Health Classification System of Romaine Lettuce Plants in Hydroponic Setup Using Convolutional Neural Networks (CNN)

Hydroponics farming setup has many challenges that target the health condition of the plants, specifically romaine lettuce plants. One of the critical elements for their excellent health condition is their nutrition. Nutrients are essential components for the plant to grow, and insufficient nutrients may lead to a significant nutritional disorder that is difficult to spot during its growth stage. This may also cause marked yield and quality losses. It is also tedious to manually determine it without knowing about the plant. Plants require various ions as essential nutrients. One of the objectives of the research is to implement the convolutional neural network in determining the health condition of the leaves of the romaine lettuce. In the result of data gathering, the overall accuracy of the device in detecting and classifying leaf health is 90%. From the gathered data, the researchers have accomplished the research objectives that the proposed system can distinguish the condition of the romaine lettuce plants.

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