A comprehensive review on deep learning assisted computer vision techniques for smart greenhouse agriculture

JUM Akbar, SF Kamarulzaman, AJM Muzahid… - IEEE …, 2024 - ieeexplore.ieee.org
With the escalating global challenges of food security and resource sustainability, innovative
solutions like deep learning and computer vision are transforming agricultural practices by …

Applications, technologies, and evaluation methods in smart aquaponics: a systematic literature review

M Anila, O Daramola - Artificial Intelligence Review, 2024 - Springer
Smart aquaponics systems are gaining popularity as they contribute immensely to
sustainable food production. These systems enhance traditional farming with advanced …

Machine learning-based analysis of nutrient and water uptake in hydroponically grown soybeans

SB Dhal, S Mahanta, JMC Moore, S Kalafatis - Scientific Reports, 2024 - nature.com
Recent advancements in sustainable agriculture have spurred interest in hydroponics as an
alternative to conventional farming methods. However, the lack of data-driven approaches in …

[HTML][HTML] High-throughput analysis of leaf chlorophyll content in aquaponically grown lettuce using hyperspectral reflectance and RGB images

MF Taha, H Mao, Y Wang, AI ElManawy, G Elmasry… - Plants, 2024 - mdpi.com
Chlorophyll content reflects plants' photosynthetic capacity, growth stage, and nitrogen
status and is, therefore, of significant importance in precision agriculture. This study aims to …

Design and Development of Large-Band Dual-MSFA Sensor Camera for Precision Agriculture

V Mohammadi, P Gouton, M Rossé, KK Katakpe - Sensors, 2023 - mdpi.com
The optimal design and construction of multispectral cameras can remarkably reduce the
costs of spectral imaging systems and efficiently decrease the amount of image processing …

[HTML][HTML] Smart aquaponics: An innovative machine learning framework for fish farming optimization

A Khandakar, IM Elzein, M Nahiduzzaman… - Computers and …, 2024 - Elsevier
This study presents an innovative approach to aquaponics by integrating artificial
intelligence (AI). The system addresses sustainability challenges by utilizing a novel …

Assessing Contents of Sugars, Vitamins, and Nutrients in Baby Leaf Lettuce from Hyperspectral Data with Machine Learning Models

S Eshkabilov, I Simko - Agriculture, 2024 - mdpi.com
Lettuce (Lactuca sativa) is a leafy vegetable that provides a valuable source of
phytonutrients for a healthy human diet. The assessment of plant growth and composition is …

[PDF][PDF] Exploring Microelement Fertilization and Visible–Near-Infrared Spectroscopy for Enhanced Productivity in Capsicum annuum and Cyprinus carpio Aquaponic …

I Sirakov, S Stoyanova, K Velichkova… - Plants, 2024 - researchgate.net
This study explores the effects of varying exposure times of microelement fertilization on
hydrochemical parameters, plant growth, and nutrient content in an aquaponic system …

[PDF][PDF] Deep Learning-Enabled Dynamic Model for Nutrient Status Detection of Aquaponically Grown Plants. Agronomy 2024, 14, 2290. htps

MF Taha, H Mao, S Mousa, L Zhou… - doi. org/10.3390 …, 2024 - researchgate.net
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 …

Exploring Hyperspectral Imaging and 3D Convolutional Neural Network for Stress Classification in Plants

N Noshiri - 2023 - winnspace.uwinnipeg.ca
Hyperspectral imaging (HSI) has emerged as a transformative technology in imaging,
characterized by its ability to capture a wide spectrum of light, including wavelengths beyond …