Image Analysis for Measuring Disease Symptom to Bacterial Soft Rot in Potato
Bacterial soft rot is a devastating disease in potato. However, it is difficult to evaluate disease resistance because there are a number of ways the bacterium can infect tubers, including through lenticels, in bruised tissue, and through wounds. Thus, various screening methods have been developed t...
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| Veröffentlicht in: | American journal of potato research 2019-06, Vol.96 (3), p.303-313 |
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| container_title | American journal of potato research |
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| creator | Lee, Unseok Silva, Renato Rodrigues Kim, Changsoo Kim, Hyoungseok Heo, Seong Park, In Sung Kim, Wook Jansky, Shelley Chung, Yong Suk |
| description | Bacterial soft rot is a devastating disease in potato. However, it is difficult to evaluate disease resistance because there are a number of ways the bacterium can infect tubers, including through lenticels, in bruised tissue, and through wounds. Thus, various screening methods have been developed to evaluate resistance in potato tubers. The methods published to date are limited in their ability to measure symptoms quickly and accurately in a large number of samples. Therefore, we developed a new high throughput phenotyping method to evaluate soft rot disease symptoms the assistance of image analysis software. This method has proven to be very efficient in evaluating disease symptoms. |
| doi_str_mv | 10.1007/s12230-019-09717-8 |
| format | Article |
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However, it is difficult to evaluate disease resistance because there are a number of ways the bacterium can infect tubers, including through lenticels, in bruised tissue, and through wounds. Thus, various screening methods have been developed to evaluate resistance in potato tubers. The methods published to date are limited in their ability to measure symptoms quickly and accurately in a large number of samples. Therefore, we developed a new high throughput phenotyping method to evaluate soft rot disease symptoms the assistance of image analysis software. This method has proven to be very efficient in evaluating disease symptoms.</description><identifier>ISSN: 1099-209X</identifier><identifier>EISSN: 1874-9380</identifier><identifier>DOI: 10.1007/s12230-019-09717-8</identifier><language>eng</language><publisher>New York: Springer US</publisher><subject>Agriculture ; Automation ; Bacteria ; Biomedical and Life Sciences ; Cloning ; Deep learning ; Disease resistance ; Image analysis ; Image processing ; Life Sciences ; Methods ; Phenotyping ; Plant Breeding/Biotechnology ; Plant Genetics and Genomics ; Plant Pathology ; Plant resistance ; Plant Sciences ; Potatoes ; Signs and symptoms ; Soft rot ; Software ; Tubers</subject><ispartof>American journal of potato research, 2019-06, Vol.96 (3), p.303-313</ispartof><rights>The Potato Association of America 2019</rights><rights>American Journal of Potato Research is a copyright of Springer, (2019). All Rights Reserved.</rights><rights>Copyright Springer Nature B.V. 2019</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c347t-c948e234ee0d60306985bb8c4f5366f9ea19f57e2323f783194f99f2e3b7e7023</citedby><cites>FETCH-LOGICAL-c347t-c948e234ee0d60306985bb8c4f5366f9ea19f57e2323f783194f99f2e3b7e7023</cites><orcidid>0000-0003-3121-7600</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s12230-019-09717-8$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s12230-019-09717-8$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27901,27902,41464,42533,51294</link.rule.ids></links><search><creatorcontrib>Lee, Unseok</creatorcontrib><creatorcontrib>Silva, Renato Rodrigues</creatorcontrib><creatorcontrib>Kim, Changsoo</creatorcontrib><creatorcontrib>Kim, Hyoungseok</creatorcontrib><creatorcontrib>Heo, Seong</creatorcontrib><creatorcontrib>Park, In Sung</creatorcontrib><creatorcontrib>Kim, Wook</creatorcontrib><creatorcontrib>Jansky, Shelley</creatorcontrib><creatorcontrib>Chung, Yong Suk</creatorcontrib><title>Image Analysis for Measuring Disease Symptom to Bacterial Soft Rot in Potato</title><title>American journal of potato research</title><addtitle>Am. J. Potato Res</addtitle><description>Bacterial soft rot is a devastating disease in potato. However, it is difficult to evaluate disease resistance because there are a number of ways the bacterium can infect tubers, including through lenticels, in bruised tissue, and through wounds. Thus, various screening methods have been developed to evaluate resistance in potato tubers. The methods published to date are limited in their ability to measure symptoms quickly and accurately in a large number of samples. Therefore, we developed a new high throughput phenotyping method to evaluate soft rot disease symptoms the assistance of image analysis software. This method has proven to be very efficient in evaluating disease symptoms.