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Early Detection of Rice Blast (Pyricularia) at Seedling Stage based on Near-infrared Hyper-spectral Image

Authors:

Yang Yan,

Wang YuAuthors Info & Claims

ICBBS '19: Proceedings of the 2019 8th International Conference on Bioinformatics and Biomedical Science

Pages 64 - 68

https://doi.org/10.1145/3369166.3369185

Published: 13 January 2020 Publication History

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Abstract

Blast rice is a biological disaster in rice cultivation. Once it happens, it will reduce production at least up to 40-50%. In this study, the near-infrared hyper-spectral image was used to early detect blast rice at seedling stage. Samples were divided into two classes: infected samples and healthy samples. All of samples were imaged using Near-infrared hyper-spectral imaging system(900-1700nm). In order to detect disease, principal component analysis (PCA) was applied and linear discriminant analysis (LDA) model was built. The classification accuracy and precision of PCALDA model reach 0.92 and 0.862 on validation set. Meanwhile, five feature wavelengths (1188nm, 1339nm, 1377nm, 1432nm, 1614nm) were found and PCALDA classification model base on feature images was also built and discussed. The result showed it feasibility to early detect Rice Blast (Pyricularia) at seedling stage based on Near-infrared Hyper-Spectral Images in a quick and easy way.

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Kumar ABhowmik B(2023)Rice Cultivation and Its Disease Classification in Precision Agriculture2023 International Conference on Artificial Intelligence and Smart Communication (AISC)10.1109/AISC56616.2023.10085072(200-205)Online publication date: 27-Jan-2023
https://doi.org/10.1109/AISC56616.2023.10085072
Sethy PPandey CSahu YBehera S(2022)Hyperspectral imagery applications for precision agriculture - a systemic surveyMultimedia Tools and Applications10.1007/s11042-021-11729-881:2(3005-3038)Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.1007/s11042-021-11729-8
Arias FZambrano MBroce KMedina CPacheco HNunez Y(2021)Hyperspectral imaging for rice cultivation: Applications, methods and challengesAIMS Agriculture and Food10.3934/agrfood.20210186:1(273-307)Online publication date: 2021
https://doi.org/10.3934/agrfood.2021018

Index Terms

Early Detection of Rice Blast (Pyricularia) at Seedling Stage based on Near-infrared Hyper-spectral Image
1. Applied computing
  1. Life and medical sciences
    1. Bioinformatics

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ICBBS '19: Proceedings of the 2019 8th International Conference on Bioinformatics and Biomedical Science

October 2019

141 pages

ISBN:9781450372510

DOI:10.1145/3369166

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Beijing University of Technology
Harbin Inst. Technol.: Harbin Institute of Technology

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Published: 13 January 2020

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ICBBS 2019: 2019 8th International Conference on Bioinformatics and Biomedical Science

October 23 - 25, 2019

Beijing, China

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Kumar ABhowmik B(2023)Rice Cultivation and Its Disease Classification in Precision Agriculture2023 International Conference on Artificial Intelligence and Smart Communication (AISC)10.1109/AISC56616.2023.10085072(200-205)Online publication date: 27-Jan-2023
https://doi.org/10.1109/AISC56616.2023.10085072
Sethy PPandey CSahu YBehera S(2022)Hyperspectral imagery applications for precision agriculture - a systemic surveyMultimedia Tools and Applications10.1007/s11042-021-11729-881:2(3005-3038)Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.1007/s11042-021-11729-8
Arias FZambrano MBroce KMedina CPacheco HNunez Y(2021)Hyperspectral imaging for rice cultivation: Applications, methods and challengesAIMS Agriculture and Food10.3934/agrfood.20210186:1(273-307)Online publication date: 2021
https://doi.org/10.3934/agrfood.2021018

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Early detection of Fusarium infection in wheat using hyper-spectral imaging

Feasibility of estimating leaf water content using spectral indices from WorldView-3’s near-infrared and shortwave infrared bands

Hyperspectral detection of rice damaged by rice leaf folder (Cnaphalocrocis medinalis)

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