Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Lee, Unseok | - |
dc.contributor.author | Silva, Renato Rodrigues | - |
dc.contributor.author | Kim, Changsoo | - |
dc.contributor.author | Kim, Hyoungseok | - |
dc.contributor.author | Heo, Seong | - |
dc.contributor.author | Park, In Sung | - |
dc.contributor.author | Kim, Wook | - |
dc.contributor.author | Jansky, Shelley | - |
dc.contributor.author | Chung, Yong Suk | - |
dc.date.accessioned | 2024-01-19T20:02:03Z | - |
dc.date.available | 2024-01-19T20:02:03Z | - |
dc.date.created | 2021-09-02 | - |
dc.date.issued | 2019-06 | - |
dc.identifier.issn | 1099-209X | - |
dc.identifier.uri | https://pubs.kist.re.kr/handle/201004/119959 | - |
dc.description.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. This method has proven to be very efficient in evaluating disease symptoms. | - |
dc.language | English | - |
dc.publisher | SPRINGER | - |
dc.title | Image Analysis for Measuring Disease Symptom to Bacterial Soft Rot in Potato | - |
dc.type | Article | - |
dc.identifier.doi | 10.1007/s12230-019-09717-8 | - |
dc.description.journalClass | 1 | - |
dc.identifier.bibliographicCitation | AMERICAN JOURNAL OF POTATO RESEARCH, v.96, no.3, pp.303 - 313 | - |
dc.citation.title | AMERICAN JOURNAL OF POTATO RESEARCH | - |
dc.citation.volume | 96 | - |
dc.citation.number | 3 | - |
dc.citation.startPage | 303 | - |
dc.citation.endPage | 313 | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.identifier.wosid | 000467380900010 | - |
dc.identifier.scopusid | 2-s2.0-85062778772 | - |
dc.relation.journalWebOfScienceCategory | Agronomy | - |
dc.relation.journalResearchArea | Agriculture | - |
dc.type.docType | Article | - |
dc.subject.keywordPlus | TUBERS | - |
dc.subject.keywordPlus | PECTOBACTERIUM | - |
dc.subject.keywordPlus | CAROTOVORA | - |
dc.subject.keywordPlus | RESISTANCE | - |
dc.subject.keywordPlus | SEVERITY | - |
dc.subject.keywordAuthor | High throughput phenotyping | - |
dc.subject.keywordAuthor | Automated screening | - |
dc.subject.keywordAuthor | Digital | - |
dc.subject.keywordAuthor | Disease | - |
dc.subject.keywordAuthor | Accurate data | - |
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