Early detection of plant disease using close range sensing system for input into digital earth

A case study on pre-symptom stage of plant disease infection using ground based hyperspectral remote sensing was conducted. The objectives of the study are: (1) to validate the existence of pre-symptom stage of Ralstonia Solanacearum infection in Solanum Melongena L. (eggplant), and (2) to determine...

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Main Authors: Chew, W. C., Hashim, Mazlan, Lau, A. M. S., Battay, E., Kang, C. S.
Format: Conference or Workshop Item
Language:English
Published: 2013
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Online Access:http://eprints.utm.my/id/eprint/39399/1/WCChew2014_EarlyDetectionofPlantDiseaseUsingCloseRange.pdf
http://eprints.utm.my/id/eprint/39399/
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spelling my.utm.393992017-10-10T08:12:25Z http://eprints.utm.my/id/eprint/39399/ Early detection of plant disease using close range sensing system for input into digital earth Chew, W. C. Hashim, Mazlan Lau, A. M. S. Battay, E. Kang, C. S. S Agriculture A case study on pre-symptom stage of plant disease infection using ground based hyperspectral remote sensing was conducted. The objectives of the study are: (1) to validate the existence of pre-symptom stage of Ralstonia Solanacearum infection in Solanum Melongena L. (eggplant), and (2) to determine the induced electromagnetic spectral response for infected eggplant. From the experiment, the pre-symptom duration of Ralstonia Solanacearum infection in the case of eggplant was estimated (with the artificial photosynthetic stress conditions were adopted in the experiment to induce measurable changes in daily hyperspectral measurement of disease infected eggplant samples during the pre-symptom stage) as four days which is the critical period for practicing effective treatments. Vegetation indices namely, (1) Chlorophyll Absorption Integral (CAI), (2) Photochemical Radiation Index (PRI), and (3) Normalized Difference Vegetation Index (NDVI) have successfully shown noticeable progress of index value from the infected sample plant (with 100% light stress condition) throughout the study. Yet, other infected sample plants with moderate light stress conditions (50% or 75%) did not result any similar progress of index value from the daily leaf scale hyperspectral measurements. Apparently, extreme light stress can induce significant changes at visible portion in hyperspectral measurements for a disease infected eggplant during the pre-symptom stage. 2013 Conference or Workshop Item PeerReviewed application/pdf en http://eprints.utm.my/id/eprint/39399/1/WCChew2014_EarlyDetectionofPlantDiseaseUsingCloseRange.pdf Chew, W. C. and Hashim, Mazlan and Lau, A. M. S. and Battay, E. and Kang, C. S. (2013) Early detection of plant disease using close range sensing system for input into digital earth. In: 8th International Symposium on Digital, 2013.
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
language English
topic S Agriculture
spellingShingle S Agriculture
Chew, W. C.
Hashim, Mazlan
Lau, A. M. S.
Battay, E.
Kang, C. S.
Early detection of plant disease using close range sensing system for input into digital earth
description A case study on pre-symptom stage of plant disease infection using ground based hyperspectral remote sensing was conducted. The objectives of the study are: (1) to validate the existence of pre-symptom stage of Ralstonia Solanacearum infection in Solanum Melongena L. (eggplant), and (2) to determine the induced electromagnetic spectral response for infected eggplant. From the experiment, the pre-symptom duration of Ralstonia Solanacearum infection in the case of eggplant was estimated (with the artificial photosynthetic stress conditions were adopted in the experiment to induce measurable changes in daily hyperspectral measurement of disease infected eggplant samples during the pre-symptom stage) as four days which is the critical period for practicing effective treatments. Vegetation indices namely, (1) Chlorophyll Absorption Integral (CAI), (2) Photochemical Radiation Index (PRI), and (3) Normalized Difference Vegetation Index (NDVI) have successfully shown noticeable progress of index value from the infected sample plant (with 100% light stress condition) throughout the study. Yet, other infected sample plants with moderate light stress conditions (50% or 75%) did not result any similar progress of index value from the daily leaf scale hyperspectral measurements. Apparently, extreme light stress can induce significant changes at visible portion in hyperspectral measurements for a disease infected eggplant during the pre-symptom stage.
format Conference or Workshop Item
author Chew, W. C.
Hashim, Mazlan
Lau, A. M. S.
Battay, E.
Kang, C. S.
author_facet Chew, W. C.
Hashim, Mazlan
Lau, A. M. S.
Battay, E.
Kang, C. S.
author_sort Chew, W. C.
title Early detection of plant disease using close range sensing system for input into digital earth
title_short Early detection of plant disease using close range sensing system for input into digital earth
title_full Early detection of plant disease using close range sensing system for input into digital earth
title_fullStr Early detection of plant disease using close range sensing system for input into digital earth
title_full_unstemmed Early detection of plant disease using close range sensing system for input into digital earth
title_sort early detection of plant disease using close range sensing system for input into digital earth
publishDate 2013
url http://eprints.utm.my/id/eprint/39399/1/WCChew2014_EarlyDetectionofPlantDiseaseUsingCloseRange.pdf
http://eprints.utm.my/id/eprint/39399/
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score 13.211869