An Integration Framework for Agricultural Analytics R package AgriFusionR version 0.1.0 Assembles agricultural analyses around a single unit of observation, the management unit within a season, and keeps climate, soil and remote-sensing covariates aligned to it. Covariates are aggregated over phenological windows derived from accumulated growing degree days rather than calendar months, following McMaster and Wilhelm (1997) <doi:10.1016/S0168-1923(97)00027-0>. Models are validated with spatial resampling by default, since random cross-validation inflates apparent skill when observations are spatially autocorrelated, as shown by Roberts and others (2017) <doi:10.1111/ecog.02881>. Prediction intervals use split conformal inference after Lei and others (2018) <doi:10.1080/01621459.2017.1307116>. Data sources and learning algorithms are supplied through registries so that new providers and methods can be added without modifying the package. Software Depends: R (>= 4.1.0) Imports: graphics, grDevices, stats, utils Suggests: testthat (>= 3.0.0), ranger, xgboost, Cubist, glmnet, kernlab, mgcv, treeshap, nasapower, chirps, daymetr, geodata, terra, agridat, knitr, rmarkdown Muhammad Farooqi <mqfarooqi@gmail.com> Comprehensive R Archive Network (CRAN) Muhammad Farooqi [aut, cre] (ORCID: <https://orcid.org/0000-0003-4918-9791>) MIT + file LICENSE (https://CRAN.R-project.org/package=AgriFusionR/LICENSE) 2026-08-26 application/tgz https://CRAN.R-project.org/package=AgriFusionR doi:10.32614/CRAN.package.AgriFusionR en-GB