Athira ja, Prof.K. Geetha, S. Arulraj, N. Megala, Prasa na
{"title":"Survey on Identify the Agricultural Diseases Using Image Processing and Soft Computing Techniques","authors":"Athira ja, Prof.K. Geetha, S. Arulraj, N. Megala, Prasa na","doi":"10.47059/alinteri/v36i2/ajas21130","DOIUrl":null,"url":null,"abstract":"The agricultural land mass is more than just being a feeding sourcing in today’s world. Agriculture productivity defines the economy of India in a great manner. So, in plants, disease detection plays a vital role in agriculture field. Automatic disease detection approaches are used for detecting plant diseases during the initial stages. To identify the agricultural diseases using digital image based on various features like color, textures and shape. Research firm currently doing a research to detect and diagnosis agricultural diseases based on digital image. This survey provides a better understanding of the soft computing techniques and image processing used for researcher and farmers to identify the agricultural diseases. This survey highlights several diseases of agricultural plants like rice, apple, cucumber, graphs, banana, cherry, wheat and sugarcane. And also this analysis work provides the comparison analysis of different research techniques in terms of their merits and demerits along with numerical analysis.","PeriodicalId":42396,"journal":{"name":"Alinteri Journal of Agriculture Sciences","volume":"64 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Alinteri Journal of Agriculture Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.47059/alinteri/v36i2/ajas21130","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The agricultural land mass is more than just being a feeding sourcing in today’s world. Agriculture productivity defines the economy of India in a great manner. So, in plants, disease detection plays a vital role in agriculture field. Automatic disease detection approaches are used for detecting plant diseases during the initial stages. To identify the agricultural diseases using digital image based on various features like color, textures and shape. Research firm currently doing a research to detect and diagnosis agricultural diseases based on digital image. This survey provides a better understanding of the soft computing techniques and image processing used for researcher and farmers to identify the agricultural diseases. This survey highlights several diseases of agricultural plants like rice, apple, cucumber, graphs, banana, cherry, wheat and sugarcane. And also this analysis work provides the comparison analysis of different research techniques in terms of their merits and demerits along with numerical analysis.