Gradient boosting and bayesian network machine learning models predict aflatoxin and fumonisin contamination of maize in Illinois – First USA case study

Mycotoxin contamination of corn results in significant agroeconomic losses and poses serious health issues worldwide. This paper presents the first report utilizing machine learning and historical aflatoxin and fumonisin contamination levels in-order-to develop models that can confidently predict my...

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Detalles Bibliográficos
Autores principales: Castano-Duque, Lina, Vaughan, Martha, Lindsay, James, Barnett, Kristin, Rajasekaran, Kanniah
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Microbiology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9684211/
https://www.ncbi.nlm.nih.gov/pubmed/36439814
http://dx.doi.org/10.3389/fmicb.2022.1039947

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9684211/
https://www.ncbi.nlm.nih.gov/pubmed/36439814
http://dx.doi.org/10.3389/fmicb.2022.1039947

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