Machine learning models based on remote and proximal sensing as potential methods for in-season biomass yields prediction in commercial sorghum fields

Ephrem Habyarimana; Faheem S. Baloch

doi:10.1371/journal.pone.0249136

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Open Access

Peer-reviewed

Research Article

Machine learning models based on remote and proximal sensing as potential methods for in-season biomass yields prediction in commercial sorghum fields

Ephrem Habyarimana ,

Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing

* E-mail: ephrem.habyarimana@crea.gov.it

Affiliation CREA Research Center for Cereal and Industrial Crops, Bologna, Italy

https://orcid.org/0000-0003-2731-2744

⨯
Faheem S. Baloch

Roles Formal analysis, Visualization, Writing – review & editing

Affiliation Faculty of Agricultural Sciences and Technologies, Sivas University of Science and Technology, Sivas, Turkey
⨯

Machine learning models based on remote and proximal sensing as potential methods for in-season biomass yields prediction in commercial sorghum fields

Ephrem Habyarimana,
Faheem S. Baloch

Published: March 25, 2021
https://doi.org/10.1371/journal.pone.0249136

About the Authors

Ephrem Habyarimana

Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing

* E-mail: ephrem.habyarimana@crea.gov.it

Affiliation CREA Research Center for Cereal and Industrial Crops, Bologna, Italy

https://orcid.org/0000-0003-2731-2744

Faheem S. Baloch

Roles Formal analysis, Visualization, Writing – review & editing

Affiliation Faculty of Agricultural Sciences and Technologies, Sivas University of Science and Technology, Sivas, Turkey

Competing Interests

The authors have declared that no competing interests exist.

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Crops
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Sorghum
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Chlorophyll
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Machine learning
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Forecasting
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Neural networks
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Machine learning algorithms
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Remote sensing
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