Deep Learning-Enabled Dynamic Model for Nutrient Status Detection of Aquaponically Grown Plants

Deep Learning-Enabled Dynamic Model for Nutrient Status Detection of Aquaponically Grown Plants

Developing models to assess the nutrient status of plants at various growth stages is challenging due to the dynamic nature of plant development. Hence, this study encoded spatiotemporal information of plants within a single time-series model to precisely assess the nutrient status of aquaponically...

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Bibliographic Details
Main Authors: Mohamed Farag Taha, Hanping Mao, Samar Mousa, Lei Zhou, Yafei Wang, Gamal Elmasry, Salim Al-Rejaie, Abdallah Elshawadfy Elwakeel, Yazhou Wei, Zhengjun Qiu
Format: Article
Language:English
Published: MDPI AG 2024-10-01
Series:Agronomy
Subjects:
aquaponics
long short-term memory (LSTM)
autoencoder
convolutional neural networks (CNN)
nutrition stress
Online Access:https://www.mdpi.com/2073-4395/14/10/2290
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https://www.mdpi.com/2073-4395/14/10/2290

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