Fitting | Cross-validation | Multiple chains and clustered models | Predicting untested environments | Planting dates | 5 · Simulation | Citation | Key references

Why envirotyping | From covariables to kernels | Why the growing season must be partitioned | How the package is organised | 1 · Data acquisition | Daily weather | Hourly weather, day/night partitioned | Resumable downloads | Soil, elevation, bioclimate and zones | 2 · Processing | Agro-meteorological parameters | Summarising by environment or stage | Phenology | FAO-56 water balance | 3 · Characterisation | The environmental covariable matrix | Environmental typologies | The envirotype frequency matrix | Clustering environments into mega-environments | Which environmental factors drive a grouping | Multi-year risk profiles and TPE weights | Copula-based indices | Interval-resolved dissection and PCA | Soil zoning by Gaussian mixture | 4 · Prediction | Environmental relatedness kernels | Assembling the model | Fitting | Cross-validation | Multiple chains and clustered models | Predicting untested environments | Planting dates | 5 · Simulation | Citation | Key references