Identification of Vegetables Diseases through Computational Approaches: A Review
R. Manavalan *
Department of Computer Science, Arignar Anna Government Arts College, Villupuram – 605 602, Tamilnadu, India.
*Author to whom correspondence should be addressed.
Abstract
The agriculture sector is closely connected with all parts of society and influences more in the country's economic growth. The vegetables and fruits are usually fortified by high sources of vitamins and minerals to stay remain healthy. Vegetable production is significantly hampered by different diseases and pests. So, farmers suffer serious economic losses. Early detection of a range of infections in vegetable plants and the appropriate pest management strategies are essential to increase productivity. Diseases on vegetables cannot be detected with the naked eye, resulting in erroneous pesticide control measurements. Thus, it is crucial to accurately identify and diagnose diseases in plants to boost productivity and quality. The numerous Image processing techniques efficiently extract features from the leaves of the vegetable and recognize the diseases at an early stage. Multiple image processing algorithms extract useful information from the leaves of vegetable plants, and this information is then utilized to identify various diseases. This article provides an overview of several specialized computational methods for diagnosing various illnesses in vegetable plant leaves. The issues that arise when using computational tools to analyze vegetable leaf diseases are also discussed, along with future directions.
Keywords: Relatives of Isoetes pantii, Plant diseases, spiny spores in lycophyta New species of lsoetes, computational approach, plant leaves, image processing, feature extraction, classification