Using Machine-Learning Models for Field-Scale Crop Yield and Condition Modeling in Argentina
Accurately determining crop growth progress and crop yields at field-scale can help farmers estimate their net profit, enable insurance companies to ascertain payouts, and help in ensuring food security. At field scales, the troika of management, soil and weather combine to impact crop growth progre...
Guardado en:
| Autores principales: | Sahajpal, Ritvik, Fontana, Lucas, Lafluf, Pedro, Leale, Guillermo, Puricelli, Estefania, O’Neill, Dan, Hosseini, Mehdi, Varela, Mauricio, Reshef, Inbal |
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| Formato: | Objeto de conferencia |
| Lenguaje: | Inglés |
| Publicado: |
2020
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| Materias: | |
| Acceso en línea: | http://sedici.unlp.edu.ar/handle/10915/115530 |
| Aporte de: |
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