{'fraction_non_alphanumeric': 0.01646843549862763, 'fraction_numerical': 0.0, 'mean_word_length': 4.881720430107527, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Application of Fuzzy Logic in Plant Disease Management

The timely detection of the infection in plants and its severity is a major concern for the farmers. Although various techniques have been employed to identify and estimate the severity of infection, they generally use a fixed threshold to segment the infected areas from the leaf image. Such methods define the participation of a pixel, as part of the infected area, in the form of a classical or crisp set. Use of fuzzy logic in feature extraction, grading the disease post identification, and estimating the disease severity are seen as rapidly growing techniques. Using fuzzy logic, the infected area is calculated by considering the degree of contribution provided by neighboring pixels to the current pixel. The severity estimation is performed on the basis of the infected area and the number of lesions in the leaf image. Depending on the amount of infection, severity has been classified into early, middle, later, and advanced stage. The proposed technique will help the farmers to identify the disease class at an early stage.