Fruit Disease Prediction with Fertilizer Recommendation for Citrus Family using Deep Learning

Numerous diseases, including lemon canker, melanose, orange black spot, etc., harm the citrus fruit plants. Citrus canker is a contagious ailment of citrus trees that causes yellow halo lesions and scabs on the leaves or fruits. Extreme diseases have the potential to kill a person as well as damage fruit. The cancer bacteria can easily and quickly spread to plants, birds, and humans through cloths and other contaminated items. The proposed method uses effective CNN models to recognise and categorise citrus illnesses from citrus images. The automatic detection and early diagnosis of illnesses in citrus fruits for enhancing growth and quality are greatly facilitated by computational methodologies. Pre-processing, image segmentation, features extraction, and classification are the image processing methods utilised to create a diagnosis system for citrus plant diseases. In most cases, users collected images of citrus fruit and leaves from the field using sensors and cameras. The pre-processing procedures improve the images by removing noise from the ones that are captured. Analytically, CNN separates features from raw inputs. For categorization, the characteristics with highest likelihood value are picked. The sick regions’ features are extracted using feature extraction techniques. The categorization approaches are then used to identify the diseases of citrus fruit.