{"created":"2023-05-15T13:38:48.512399+00:00","id":2836,"links":{},"metadata":{"_buckets":{"deposit":"d803076f-2f62-462d-b241-14c7fcd0747c"},"_deposit":{"created_by":11,"id":"2836","owners":[11],"pid":{"revision_id":0,"type":"depid","value":"2836"},"status":"published"},"_oai":{"id":"oai:repository.naro.go.jp:00002836","sets":["2:581:63","87:653:40","87:676:61"]},"author_link":["1718","841"],"item_10001_biblio_info_7":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2018-11","bibliographicIssueDateType":"Issued"},"bibliographicPageEnd":"182","bibliographicPageStart":"168","bibliographicVolumeNumber":"175","bibliographic_titles":[{"bibliographic_title":"Biosystems Engineering"},{"bibliographic_title":"Biosystems Engineering","bibliographic_titleLang":"en"}]}]},"item_10001_description_5":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"Some stresses are utilised to improve qualities of agricultural products. Low light stress increases the chlorophyll content of tea leaves, which improves appearance. Although chlorophyll content estimation is one of the most common applications of hyperspectral remote sensing, previous studies were based on measurements under relatively low stress conditions. In this study, two methods, machine learning algorithms and the inversion of a radiative transfer model, were evaluated using measurements from tea leaves with shading treatments. According to the ratio of performance to deviation (RPD), PROSPECT-D inversion (RPD = 1.71–2.31) had the potential for quantifying chlorophyll content, although it required some improvements. Overall, the regression models based on machine learning had high performances. The kernel-based extreme learning machine had the highest performance with a root mean square error of 3.04 ± 0.52 μg cm−2 and RPD values from 3.38 to 5.92 for the test set, which was used for assessing generalisation error.","subitem_description_type":"Abstract"}]},"item_10001_publisher_8":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"Elsevier"}]},"item_10001_relation_14":{"attribute_name":"DOI","attribute_value_mlt":[{"subitem_relation_type":"isVersionOf","subitem_relation_type_id":{"subitem_relation_type_id_text":"10.1016/j.biosystemseng.2018.09.018","subitem_relation_type_select":"DOI"}}]},"item_10001_relation_16":{"attribute_name":"情報源","attribute_value_mlt":[{"subitem_relation_name":[{"subitem_relation_name_text":"SC30201903070023"}]},{"subitem_relation_name":[{"subitem_relation_name_text":"NARO成果DBa"}]},{"subitem_relation_name":[{"subitem_relation_name_text":"author manuscript "}]},{"subitem_relation_name":[{"subitem_relation_name_text":"This is not the published version. Please cite only the published version. "}]},{"subitem_relation_name":[{"subitem_relation_name_text":" この論文は出版社版ではありません。引用の際には出版社版をご利用ください。"}]},{"subitem_relation_name":[{"subitem_relation_name_text":"Green open Access /This journal has an embargo period of 24 months."}]}]},"item_10001_relation_17":{"attribute_name":"関連サイト","attribute_value_mlt":[{"subitem_relation_name":[{"subitem_relation_name_text":"Biosystems Engineering"}],"subitem_relation_type_id":{"subitem_relation_type_id_text":"http://dx.doi.org/10.1016/j.biosystemseng.2018.09.018","subitem_relation_type_select":"DOI"}}]},"item_10001_rights_15":{"attribute_name":"権利","attribute_value_mlt":[{"subitem_rights":"2018 Published by Elsevier Ltd."},{"subitem_rights":"The Author(s) "}]},"item_10001_source_id_9":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"1537-5110","subitem_source_identifier_type":"ISSN"}]},"item_10001_version_type_20":{"attribute_name":"著者版フラグ","attribute_value_mlt":[{"subitem_version_resource":"http://purl.org/coar/version/c_ab4af688f83e57aa","subitem_version_type":"AM"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"佐野, 智人"},{"creatorName":"サノ, トモヒト","creatorNameLang":"ja-Kana"},{"creatorName":"SANO, Tomohito","creatorNameLang":"en"}],"nameIdentifiers":[{"nameIdentifier":"1718","nameIdentifierScheme":"WEKO"},{"nameIdentifier":"80611300","nameIdentifierScheme":"e-Rad","nameIdentifierURI":"https://kaken.nii.ac.jp/ja/search/?qm=80611300"},{"nameIdentifier":"sanotomo","nameIdentifierScheme":"researchmap","nameIdentifierURI":"http://researchmap.jp/sanotomo"}]},{"creatorNames":[{"creatorName":"堀江, 秀樹"},{"creatorName":"ホリエ, ヒデキ","creatorNameLang":"ja-Kana"},{"creatorName":"HORIE, Hideki","creatorNameLang":"en"}],"nameIdentifiers":[{"nameIdentifier":"841","nameIdentifierScheme":"WEKO"},{"nameIdentifier":"90355628","nameIdentifierScheme":"e-Rad","nameIdentifierURI":"https://kaken.nii.ac.jp/ja/search/?qm=90355628"},{"nameIdentifier":"read0004523","nameIdentifierScheme":"researchmap","nameIdentifierURI":"http://researchmap.jp/read0004523"}]}]},"item_files":{"attribute_name":"ファイル情報","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_date","date":[{"dateType":"Available","dateValue":"2020-12-01"}],"displaytype":"detail","filename":"SC30201903070023_PostPrint_a.pdf","filesize":[{"value":"1.1 MB"}],"format":"application/pdf","licensetype":"license_11","mimetype":"application/pdf","url":{"label":"SC30201903070023_PostPrint","url":"https://repository.naro.go.jp/record/2836/files/SC30201903070023_PostPrint_a.pdf"},"version_id":"cdd12ede-f587-4798-8667-502f6d07f3b8"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"chlorophyll","subitem_subject_scheme":"Other"},{"subitem_subject":"green tea","subitem_subject_scheme":"Other"},{"subitem_subject":"vegetation indices","subitem_subject_scheme":"Other"},{"subitem_subject":"machine learning","subitem_subject_scheme":"Other"},{"subitem_subject":"PROSPECT-D","subitem_subject_scheme":"Other"},{"subitem_subject":"chlorophyll","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"green tea","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"vegetation indices","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"machine learning","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"PROSPECT-D","subitem_subject_language":"en","subitem_subject_scheme":"Other"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"eng"}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourcetype":"journal article","resourceuri":"http://purl.org/coar/resource_type/c_6501"}]},"item_title":"Using spectral reflectance to estimate leaf chlorophyll content of tea with shading treatments","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Using spectral reflectance to estimate leaf chlorophyll content of tea with shading treatments"},{"subitem_title":"Using spectral reflectance to estimate leaf chlorophyll content of tea with shading treatments","subitem_title_language":"en"}]},"item_type_id":"10001","owner":"11","path":["40","61","63"],"pubdate":{"attribute_name":"公開日","attribute_value":"2019-10-04"},"publish_date":"2019-10-04","publish_status":"0","recid":"2836","relation_version_is_last":true,"title":["Using spectral reflectance to estimate leaf chlorophyll content of tea with shading treatments"],"weko_creator_id":"11","weko_shared_id":-1},"updated":"2023-05-15T15:59:35.016857+00:00"}