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Image Analysis for Measuring Disease Symptom to Bacterial Soft Rot in Potato

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dc.contributor.authorLee, Unseok-
dc.contributor.authorSilva, Renato Rodrigues-
dc.contributor.authorKim, Changsoo-
dc.contributor.authorKim, Hyoungseok-
dc.contributor.authorHeo, Seong-
dc.contributor.authorPark, In Sung-
dc.contributor.authorKim, Wook-
dc.contributor.authorJansky, Shelley-
dc.contributor.authorChung, Yong Suk-
dc.date.accessioned2021-09-01T14:28:54Z-
dc.date.available2021-09-01T14:28:54Z-
dc.date.created2021-06-19-
dc.date.issued2019-06-
dc.identifier.issn1099-209X-
dc.identifier.urihttps://scholar.korea.ac.kr/handle/2021.sw.korea/65195-
dc.description.abstractBacterial 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.-
dc.languageEnglish-
dc.language.isoen-
dc.publisherSPRINGER-
dc.subjectTUBERS-
dc.subjectPECTOBACTERIUM-
dc.subjectCAROTOVORA-
dc.subjectRESISTANCE-
dc.subjectSEVERITY-
dc.titleImage Analysis for Measuring Disease Symptom to Bacterial Soft Rot in Potato-
dc.typeArticle-
dc.contributor.affiliatedAuthorKim, Wook-
dc.identifier.doi10.1007/s12230-019-09717-8-
dc.identifier.scopusid2-s2.0-85062778772-
dc.identifier.wosid000467380900010-
dc.identifier.bibliographicCitationAMERICAN JOURNAL OF POTATO RESEARCH, v.96, no.3, pp.303 - 313-
dc.relation.isPartOfAMERICAN JOURNAL OF POTATO RESEARCH-
dc.citation.titleAMERICAN JOURNAL OF POTATO RESEARCH-
dc.citation.volume96-
dc.citation.number3-
dc.citation.startPage303-
dc.citation.endPage313-
dc.type.rimsART-
dc.type.docTypeArticle-
dc.description.journalClass1-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaAgriculture-
dc.relation.journalWebOfScienceCategoryAgronomy-
dc.subject.keywordPlusTUBERS-
dc.subject.keywordPlusPECTOBACTERIUM-
dc.subject.keywordPlusCAROTOVORA-
dc.subject.keywordPlusRESISTANCE-
dc.subject.keywordPlusSEVERITY-
dc.subject.keywordAuthorHigh throughput phenotyping-
dc.subject.keywordAuthorAutomated screening-
dc.subject.keywordAuthorDigital-
dc.subject.keywordAuthorDisease-
dc.subject.keywordAuthorAccurate data-
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