Objective and non-destructive growth measurement of cabbage [Brassica oleracea capitata] plug seedlings population using machine vision
The aim of this study is to develop an objective and non-destructive method of growth measurement of cabbage plug seedlings using a machine vision. A method of discriminant analysis was used to select the threshold value of the chromaticity g component for the objective extraction of images. The soi...
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| Veröffentlicht in: | Journal of Society of High Technology in Agriculture (Japan) 2000/03/01, Vol.12(1), pp.4-9 |
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| Sprache: | eng ; jpn |
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| container_title | Journal of Society of High Technology in Agriculture (Japan) |
| container_volume | 12 |
| creator | Suzuki, T. (Osaka-fu. Agricultural and Forestry Research Center, Habikino (Japan)) Murase, H |
| description | The aim of this study is to develop an objective and non-destructive method of growth measurement of cabbage plug seedlings using a machine vision. A method of discriminant analysis was used to select the threshold value of the chromaticity g component for the objective extraction of images. The soil coverage and standard deviation of lightness in the extracted images were calculated and inputted to a neural network model for the non-destructive measurement of the leaf area. The predicted leaf area of test plug seedlings populations based on the neural network model were fitted well with the actual values. The coefficient of determination R2 was 0.94. The leaf area of the cabbage plug seedlings population could be measured objectively and non-destructively using the machine vision. |
| doi_str_mv | 10.2525/jshita.12.4 |
| format | Article |
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(Osaka-fu. Agricultural and Forestry Research Center, Habikino (Japan)) ; Murase, H</creator><creatorcontrib>Suzuki, T. (Osaka-fu. Agricultural and Forestry Research Center, Habikino (Japan)) ; Murase, H</creatorcontrib><description>The aim of this study is to develop an objective and non-destructive method of growth measurement of cabbage plug seedlings using a machine vision. A method of discriminant analysis was used to select the threshold value of the chromaticity g component for the objective extraction of images. The soil coverage and standard deviation of lightness in the extracted images were calculated and inputted to a neural network model for the non-destructive measurement of the leaf area. The predicted leaf area of test plug seedlings populations based on the neural network model were fitted well with the actual values. The coefficient of determination R2 was 0.94. The leaf area of the cabbage plug seedlings population could be measured objectively and non-destructively using the machine vision.</description><identifier>ISSN: 0918-6638</identifier><identifier>EISSN: 1880-3555</identifier><identifier>DOI: 10.2525/jshita.12.4</identifier><language>eng ; jpn</language><publisher>JAPANESE SOCIETY OF AGRICULTURAL, BIOLOGICAL AND ENVIRONMENTAL ENGINEERS AND SCIENTISTS</publisher><subject>BRASSICA OLERACEA CAPITATA ; cabbage plug seedlings ; chromaticity g component ; CONTAINER PLANTING ; CRECIMIENTO ; CROISSANCE ; GROWTH ; MEASUREMENT ; MEDICION ; MESURE ; method of discriminant analysis ; METHODE ; METHODS ; METODOS ; neural network model ; PLANT ; PLANT POPULATION ; PLANTACION EN CONTENEDOR ; PLANTATION EN CONTAINER ; PLANTING STOCK ; PLANTON DE VIVERO ; POBLACION VEGETAL ; population ; POPULATION VEGETALE ; soil coverage ; standard deviation of lightness</subject><ispartof>Shokubutsu Kojo Gakkaishi, 2000/03/01, Vol.12(1), pp.4-9</ispartof><rights>Japanese Society of Agricultura,Biologocal