A Review on Artificial Intelligence Techniques for Disease Recognition in Plants. Issue 1 (January 2021)

• Record Type: Journal Article
• Authors: Singh, Taranjeet; Kumar, Krishna; Bedi, SS
• Is Part Of: IOP conference series. Volume 1022:Issue 1(2021)
• Publication Date: 2021-01
• Subjects: Artificial Intelligence -- classification -- feature extraction -- disease detection -- Image processing; Materials science -- Periodicals; 620.1105
• DOI: 10.1088/1757-899X/1022/1/012032
• Languages: English
• ISSNs: 1757-8981

Abstract

Abstract: Disease detection in crops is one of major task that every farmer practice and takes necessary action for eradicating them as they are harmful to not only crops but also to farmers, consumers, and environment too. Quality and safety of agricultural products is one of major concern in today's scenario. In earlier times farmers consults experts or use their own experience for identification of diseases in their crops but now days intelligent techniques are slowly replacing the monitoring of crops as they are more reliable, accurate, fast and economical in comparison to earlier techniques. This paper discusses few techniques based on machine learning and image processing that were presented by researchers all over the world for recognition of diseases in crops, later discussions are presented that can be helpful for improvements in this domain. This study would help other researchers and practitioners to survey various techniques used for the process of disease detection in plants and limitations of current systems.