{"title":"Exploring the Role of Vegetation Indices in Plant Diseases Identification","authors":"Sangeeta Vaibhav Meena, V. Dhaka, Deepak Sinwar","doi":"10.1109/PDGC50313.2020.9315814","DOIUrl":null,"url":null,"abstract":"The economy of the agriculture industry is badly affected by plant diseases. Effective management practices involve regular monitoring of the plant's health with early detection of pathogens for reducing the spread of diseases. Traditionally, several invasive plant disease diagnostic techniques are used that involve the devastation of leaf samples with chemical treatment. Apart from that, non-invasive disease detection techniques are more feasible and practical ways of monitoring plant diseases in real time applications without affecting the growth of plants. Imaging and spectroscopic are non-invasive disease identification methods used for discovering harmful organisms that affect the health of plants. For identifying diseases, biophysical parameters of plants are extracted through vegetation indices. A vegetation index is a spectral computation that can be done using two or more spectral bands that are sensitive to plant vigor and biomass. Vegetation indices are used to estimate water contents of soils, monitor drought, classify vegetation, examine climate trends, crop management, identify changes in biodiversity, etc. The paper aims to discuss various methods used for detecting plant diseases. Some commonly used vegetation indices are also discussed along with the role of vegetation indices in identifying plant diseases.","PeriodicalId":347216,"journal":{"name":"2020 Sixth International Conference on Parallel, Distributed and Grid Computing (PDGC)","volume":"176 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 Sixth International Conference on Parallel, Distributed and Grid Computing (PDGC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PDGC50313.2020.9315814","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
The economy of the agriculture industry is badly affected by plant diseases. Effective management practices involve regular monitoring of the plant's health with early detection of pathogens for reducing the spread of diseases. Traditionally, several invasive plant disease diagnostic techniques are used that involve the devastation of leaf samples with chemical treatment. Apart from that, non-invasive disease detection techniques are more feasible and practical ways of monitoring plant diseases in real time applications without affecting the growth of plants. Imaging and spectroscopic are non-invasive disease identification methods used for discovering harmful organisms that affect the health of plants. For identifying diseases, biophysical parameters of plants are extracted through vegetation indices. A vegetation index is a spectral computation that can be done using two or more spectral bands that are sensitive to plant vigor and biomass. Vegetation indices are used to estimate water contents of soils, monitor drought, classify vegetation, examine climate trends, crop management, identify changes in biodiversity, etc. The paper aims to discuss various methods used for detecting plant diseases. Some commonly used vegetation indices are also discussed along with the role of vegetation indices in identifying plant diseases.