Deep Learning for Non-Invasive Diagnosis of Nutrient Deficiencies in Sugar Beet Using RGB Images

Deep Learning for Non-Invasive Diagnosis of Nutrient Deficiencies in Sugar Beet Using RGB Images

In order to enable timely actions to prevent major losses of crops caused by lack of nutrients and, hence, increase the potential yield throughout the growing season while at the same time prevent excess fertilization with detrimental environmental consequences, early, non-invasive, and on-site dete...

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Bibliographic Details
Main Authors: Jinhui Yi, Lukas Krusenbaum, Paula Unger, Hubert Hüging, Sabine J. Seidel, Gabriel Schaaf, Juergen Gall
Format: Article
Language:English
Published: MDPI AG 2020-10-01
Series:Sensors
Subjects:
nutrient deficiencies
sugar beet
deep learning
nitrogen
phosphorous
potassium
Online Access:https://www.mdpi.com/1424-8220/20/20/5893

Internet

https://www.mdpi.com/1424-8220/20/20/5893

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