and Environmental Engineers and Science</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,1883,27924,27925</link.rule.ids></links><search><creatorcontrib>Suzuki, T. (Osaka-fu. Agricultural and Forestry Research Center, Habikino (Japan))</creatorcontrib><creatorcontrib>Murase, H</creatorcontrib><title>Objective and non-destructive growth measurement of cabbage [Brassica oleracea capitata] plug seedlings population using machine vision</title><title>Journal of Society of High Technology in Agriculture (Japan)</title><addtitle>Journal of Society of High Technology in Agriculture</addtitle><description>The aim of this study is to develop an objective and non-destructive method of growth measurement of cabbage plug seedlings using a machine vision. A method of discriminant analysis was used to select the threshold value of the chromaticity g component for the objective extraction of images. The soil coverage and standard deviation of lightness in the extracted images were calculated and inputted to a neural network model for the non-destructive measurement of the leaf area. The predicted leaf area of test plug seedlings populations based on the neural network model were fitted well with the actual values. The coefficient of determination R2 was 0.94. The leaf area of the cabbage plug seedlings population could be measured objectively and non-destructively using the machine vision.</description><subject>BRASSICA OLERACEA CAPITATA</subject><subject>cabbage plug seedlings</subject><subject>chromaticity g component</subject><subject>CONTAINER PLANTING</subject><subject>CRECIMIENTO</subject><subject>CROISSANCE</subject><subject>GROWTH</subject><subject>MEASUREMENT</subject><subject>MEDICION</subject><subject>MESURE</subject><subject>method of discriminant analysis</subject><subject>METHODE</subject><subject>METHODS</subject><subject>METODOS</subject><subject>neural network model</subject><subject>PLANT</subject><subject>PLANT POPULATION</subject><subject>PLANTACION EN CONTENEDOR</subject><subject>PLANTATION EN CONTAINER</subject><subject>PLANTING STOCK</subject><subject>PLANTON DE VIVERO</subject><subject>POBLACION VEGETAL</subject><subject>population</subject><subject>POPULATION VEGETALE</subject><subject>soil coverage</subject><subject>standard deviation of lightness</subject><issn>0918-6638</issn><issn>1880-3555</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2000</creationdate><recordtype>article</recordtype><recordid>eNo9kE1LxDAQhoMouOiePAu5S9ck_cxR128W1oOeRMIkTdss3bYk6Yq_wL9tli47hxl455mXmUHoipIFS1l6u3GN8bCgbJGcoBktChLFaZqeohnhtIiyLC7O0dw5IwkhPKMZTWboby03Wnmz0xi6End9F5XaeTtOWm37H9_grQY3Wr3Vncd9hRVICbXGX_cWgp8C3LfagtIQWkNYwsM3Htqxxk7rsjVd7fDQD2ML3vQdHl1Q8BZUYzqNd8YF8RKdVdA6PT_UC_T59PixfIlW6-fX5d0qUozGSSRJDjKjjFGlyjxO4lSynCdQliqnCWdlpeKchFMrWnKZM-AVlxRYDhxSGSYu0M3kq2zvnNWVGKzZgv0VlIj9G8X0RkGZSAL9MNEb58PBRxasN6rVB5ZyTvf8ISXHtmrACt0Fm-vJpoJeQG2NE2_vjOyDZQWL_wGJxYvz</recordid><startdate>20000301</startdate><enddate>20000301</enddate><creator>Suzuki, T. (Osaka-fu. Agricultural and Forestry Research Center, Habikino (Japan))</creator><creator>Murase, H</creator><general>JAPANESE SOCIETY OF AGRICULTURAL, BIOLOGICAL AND ENVIRONMENTAL ENGINEERS AND SCIENTISTS</general><scope>FBQ</scope><scope>AAYXX</scope><scope>CITATION</scope></search><sort><creationdate>20000301</creationdate><title>Objective and non-destructive growth measurement of cabbage [Brassica oleracea capitata] plug seedlings population using machine vision</title><author>Suzuki, T. (Osaka-fu. Agricultural and Forestry Research Center, Habikino (Japan)) ; Murase, H</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c2134-b07ab61221ccd73435b2794addc71492dfc370663f1d9b72a9f9b1a27a9a5bd73</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng ; jpn</language><creationdate>2000</creationdate><topic>BRASSICA OLERACEA CAPITATA</topic><topic>cabbage plug seedlings</topic><topic>chromaticity g component</topic><topic>CONTAINER PLANTING</topic><topic>CRECIMIENTO</topic><topic>CROISSANCE</topic><topic>GROWTH</topic><topic>MEASUREMENT</topic><topic>MEDICION</topic><topic>MESURE</topic><topic>method of discriminant analysis</topic><topic>METHODE</topic><topic>METHODS</topic><topic>METODOS</topic><topic>neural network model</topic><topic>PLANT</topic><topic>PLANT POPULATION</topic><topic>PLANTACION EN CONTENEDOR</topic><topic>PLANTATION EN CONTAINER</topic><topic>PLANTING STOCK</topic><topic>PLANTON DE VIVERO</topic><topic>POBLACION VEGETAL</topic><topic>population</topic><topic>POPULATION VEGETALE</topic><topic>soil coverage</topic><topic>standard deviation of lightness</topic><toplevel>online_resources</toplevel><creatorcontrib>Suzuki, T. (Osaka-fu. Agricultural and Forestry Research Center, Habikino (Japan))</creatorcontrib><creatorcontrib>Murase, H</creatorcontrib><collection>AGRIS</collection><collection>CrossRef</collection><jtitle>Journal of Society of High Technology in Agriculture (Japan)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Suzuki, T. (Osaka-fu. Agricultural and Forestry Research Center, Habikino (Japan))</au><au>Murase, H</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Objective and non-destructive growth measurement of cabbage [Brassica oleracea capitata] plug seedlings population using machine vision</atitle><jtitle>Journal of Society of High Technology in Agriculture (Japan)</jtitle><addtitle>Journal of Society of High Technology in Agriculture</addtitle><date>2000-03-01</date><risdate>2000</risdate><volume>12</volume><issue>1</issue><spage>4</spage><epage>9</epage><pages>4-9</pages><issn>0918-6638</issn><eissn>1880-3555</eissn><abstract>The aim of this study is to develop an objective and non-destructive method of growth measurement of cabbage plug seedlings using a machine vision. A method of discriminant analysis was used to select the threshold value of the chromaticity g component for the objective extraction of images. The soil coverage and standard deviation of lightness in the extracted images were calculated and inputted to a neural network model for the non-destructive measurement of the leaf area. The predicted leaf area of test plug seedlings populations based on the neural network model were fitted well with the actual values. The coefficient of determination R2 was 0.94. The leaf area of the cabbage plug seedlings population could be measured objectively and non-destructively using the machine vision.</abstract><pub>JAPANESE SOCIETY OF AGRICULTURAL, BIOLOGICAL AND ENVIRONMENTAL ENGINEERS AND SCIENTISTS</pub><doi>10.2525/jshita.12.4</doi><tpages>6</tpages><oa>free_for_read</oa></addata></record> |
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| identifier | ISSN: 0918-6638 |
| ispartof | Shokubutsu Kojo Gakkaishi, 2000/03/01, Vol.12(1), pp.4-9 |
| issn | 0918-6638 1880-3555 |
| language | eng ; jpn |
| recordid | cdi_crossref_primary_10_2525_jshita_12_4 |
| source | J-STAGE Free; EZB-FREE-00999 freely available EZB journals |
| subjects | BRASSICA OLERACEA CAPITATA cabbage plug seedlings chromaticity g component CONTAINER PLANTING CRECIMIENTO CROISSANCE GROWTH MEASUREMENT MEDICION MESURE method of discriminant analysis METHODE METHODS METODOS neural network model PLANT PLANT POPULATION PLANTACION EN CONTENEDOR PLANTATION EN CONTAINER PLANTING STOCK PLANTON DE VIVERO POBLACION VEGETAL population POPULATION VEGETALE soil coverage standard deviation of lightness |
| title | Objective and non-destructive growth measurement of cabbage [Brassica oleracea capitata] plug seedlings population using machine vision |
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