Diagnosing of rice nitrogen stress based on static scanning technology and image information extraction

At present, the identifying of rice nitrogen stress by the chemical analysis is time-consuming and laborious. Machine vision technology can be used to non-destructively and rapidly identify rice nitrogen status, but image acquisition via digital camera is vulnerable to external conditions, and the i...

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Autores principales:	Chen,L.S, Wang,K
Lenguaje:	English
Publicado:	Chilean Society of Soil Science / Sociedad Chilena de la Ciencia del Suelo 2014
Materias:	Static scanning rice nitrogen stress SVM LOO-CV
Acceso en línea:	http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-95162014000200010
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spelling	oai:scielo:S0718-951620140002000102014-07-30Diagnosing of rice nitrogen stress based on static scanning technology and image information extractionChen,L.SWang,K Static scanning rice nitrogen stress SVM LOO-CV At present, the identifying of rice nitrogen stress by the chemical analysis is time-consuming and laborious. Machine vision technology can be used to non-destructively and rapidly identify rice nitrogen status, but image acquisition via digital camera is vulnerable to external conditions, and the images are of poor quality. In this research static scanning technology was used to collect images of the rice's top-three leaves that were fully expand in 4 growth periods. From those images, 14 spectral and shape characteristic parameters were extracted by R, G, B mean value function and Regionprops function in MATLAB. After analyzing, the R, G, Leaf Length, LeafArea, and Leaf Perimeter were chosen as 5 universal characteristic parameters for identifying nitrogen stress in 4 growth periods. The results showed that the overall recognition accuracy of nitrogen stress were 92%, 92%, 100% and 96% respectively. Based on the result, the methodology developed in the study is capable of identifying nitrogen stress accurately in the rice.info:eu-repo/semantics/openAccessChilean Society of Soil Science / Sociedad Chilena de la Ciencia del SueloJournal of soil science and plant nutrition v.14 n.2 20142014-06-01text/htmlhttp://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-95162014000200010en10.4067/S0718-95162014005000030
institution	Scielo Chile
collection	Scielo Chile
language	English
topic	Static scanning rice nitrogen stress SVM LOO-CV
spellingShingle	Static scanning rice nitrogen stress SVM LOO-CV Chen,L.S Wang,K Diagnosing of rice nitrogen stress based on static scanning technology and image information extraction
description	At present, the identifying of rice nitrogen stress by the chemical analysis is time-consuming and laborious. Machine vision technology can be used to non-destructively and rapidly identify rice nitrogen status, but image acquisition via digital camera is vulnerable to external conditions, and the images are of poor quality. In this research static scanning technology was used to collect images of the rice's top-three leaves that were fully expand in 4 growth periods. From those images, 14 spectral and shape characteristic parameters were extracted by R, G, B mean value function and Regionprops function in MATLAB. After analyzing, the R, G, Leaf Length, LeafArea, and Leaf Perimeter were chosen as 5 universal characteristic parameters for identifying nitrogen stress in 4 growth periods. The results showed that the overall recognition accuracy of nitrogen stress were 92%, 92%, 100% and 96% respectively. Based on the result, the methodology developed in the study is capable of identifying nitrogen stress accurately in the rice.
author	Chen,L.S Wang,K
author_facet	Chen,L.S Wang,K
author_sort	Chen,L.S
title	Diagnosing of rice nitrogen stress based on static scanning technology and image information extraction
title_short	Diagnosing of rice nitrogen stress based on static scanning technology and image information extraction
title_full	Diagnosing of rice nitrogen stress based on static scanning technology and image information extraction
title_fullStr	Diagnosing of rice nitrogen stress based on static scanning technology and image information extraction
title_full_unstemmed	Diagnosing of rice nitrogen stress based on static scanning technology and image information extraction
title_sort	diagnosing of rice nitrogen stress based on static scanning technology and image information extraction
publisher	Chilean Society of Soil Science / Sociedad Chilena de la Ciencia del Suelo
publishDate	2014
url	http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-95162014000200010
work_keys_str_mv	AT chenls diagnosingofricenitrogenstressbasedonstaticscanningtechnologyandimageinformationextraction AT wangk diagnosingofricenitrogenstressbasedonstaticscanningtechnologyandimageinformationextraction
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Diagnosing of rice nitrogen stress based on static scanning technology and image information extraction

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