A Survey on Diseases of Grape Leaf Identification Using Techniques of Machine Learning

Abstract

This paper presents a survey of different types of leaf diseases of the grapes and introduces variant kinds of techniques that are the detection of diseases. Grape diseases could cause financial losses to farmers if not detected. Grape leaves are affected by fungal infection, bacterial infection, and viral infection. Target diseases are black rot, black measles, white powdery, powdery mildew, downy mildew, and anthracnose. Detecting the diseases in leaves is the most precious method for increasing food production. It is very difficult and time-consuming to follow and test grape diseases manually. Effective detection of grape leaf diseases is crucial for preventing financial losses to farmers. This paper conducts a comprehensive survey of various grape diseases, including fungal, bacterial, and viral infections such as black rot, black measles, white powdery, powdery mildew, downy mildew, and anthracnose. To address the challenges posed by manual inspection, the paper introduces diverse techniques for disease detection. Automating this process not only enhances efficiency but also plays a pivotal role in boosting food production, emphasizing the significance of advanced methods in agriculture.