An Algorithm Based on the RGB Colour Model to Estimate Plant Chlorophyll and Nitrogen Contents

Ali, MM; Al-Ani, A; Eamus, D; Tan, DK

An Algorithm Based on the RGB Colour Model to Estimate Plant Chlorophyll and Nitrogen Contents

Ali, MM Al-Ani, A

Eamus, D

Tan, DK

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Publisher:: International Association of Computer Science & Information Technology Press
Publication Type:: Conference Proceeding
Citation:: 2013 International Conference on Sustainable Environment and Agriculture, 2013, pp. 52 - 56
Issue Date:: 2013-01

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Field	Value	Language
dc.contributor.author	Ali, MM	en_US
dc.contributor.author	Al-Ani, A https://orcid.org/0000-0002-8092-8954	en_US
dc.contributor.author	Eamus, D https://orcid.org/0000-0003-2765-8040	en_US
dc.contributor.author	Tan, DK	en_US
dc.contributor.editor	Li Hairu	en_US
dc.date	2013-11-17	en_US
dc.date.issued	2013-01	en_US
dc.identifier.citation	2013 International Conference on Sustainable Environment and Agriculture, 2013, pp. 52 - 56	en_US
dc.identifier.uri	http://hdl.handle.net/10453/28424
dc.description.abstract	Leaf colour gives a good indication of chlorophyll (Ch) and nitrogen (N)status in plants. In this paper we developed a new, easy to use and non-destructive diagnostic approach to detect plantCh and N levels using an image processing technique developed using the RGB (Red, Green and Blue) colour model. The experiment was conducted on tomato (Tommy Toy) in field with three N treatments (0, 60 and 140 kg N / ha), where leaf images were collected using a handheld scanner. The new algorithm achieves superior correlation with the value of Ch and N, measured in laboratory, compared with the existing non-destructive methods of SPAD 502 and Dark green Colour Index (DGCI ).	en_US
dc.publisher	International Association of Computer Science & Information Technology Press	en_US
dc.relation.ispartof	2013 International Conference on Sustainable Environment and Agriculture	en_US
dc.relation.ispartof	International Conference on Sustainable Environment and Agriculture	en_US
dc.relation.isbasedon	10.7763/IPCBEE	en_US
dc.title	An Algorithm Based on the RGB Colour Model to Estimate Plant Chlorophyll and Nitrogen Contents	en_US
dc.type	Conference Proceeding
utslib.location	Singapore	en_US
utslib.location.activity	Abu Dhabi, UAE	en_US
utslib.for	0909 Geomatic Engineering	en_US
dc.location.activity	Abu Dhabi, UAE	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Biomedical Engineering
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
pubs.organisational-group	/University of Technology Sydney/Faculty of Science/School of Life Sciences
pubs.organisational-group	/University of Technology Sydney/Strength - CHT - Health Technologies
utslib.copyright.status	open_access
pubs.consider-herdc	true	en_US
pubs.finish-date	2013-11-18	en_US
pubs.place-of-publication	Singapore	en_US
pubs.start-date	2013-11-17	en_US

Abstract:

Leaf colour gives a good indication of chlorophyll (Ch) and nitrogen (N)status in plants. In this paper we developed a new, easy to use and non-destructive diagnostic approach to detect plantCh and N levels using an image processing technique developed using the RGB (Red, Green and Blue) colour model. The experiment was conducted on tomato (Tommy Toy) in field with three N treatments (0, 60 and 140 kg N / ha), where leaf images were collected using a handheld scanner. The new algorithm achieves superior correlation with the value of Ch and N, measured in laboratory, compared with the existing non-destructive methods of SPAD 502 and Dark green Colour Index (DGCI ).

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/28424