</description><subject>Agriculture</subject><subject>Automation</subject><subject>Bacteria</subject><subject>Biomedical and Life Sciences</subject><subject>Cloning</subject><subject>Deep learning</subject><subject>Disease resistance</subject><subject>Image analysis</subject><subject>Image processing</subject><subject>Life Sciences</subject><subject>Methods</subject><subject>Phenotyping</subject><subject>Plant Breeding/Biotechnology</subject><subject>Plant Genetics and Genomics</subject><subject>Plant Pathology</subject><subject>Plant resistance</subject><subject>Plant Sciences</subject><subject>Potatoes</subject><subject>Signs and symptoms</subject><subject>Soft rot</subject><subject>Software</subject><subject>Tubers</subject><issn>1099-209X</issn><issn>1874-9380</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><recordid>eNp9kEtLAzEUhYMoWKt_wFXAdfTmMZNkWeurUFGsgruQjkmZ0mnGJLPov3fqCO66umfxnQP3Q-iSwjUFkDeJMsaBANUEtKSSqCM0okoKormC4z6D1oSB_jxFZymtARhlqhih-ayxK4cnW7vZpTphHyJ-djZ1sd6u8F2d-uzwYte0OTQ4B3xrq-xibTd4EXzGbyHjeotfQ7Y5nKMTbzfJXfzdMfp4uH-fPpH5y-NsOpmTiguZSaWFcowL5-CrBA6lVsVyqSrhC16WXjtLtS9kjzDupeJUC6-1Z44vpZPA-BhdDbttDN-dS9msQxf7F5JhjFEOUihxkKJKU841hZ5iA1XFkFJ03rSxbmzcGQpm79YMbk3v1vy6Naov8aGU2r0nF_-nD7R-AG0vees</recordid><startdate>20190601</startdate><enddate>20190601</enddate><creator>Lee, Unseok</creator><creator>Silva, Renato Rodrigues</creator><creator>Kim, Changsoo</creator><creator>Kim, Hyoungseok</creator><creator>Heo, Seong</creator><creator>Park, In Sung</creator><creator>Kim, Wook</creator><creator>Jansky, Shelley</creator><creator>Chung, Yong Suk</creator><general>Springer US</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><orcidid>https://orcid.org/0000-0003-3121-7600</orcidid></search><sort><creationdate>20190601</creationdate><title>Image Analysis for Measuring Disease Symptom to Bacterial Soft Rot in Potato</title><author>Lee, Unseok ; Silva, Renato Rodrigues ; Kim, Changsoo ; Kim, Hyoungseok ; Heo, Seong ; Park, In Sung ; Kim, Wook ; Jansky, Shelley ; Chung, Yong Suk</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c347t-c948e234ee0d60306985bb8c4f5366f9ea19f57e2323f783194f99f2e3b7e7023</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Agriculture</topic><topic>Automation</topic><topic>Bacteria</topic><topic>Biomedical and Life Sciences</topic><topic>Cloning</topic><topic>Deep learning</topic><topic>Disease resistance</topic><topic>Image analysis</topic><topic>Image processing</topic><topic>Life Sciences</topic><topic>Methods</topic><topic>Phenotyping</topic><topic>Plant Breeding/Biotechnology</topic><topic>Plant Genetics and Genomics</topic><topic>Plant Pathology</topic><topic>Plant resistance</topic><topic>Plant Sciences</topic><topic>Potatoes</topic><topic>Signs and symptoms</topic><topic>Soft rot</topic><topic>Software</topic><topic>Tubers</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Lee, Unseok</creatorcontrib><creatorcontrib>Silva, Renato Rodrigues</creatorcontrib><creatorcontrib>Kim, Changsoo</creatorcontrib><creatorcontrib>Kim, Hyoungseok</creatorcontrib><creatorcontrib>Heo, Seong</creatorcontrib><creatorcontrib>Park, In Sung</creatorcontrib><creatorcontrib>Kim, Wook</creatorcontrib><creatorcontrib>Jansky, Shelley</creatorcontrib><creatorcontrib>Chung, Yong Suk</creatorcontrib><collection>CrossRef</collection><jtitle>American journal of potato research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Lee, Unseok</au><au>Silva, Renato Rodrigues</au><au>Kim, Changsoo</au><au>Kim, Hyoungseok</au><au>Heo, Seong</au><au>Park, In Sung</au><au>Kim, Wook</au><au>Jansky, Shelley</au><au>Chung, Yong Suk</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Image Analysis for Measuring Disease Symptom to Bacterial Soft Rot in Potato</atitle><jtitle>American journal of potato research</jtitle><stitle>Am. J. Potato Res</stitle><date>2019-06-01</date><risdate>2019</risdate><volume>96</volume><issue>3</issue><spage>303</spage><epage>313</epage><pages>303-313</pages><issn>1099-209X</issn><eissn>1874-9380</eissn><abstract>Bacterial soft rot is a devastating disease in potato. However, it is difficult to evaluate disease resistance because there are a number of ways the bacterium can infect tubers, including through lenticels, in bruised tissue, and through wounds. Thus, various screening methods have been developed to evaluate resistance in potato tubers. The methods published to date are limited in their ability to measure symptoms quickly and accurately in a large number of samples. Therefore, we developed a new high throughput phenotyping method to evaluate soft rot disease symptoms the assistance of image analysis software. 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| language | eng |
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| subjects | Agriculture Automation Bacteria Biomedical and Life Sciences Cloning Deep learning Disease resistance Image analysis Image processing Life Sciences Methods Phenotyping Plant Breeding/Biotechnology Plant Genetics and Genomics Plant Pathology Plant resistance Plant Sciences Potatoes Signs and symptoms Soft rot Software Tubers |
| title | Image Analysis for Measuring Disease Symptom to Bacterial Soft Rot in Potato |
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