Package: EnvRtype 0.1.3

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>.

Authors:Germano Costa-Neto [aut, cre], Fernanda Pontes [aut]

EnvRtype_0.1.3.tar.gz
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manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
EnvRtype/json (API)

# Install 'EnvRtype' in R:

install.packages('EnvRtype', repos = c('https://gcostaneto.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/gcostaneto/envrtype/issues

Pkgdown/docs site:https://gcostaneto.github.io

Datasets:

G2F_2014_17 - Genome to Fields
maizeG - Maize Genomic Relationship Matrix
maizeWTH - Maize Weather Data
maizeYield - Maize Phenotypic Data Set

On CRAN:

breeding-systems enviromics envirotyping genomics plant-breeding plant-breeding-data quantitative-genetics

5.65 score 7 stars 32 scripts 68 exports 23 dependencies

Last updated from:add5c59616. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel	OK	187
source / vignettes	OK	287
linux-release	OK	188
macos-release	OK	144
macos-oldrel	OK	201
windows-devel	OK	131
windows-release	OK	158
windows-oldrel	OK	125
wasm-release	OK	138

Exports:aez_default_url aez_legend best_planting_date cluster_environments coverage_summary decompose_kernels env_cluster env_copula env_cor env_cor_heatmap env_expand env_indices env_kernel env_loading_curve env_pc_associate env_pca env_pca_biplot env_pca_scree env_phenology env_risk_profile env_target_importance env_typing get_AEZ get_bioclim get_climate_scenario get_elevation get_kernel get_soil get_soil_resumable get_spatial get_weather get_weather_hourly get_weather_resumable grid_scan kernel_cv kernel_model kernel_model_clustered kernel_model_mc map_scan param_atmospheric param_radiation param_temperature phenology_templates planting_window_table plot_planting_window processWTH project_risk read_progress_log restart_from_log scan_spatial_table scan_untested_envs show_phenology sim_envirome sim_markers sim_met sim_met_C sim_W sim_W_grid soil_classification summary_water_balance summaryWTH T_matrix tpe_weights truncate_gxe_kernel undecompose_kernels varcomp_summary W_matrix water_balance

Dependencies:cli cpp11 farver ggplot2 glue gtable isoband labeling lifecycle magrittr plyr R6 RColorBrewer Rcpp reshape2 rlang S7 scales stringi stringr vctrs viridisLite withr

