Combining seasonal forecasts and artificial intelligence to improve agronomy at scale

We have used the approach developed by Dorado et al. (2019) (see link provided) combined with seasonal forecasts (Esquivel et al., 2018) to produce a proof of concept where we combine seasonal forecasts and artificial intelligence prediction models for optimizing agronomic practices.

Detalles Bibliográficos
Autor principal: CGIAR Research Program on Climate Change, Agriculture and Food Security
Formato: Informe técnico
Lenguaje:Inglés
Publicado: 2019
Materias:
Acceso en línea:https://hdl.handle.net/10568/123034
Descripción
Sumario:We have used the approach developed by Dorado et al. (2019) (see link provided) combined with seasonal forecasts (Esquivel et al., 2018) to produce a proof of concept where we combine seasonal forecasts and artificial intelligence prediction models for optimizing agronomic practices.