Fecha de publicación: 21/03/2023 Fuente: Wipo "precision farming" A system and method for predicting a crop yield for a type of seed in a location is described. The method includes receiving, at a client device, seasonal crop data for the type of seed, soil data associated with the location, and mapping data associated with the location. The soil data includes soil variables, and the location is represented by voxels. The seasonal crop data, the soil data and the mapping data are uploaded to a geospatial database associated with a crop prediction engine. A random forest prediction model is applied to the seasonal crop data, the soil data and mapping data in the geospatial database by the crop prediction engine, which then ranks covariates to determine one or more significant covariates. The crop prediction engine then re-applies the significant covariates to the random forest prediction model to predict the crop yield for the type of seed at the location.