EnvRtype: Envirotyping for Quantitative Genetics and Plant Breeding

Rendered fromEnvRtype.Rmdusingknitr::rmarkdown

Last update: 2026-10-01
Started: 2026-09-30

Help page	Topics
Default GAEZ Download URL	aez_default_url
FAO GAEZ Agro-Ecological Zone Legend	aez_legend
Coerce a Simulated MET to a data.frame	as.data.frame.sim_met
Coerce a Simulated Envirome Diversity Matrix to a Plain Matrix	as.matrix.sim_envirome
Coerce a Simulated Envirome to a Plain Matrix	as.matrix.sim_W
Best planting date per genotype	best_planting_date
Clay content (g/kg) from 5 to 15cm depth for Nairobi, Kenya	clay_5_15
Group environments into mega-environments (clusters)	cluster_environments
Summarise coverage of a scanned region	coverage_summary
Attach spectral decompositions to a list of dense kernels	decompose_kernels
Envirotype clustering into mega-environments	env_cluster
Copula-based Dependence Indices for an Environmental Covariable Matrix	env_copula
Extract the Correlation Among Environments	env_cor env_cor.default env_cor.matrix env_cor.sim_envirome env_cor.sim_met env_cor.sim_W
Correlation Heatmap of Environmental Indices	env_cor_heatmap
Merge an environmental covariable matrix onto a phenotypic table	env_expand
Build Interval-Resolved Environmental Indices	env_indices
Easily Building of Environmental Relatedness Kernels	env_kernel
Seasonal Loading Curves of an Environmental PC	env_loading_curve
Correlate Environmental PCs with a Per-Environment Variable	env_pc_associate
PCA of Interval-Resolved Environmental Indices	env_pca
Environments in Principal Component Space	env_pca_biplot
Scree Plot of Environmental PCA	env_pca_scree
Thermal-Time Phenology: Map Daily Weather onto Developmental Stages	env_phenology
Historical Envirotype Risk Profile Across Years	env_risk_profile
Environmental drivers of phenotypic/target clustering	env_target_importance
Environmental Typologies based on Cardinal, Quantilic Limits or Data-Driven Mining	env_typing
Genome to Fields (G2F) GxE panel (2014-2017)	G2F_2014_17
Retrieve FAO GAEZ Agro-Ecological Zone Classification for Sites	get_AEZ
WorldClim Bioclimatic Variables at Trial Sites	get_bioclim
Future-Climate Envirotyping from CMIP6 Downscaled Scenarios	get_climate_scenario
Elevation at Trial Sites from WorldClim 2.1	get_elevation
Envirotype-informed Kernels for Multi-Environment Genomic Prediction	get_kernel
Collect Soil Features from SoilGrids (250 m)	get_soil
Crash-Resilient Wrapper for get_soil()	get_soil_resumable
Extract Point Estimates from Raster Files	get_spatial
Easily Collect Worldwide Daily Weather Data	get_weather
Day/Night Partitioned Hourly Weather from NASA POWER	get_weather_hourly
Crash-Resilient Wrapper for get_weather()	get_weather_resumable
Scan many sites in memory-bounded chunks	grid_scan
k-fold cross-validation predictive ability (out-of-sample)	kernel_cv
Kernel Models for Predicting Phenotypes across Multi-Environment Conditions	kernel_model
Fit kernel_model() informed by an environment-cluster table	kernel_model_clustered
Multi-chain fit with convergence diagnostics (Gelman-Rubin R-hat, ESS)	kernel_model_mc
Maize Genomic Relationship Matrix (GRM)	maizeG
Maize Weather Data	maizeWTH
Maize Phenotypic Data Set	maizeYield
Map scanned predictions, or training-network coverage	map_scan
Estimate Atmospheric Parameters Related to Evapotranspiration	param_atmospheric
Estimate Basic Solar-Radiation Parameters	param_radiation
Estimate Thermal Parameters	param_temperature
List Built-in Phenology Templates	phenology_templates show_phenology
Tabulate scan predictions against planting date	planting_window_table
Plot genotype performance across candidate planting dates	plot_planting_window
Diagnostic Plot for a Simulated MET	plot.sim_met
Diagnostic Plot for a Simulated Envirome	plot.sim_W
Print a kernel set	print.kernel_set
Print a Scan of Untested Environments	print.scan_untested_envs
Print a Simulated Envirome Diversity Matrix	print.sim_envirome
Print a Simulated Marker Matrix	print.sim_markers
Print a Simulated Multi-Environment Trial	print.sim_met
Print a Simulated Envirome	print.sim_W
Print a soil_gmm object	print.soil_gmm
Print an Envirotype (T) Matrix	print.T_matrix
Enrich a get_weather() Output with Derived Parameters	processWTH
Compare Envirotype Risk Between Baseline and a Climate Scenario	project_risk
Inspect the Progress Log of a Checkpointed Run	read_progress_log
Resume an Interrupted get_weather() or get_soil() Run	restart_from_log
Join scan predictions to coordinates	scan_spatial_table
Predict Trained Genotypes at Untested Environments Without Refitting	scan_untested_envs
Simulate an Envirome with a Controllable Environmental Diversity	sim_envirome
Simulate a Marker Matrix with a Controllable Genetic Diversity	sim_markers
Simulate a Multi-Environment Trial with a Known Genetic Architecture	sim_met
Simulate a q x q Genetic Correlation Among Environments	sim_met_C
Simulate an Envirome with a Known Relationship to an Environment Correlation	sim_W
Sweep Envirome Size and Quality (Power Analysis)	sim_W_grid
Delineate Soil Zones with a Gaussian Mixture Model	soil_classification
Summarise Water-Balance Output by Environment or Growth Stage	summary_water_balance
Basic Summary Statistics for Environmental Data	summaryWTH
Envirotype Frequency Matrix, Ready for the Kernel Pipeline	T_matrix
Target Population of Environments (TPE) Weights	tpe_weights
Truncate the GxE kernel to its structural rank.	truncate_gxe_kernel
Drop cached decompositions	undecompose_kernels
Validated variance components, heritabilities and genetic correlation.	varcomp_summary
Build the Matrix of Environmental Covariables for Reaction Norm	W_matrix
Daily Soil Water Balance and Crop Water-Stress Indices	water_balance

Package: EnvRtype 0.1.3

EnvRtype: Envirotyping for Quantitative Genetics and Plant Breeding

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