Predictive model for estimating nitrogen density in MD2 pineapple crops from multispectral images and sensors integrated in an IoT platform
ABSTRACT : Nitrogen is the most important nutritional element during the vegetative growth phase of the pineapple crop; however, its presence in the soil is insufficient to meet plant demands. In this doctoral research, nine machine learning techniques were validated to estimate total nitrogen (TN)...
- Autores:
-
Chaparro Mesa, Jorge Enrique
- Tipo de recurso:
- Doctoral thesis
- Fecha de publicación:
- 2024
- Institución:
- Universidad de Antioquia
- Repositorio:
- Repositorio UdeA
- Idioma:
- eng
- OAI Identifier:
- oai:bibliotecadigital.udea.edu.co:10495/44223
- Acceso en línea:
- https://hdl.handle.net/10495/44223
- Palabra clave:
- Técnicas de predicción
Forecasting techniques
Procesamiento de imágenes
Image processing
Internet de las cosas
Internet of things (IoT)
Multispectral Imaging
Unmanned Aerial Vehicle (UAV)
Sensors in the crop
http://aims.fao.org/aos/agrovoc/c_e4315b22
- Rights
- openAccess
- License
- https://creativecommons.org/licenses/by-nc-sa/4.0/