Comparative Evaluation of Mango Fruit Diseases Classification Using Machine Learning

A fruit valued for its great flavor, scent, and nutritional content; the mango (Mangifera indica L.) is one of the most significant tropical fruits in the world economically. However, several illnesses that compromise fruit quality and output significantly hinder the commercial cultivation and trading of mangoes. This widespread illness has significant financial consequences and represents a danger to mango farming worldwide. A key component of effectively managing the illness and protecting crops is the timely and accurate assessment of the disease's severity. The message highlights how critical it is to detect illnesses as soon as possible and with precision to enable effective crop management. The main illnesses that afflict mango fruits are covered in detail in this document, along with information on their genesis, symptoms, epidemiology, and management techniques. The primary disorders covered are anthracnose, mango malformation, powdery mildew, mango bacterial black spot, and mango abrupt decline (mango decline-associated virus). Every disease is thoroughly investigated, covering its causes, methods of spread, symptoms, and effects on fruit output and quality. Machine learning (ML) approaches have become more effective tools for agricultural system disease detection and categorization in recent years. To shed light on the efficacy and relevance of machine learning (ML) algorithms for categorizing mango fruit illnesses, this research study compares and contrasts them.