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Machine learning models based on remote and proximal sensing as potential methods for in-season biomass yields prediction in commercial sorghum fields
Crop yield monitoring demonstrated the potential to improve agricultural productivity through improved crop breeding, farm management and commodity planning. Remote and proximal sensing offer the possibility to cut crop monitoring costs traditionally associated with surveys and censuses. Fraction of...
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| Publicado en: | PLoS One |
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| Main Authors: | , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado: |
Public Library of Science
2021
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| Assuntos: | |
| Acceso en liña: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7993797/ https://ncbi.nlm.nih.gov/pubmed/33765103 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0249136 |
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