/Prototype

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Primary LanguagePython

Tip Burn Detection System in Hydroponic Lettuce Using Thresholding Method on Color Hue Saturation Value

by Abimanyu Sri Setyo, supervisors by Hurriyatul Fitriyah, S.T., M.Sc. and Rakhmadhany Primananda, S.T., M.Kom.

ABSTRACT

Lettuce is a vegetable crop with great economic potential in Indonesia. However, every year lettuce production has decreased due to disease disorders in these plants. Observation of conditions in lettuce plants can be seen in the changes that occur in lettuce leaves with direct eye sight. To speed up the handling process, a system is needed that is able to detect the presence of disease accurately. Disease detection in hydroponic lettuce is necessary to minimize the risk of crop failure in lettuce as well as a strategic control effort. The number of types of diseases in lettuce plants is quite a lot and the lack of knowledge about the symptoms of the disease makes it quite difficult for farmers to determine the type of disease that attacks. Therefore, a system is needed that is able to detect diseases on lettuce leaves, especially in hydroponic lettuce plants. Tip Burn Detection System in Hydroponic Lettuce Using Thresholding Method on Hue Saturation Value Color is used to detect tip burn disease in lettuce leaves. This study uses a camera module as input for the detection process, then the captured images are processed on a computer to obtain detection results through a user interface application. This disease detection system uses the Hue, Saturation and Value (HSV) color feature where the HSV color feature is used to analyze changes in the color of leaves infected with the disease. In the disease detection process, the thresholding segmentation method was used with the results of normal lettuce leaves and tip burn lettuce leaves. Detection of disease in hydroponic lettuce using this method using 18 test data obtains an accuracy of 94%.