Identification of Citrus Fruit Diseases Through Intelligent Computational Approaches: A Review

Abstract

Agriculture plays a significant role in the growth of human civilization. The fruits and vegetables are an important ingredient in the regular diets of the human. They provide high sources of vitamins and minerals that allow us to remain healthy. Citrus is used as a major source of nutrients along with vitamin C worldwide. The Citrus family consists of grapes, grapefruits, orange and lemons. The Plant diseases highly decline the growth of citrus fruits, creating a significant economic loss in agriculture. The identification of the citrus fruits leaves diseases in naked eyes leads to inaccurate results for the control measurements of pesticides. Hence, early diagnosis of diseases in citrus fruit automatically is necessary to increase the productivity. Image processing techniques are generally used to design a diagnosis system for extracting the features from the citrus plant images and identify the types of diseases at the early stage itself. This paper exhibits survey on different image processing techniques and machine learning approaches used to extract and quick examination of various citrus fruits like lemon, orange, and grapes leaves. The issues faced by the computational approaches for analyzing citrus fruits leaves are also given with future directions.