{ "_id": "6ada683ddd3792e7732388dd", "Package": "EnvRtype", "Type": "Package", "Title": "Envirotyping for Quantitative Genetics and Plant Breeding", "Version": "0.1.3", "Authors@R": "c(\nperson(\n\"Germano\", \"Costa-Neto\",\nemail = \"germano.cneto@gmail.com\",\nrole = c(\"aut\", \"cre\")\n),\nperson(\n\"Fernanda\", \"Pontes\",\nemail = \"ferpoontes@gmail.com\",\nrole = \"aut\"\n)\n)", "Description": "An enviromics toolkit for genotype-by-environment analysis\nand envirotype-informed genomic prediction. Collects worldwide\ndaily and hourly weather from 'NASA POWER', soil profiles from\n'SoilGrids', elevation and bioclimatic layers from 'WorldClim',\nagro-ecological zones from 'FAO GAEZ', and downscaled 'CMIP6'\nclimate scenarios, with checkpointed retrieval that can resume\nafter an interrupted run. Derives agro-meteorological\nparameters (solar radiation, evapotranspiration, thermal time,\natmospheric demand), runs a FAO-56 single crop coefficient soil\nwater balance, and maps daily weather onto crop developmental\nstages. Builds environmental covariable matrices, envirotype\ntypologies and frequency matrices, mega-environment clusters,\nhistorical risk profiles and target population of environments\nweights. Reduces interval-resolved envirotypes by principal\ncomponent analysis, delineates soil zones with Gaussian mixture\nmodels, and constructs linear, Gaussian and arc-cosine\nenvironmental relatedness kernels. Fits Bayesian reaction-norm\nkernel models and predicts trained genotypes at untested\nlocations and planting dates, with coverage diagnostics,\nspatial mapping and planting-window optimisation. Simulation\nfunctions generate multi-environment trials and enviromes with\nknown architecture for power analysis. Methods are described in\nCosta-Neto, Galli, Carvalho, Crossa and Fritsche-Neto (2021)\n, and build on the Bayesian\ngenotype-by-environment kernel sampler of Granato, Cuevas,\nLuna-Vazquez, Crossa, Montesinos-Lopez, Burgueno and\nFritsche-Neto (2018) .", "License": "GPL-3", "URL": "https://github.com/gcostaneto/EnvRtype,\nhttps://gcostaneto.github.io/EnvRtype/", "BugReports": "https://github.com/gcostaneto/EnvRtype/issues", "Encoding": "UTF-8", "LazyData": "true", "Config/roxygen2/version": "8.1.0", "VignetteBuilder": "knitr", "Config/testthat/edition": "3", "NeedsCompilation": "no", "Packaged": { "Date": "2026-10-22 19:27:15 UTC", "User": "root" }, "Author": "Germano Costa-Neto [aut, cre], Fernanda Pontes [aut]", "Maintainer": "Germano Costa-Neto ", "Repository": "https://cran.r-universe.dev", "Date/Publication": "2026-10-22 19:19:55 UTC", "RemoteUrl": "https://github.com/cran/EnvRtype", "RemoteRef": "HEAD", "RemoteSha": "72678f76658ce761e8769786f4aa75b934d2a247", "_user": "cran", 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{ "page": "clay_5_15", "title": "Clay content (g/kg) from 5 to 15cm depth for Nairobi, Kenya", "topics": [ "clay_5_15" ] }, { "page": "cluster_environments", "title": "Group environments into mega-environments (clusters)", "topics": [ "cluster_environments" ] }, { "page": "coverage_summary", "title": "Summarise coverage of a scanned region", "topics": [ "coverage_summary" ] }, { "page": "decompose_kernels", "title": "Attach spectral decompositions to a list of dense kernels", "topics": [ "decompose_kernels" ] }, { "page": "env_cluster", "title": "Envirotype clustering into mega-environments", "topics": [ "env_cluster" ] }, { "page": "env_copula", "title": "Copula-based Dependence Indices for an Environmental Covariable Matrix", "topics": [ "env_copula" ] }, { "page": "env_cor", "title": "Extract the Correlation Among Environments", "topics": [ "env_cor", "env_cor.default", "env_cor.matrix", "env_cor.sim_envirome", "env_cor.sim_met", "env_cor.sim_W" ] }, { "page": "env_cor_heatmap", 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Environmental PCA", "topics": [ "env_pca_scree" ] }, { "page": "env_phenology", "title": "Thermal-Time Phenology: Map Daily Weather onto Developmental Stages", "topics": [ "env_phenology" ] }, { "page": "env_risk_profile", "title": "Historical Envirotype Risk Profile Across Years", "topics": [ "env_risk_profile" ] }, { "page": "env_target_importance", "title": "Environmental drivers of phenotypic/target clustering", "topics": [ "env_target_importance" ] }, { "page": "env_typing", "title": "Environmental Typologies based on Cardinal, Quantilic Limits or Data-Driven Mining", "topics": [ "env_typing" ] }, { "page": "G2F_2014_17", "title": "Genome to Fields (G2F) GxE panel (2014-2017)", "topics": [ "G2F_2014_17" ] }, { "page": "get_AEZ", "title": "Retrieve FAO GAEZ Agro-Ecological Zone Classification for Sites", "topics": [ "get_AEZ" ] }, { "page": "get_bioclim", "title": "WorldClim Bioclimatic Variables at Trial Sites", "topics": [ "get_bioclim" ] }, { "page": "get_climate_scenario", 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MET", "topics": [ "plot.sim_met" ] }, { "page": "plot.sim_W", "title": "Diagnostic Plot for a Simulated Envirome", "topics": [ "plot.sim_W" ] }, { "page": "print.kernel_set", "title": "Print a kernel set", "topics": [ "print.kernel_set" ] }, { "page": "print.scan_untested_envs", "title": "Print a Scan of Untested Environments", "topics": [ "print.scan_untested_envs" ] }, { "page": "print.sim_envirome", "title": "Print a Simulated Envirome Diversity Matrix", "topics": [ "print.sim_envirome" ] }, { "page": "print.sim_markers", "title": "Print a Simulated Marker Matrix", "topics": [ "print.sim_markers" ] }, { "page": "print.sim_met", "title": "Print a Simulated Multi-Environment Trial", "topics": [ "print.sim_met" ] }, { "page": "print.sim_W", "title": "Print a Simulated Envirome", "topics": [ "print.sim_W" ] }, { "page": "print.soil_gmm", "title": "Print a soil_gmm object", "topics": [ "print.soil_gmm" ] }, { "page": "print.T_matrix", "title": "Print an Envirotype (T) Matrix", "topics": [ "print.T_matrix" ] }, { "page": "processWTH", "title": "Enrich a get_weather() Output with Derived Parameters", "topics": [ "processWTH" ] }, { "page": "project_risk", "title": "Compare Envirotype Risk Between Baseline and a Climate Scenario", "topics": [ "project_risk" ] }, { "page": "read_progress_log", "title": "Inspect the Progress Log of a Checkpointed Run", "topics": [ "read_progress_log" ] }, { "page": "restart_from_log", "title": "Resume an Interrupted get_weather() or get_soil() Run", "topics": [ "restart_from_log" ] }, { "page": "scan_spatial_table", "title": "Join scan predictions to coordinates", "topics": [ "scan_spatial_table" ] }, { "page": "scan_untested_envs", "title": "Predict Trained Genotypes at Untested Environments Without Refitting", "topics": [ "scan_untested_envs" ] }, { "page": "sim_envirome", "title": "Simulate an Envirome with a Controllable Environmental Diversity", "topics": [ "sim_envirome" ] }, { "page": "sim_markers", "title": "Simulate a Marker Matrix with a Controllable Genetic Diversity", "topics": [ "sim_markers" ] }, { "page": "sim_met", "title": "Simulate a Multi-Environment Trial with a Known Genetic Architecture", "topics": [ "sim_met" ] }, { "page": "sim_met_C", "title": "Simulate a q x q Genetic Correlation Among Environments", "topics": [ "sim_met_C" ] }, { "page": "sim_W", "title": "Simulate an Envirome with a Known Relationship to an Environment Correlation", "topics": [ "sim_W" ] }, { "page": "sim_W_grid", "title": "Sweep Envirome Size and Quality (Power Analysis)", "topics": [ "sim_W_grid" ] }, { "page": "soil_classification", "title": "Delineate Soil Zones with a Gaussian Mixture Model", "topics": [ "soil_classification" ] }, { "page": "summary_water_balance", "title": "Summarise Water-Balance Output by Environment or Growth Stage", "topics": [ "summary_water_balance" ] }, { "page": "summaryWTH", "title": "Basic Summary Statistics for Environmental Data", "topics": [ "summaryWTH" ] }, { "page": "T_matrix", "title": "Envirotype Frequency Matrix, Ready for the Kernel Pipeline", "topics": [ "T_matrix" ] }, { "page": "tpe_weights", "title": "Target Population of Environments (TPE) Weights", "topics": [ "tpe_weights" ] }, { "page": "truncate_gxe_kernel", "title": "Truncate the GxE kernel to its structural rank.", "topics": [ "truncate_gxe_kernel" ] }, { "page": "undecompose_kernels", "title": "Drop cached decompositions", "topics": [ "undecompose_kernels" ] }, { "page": "varcomp_summary", "title": "Validated variance components, heritabilities and genetic correlation.", "topics": [ "varcomp_summary" ] }, { "page": "W_matrix", "title": "Build the Matrix of Environmental Covariables for Reaction Norm", "topics": [ "W_matrix" ] }, { "page": "water_balance", "title": "Daily Soil Water Balance and Crop Water-Stress Indices", "topics": [ "water_balance" ] } ], "_pkglogo": "https://github.com/cran/EnvRtype/raw/HEAD/man/figures/logo.png", "_readme": 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Pontes^[Developer, ferpoontes@gmail.com]", "engine": "knitr::rmarkdown", "headings": [ "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" ], "created": "2026-10-22 19:19:55", "modified": "2026-10-22 19:19:55", "commits": 1 } ], "_score": 3.204119982655925, "_indexed": false, "_nocasepkg": "envrtype", "_universes": [ "cran", "gcostaneto" ], "_indexurl": "https://gcostaneto.r-universe.dev/EnvRtype", "_binaries": [ { "r": "4.7.0", "os": "linux", "version": "0.1.3", "date": "2026-10-22T19:29:45.000Z", "distro": "resolute", "commit": "72678f76658ce761e8769786f4aa75b934d2a247", "fileid": "https://r2.ropensci.org/e67306f12cc48b98de538fe95f363b941bfc0c6126a18d1946467774278c288e", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/cran/actions/runs/39839656311" }, { "r": "4.6.1", "os": "linux", "version": "0.1.3", "date": "2026-10-22T19:29:48.000Z", "distro": "resolute", "commit": "72678f76658ce761e8769786f4aa75b934d2a247", "fileid": "https://r2.ropensci.org/887371e2fd36209c40a4d974bae2c984dbcd5f719aa37f9293dd716e9e9b1be1", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/cran/actions/runs/39839656311" }, { "r": "4.6.0", "os": "wasm", "version": "0.1.3", "date": "2026-10-22T19:29:54.000Z", "commit": "72678f76658ce761e8769786f4aa75b934d2a247", "fileid": "https://r2.ropensci.org/b643bf192f951da0b9662aca5183a2a41084db8fc95a953af6fd7623ea94343d", "status": "success", "buildurl": "https://github.com/r-universe/cran/actions/runs/39839656311" }, { "r": "4.7.0", "os": "win", "version": "0.1.3", "date": "2026-10-22T19:28:48.000Z", "commit": "72678f76658ce761e8769786f4aa75b934d2a247", "fileid": "https://r2.ropensci.org/fba2773a98983a22ed7092b1cb89f4b8807fa914538af9229acbe6843621f268", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/cran/actions/runs/39839656311" }, { "r": "4.6.1", "os": "win", "version": "0.1.3", "date": "2026-10-22T19:29:14.000Z", "commit": "72678f76658ce761e8769786f4aa75b934d2a247", "fileid": "https://r2.ropensci.org/46deab205871fe48654918c2caa0f470e6c488ccccfd7117935f40aa9322477f", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/cran/actions/runs/39839656311" } ] }