Advancing agricultural research using machine learning algorithms

Rising global population and climate change realities dictate that agricultural productivity must be accelerated. Results from current traditional research approaches are difficult to extrapolate to all possible fields because they are dependent on specific soil types, weather conditions, and backgr...

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Detalles Bibliográficos
Autores principales: Mourtzinis, Spyridon, Esker, Paul D., Specht, James E., Conley, Shawn P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8429560/
https://www.ncbi.nlm.nih.gov/pubmed/34504206
http://dx.doi.org/10.1038/s41598-021-97380-7

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8429560/
https://www.ncbi.nlm.nih.gov/pubmed/34504206
http://dx.doi.org/10.1038/s41598-021-97380-7

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