A Review about Computational Methods Dedicated to Apple Fruit Diseases Detection
R. Manavalan *
Computer Science, Arignar Anna Government Arts College, Villupuram, India.
*Author to whom correspondence should be addressed.
Abstract
Agriculture is the most important sector that influences the country's economic growth. Fruits and vegetables can be an essential part of regular human diets. The fruits are rich in vitamins and minerals that help to stay healthy. Apple is the most significant fruit with an extensive list of antioxidants and vital health nutrients. Apple production is severely affected by pests and various diseases. So, the farmers severely suffer in economic losses. Hence, early detection of various diseases in apple fruit and pest control techniques is necessary to increase production. The identification of the apple leaves diseases by naked eyes leads to inaccurate control measurements of pesticides. Hence, automatic identification and early diagnosis of apple fruit diseases are necessary to increase production and quality. This article provides an overview of the various image processing techniques and machine learning approaches used to quickly obtain and examine apple fruit diseases.
Keywords: Apple, plant diseases, computational methods, SVM, CNN, neural network