{"created":"2025-09-05T07:20:36.137140+00:00","id":2000021,"links":{},"metadata":{"_buckets":{"deposit":"a4631fd1-48ff-447e-90a6-720a84aa48fe"},"_deposit":{"created_by":13,"id":"2000021","owners":[13],"pid":{"revision_id":0,"type":"depid","value":"2000021"},"status":"published"},"_oai":{"id":"oai:kit.repo.nii.ac.jp:02000021","sets":["1753926516427:1753929991454:1753936243499"]},"author_link":[],"item_30002_access_rights4":{"attribute_name":"Access Rights","attribute_value_mlt":[{"subitem_access_right":"open access","subitem_access_right_uri":"http://purl.org/coar/access_right/c_abf2"}]},"item_30002_alternative_title1":{"attribute_name":"Alternative Title","attribute_value_mlt":[{"subitem_alternative_title":"マルチスペクトルセンサーを用いた果実糖度の非破壊評価に関する研究","subitem_alternative_title_language":"ja"}]},"item_30002_creator2":{"attribute_name":"Creator","attribute_type":"creator","attribute_value_mlt":[{"creatorAlternatives":[{"creatorAlternative":"チャン, ニュット タン","creatorAlternativeLang":"ja"}],"creatorNames":[{"creatorName":"TRAN, NHUT THANH","creatorNameLang":"en"}]}]},"item_30002_date11":{"attribute_name":"Date","attribute_value_mlt":[{"subitem_date_issued_datetime":"2021-03-25","subitem_date_issued_type":"Issued"}]},"item_30002_date_granted32":{"attribute_name":"Date Granted","attribute_value_mlt":[{"subitem_dategranted":"2021-03-25"}]},"item_30002_degree_grantor33":{"attribute_name":"Degree Grantor","attribute_value_mlt":[{"subitem_degreegrantor":[{"subitem_degreegrantor_language":"ja","subitem_degreegrantor_name":"京都工芸繊維大学"}],"subitem_degreegrantor_identifier":[{"subitem_degreegrantor_identifier_name":"14303","subitem_degreegrantor_identifier_scheme":"kakenhi"}]}]},"item_30002_degree_name31":{"attribute_name":"Degree Name","attribute_value_mlt":[{"subitem_degreename":"博士（工学）","subitem_degreename_language":"ja"}]},"item_30002_description9":{"attribute_name":"Description","attribute_value_mlt":[{"subitem_description":"Sweetness is one of the most important characteristics of fruits and it affects commercial fruit value. However, it is an internal characteristic and not easy to assess nondestructively. Visible and near-infrared (VIS-NIR) spectroscopy combined with chemometrics is a powerful tool for nondestructive prediction of fruit sweetness but its practical application in the field is still limited due to its high cost and complexity. In this study, a practical approach based on VIS-NIR spectroscopy was proposed for nondestructive assessment of fruit sweetness and its performance was examined. A simple optical setup based on a pre-calibrated multispectral sensor chipset with 18 wavebands revealed good spectrometric performance at only one tenth the cost of a commercial dispersive spectrometer. An optimal multiple linear regression model with optimally-selected five wavebands at 900, 760, 730, 680, and 535 nm showed the best performance on quantitative prediction of apple sweetness. The coefficient of determination of prediction and the root mean square error of prediction were 0.861 and 0.403 oBrix, respectively, which were comparable to those of the previous studies with the dispersive spectrometers. As for sweetness grading, several classification algorithms such as discriminant analysis (DA), support vector machine, random forest, and k-nearest neighbors were examined and the DA model with the optimally-selected five wavebands showed the best performance with the accuracy of 91.3 % and the precision of 91.5%, which were better than those of previous studies with similar simple optical setups. The good performance in sweetness grading was also demonstrated in mangoes with the accuracy of 82.1 %. In terms of system manufacturability and reproducibility, the proposed system showed a clear advantage compared to the previous studies because neither customized fixture nor individual alignment were required. With a high performance in sweetness assessment and its design advantages, the proposed system had a considerable potential for practical, cost-effective applications in assessment of fruit sweetness, not only for apples or mangoes but also for other fruits.","subitem_description_language":"en","subitem_description_type":"Abstract"}]},"item_30002_dissertation_number30":{"attribute_name":"Dissertation Number","attribute_value_mlt":[{"subitem_dissertationnumber":"甲第995号"}]},"item_30002_file35":{"attribute_name":"File","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_access","displaytype":"detail","filename":"D1-0995_h1.pdf","filesize":[{"value":"3.8 MB"}],"format":"application/pdf","mimetype":"application/pdf","url":{"label":"全文","objectType":"fulltext","url":"https://kit.repo.nii.ac.jp/record/2000021/files/D1-0995_h1.pdf"},"version_id":"f7697936-a55b-44c3-a535-26659c40d365"},{"accessrole":"open_access","displaytype":"detail","filename":"D1-0995.pdf","filesize":[{"value":"141.5 KB"}],"format":"application/pdf","mimetype":"application/pdf","url":{"label":"内容・審査結果の要旨","objectType":"abstract","url":"https://kit.repo.nii.ac.jp/record/2000021/files/D1-0995.pdf"},"version_id":"1b246658-5cdf-4a7e-b6e6-550592de9bb2"}]},"item_30002_language12":{"attribute_name":"Language","attribute_value_mlt":[{"subitem_language":"eng"}]},"item_30002_resource_type13":{"attribute_name":"Resource Type","attribute_value_mlt":[{"resourcetype":"doctoral thesis","resourceuri":"http://purl.org/coar/resource_type/c_db06"}]},"item_30002_subject8":{"attribute_name":"Subject","attribute_value_mlt":[{"subitem_subject":"internal fruit quality","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"multispectral sensor","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"quantitative prediction","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"sweetness grading","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"machine learning","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"reproductive alignment","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"system manufacturability","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"soluble solids content.","subitem_subject_language":"en","subitem_subject_scheme":"Other"}]},"item_30002_title0":{"attribute_name":"Title","attribute_value_mlt":[{"subitem_title":"Study on Nondestructive Assessment of Fruit Sweetness with Multispectral Sensors","subitem_title_language":"en"}]},"item_30002_version_type15":{"attribute_name":"Version Type","attribute_value_mlt":[{"subitem_version_resource":"http://purl.org/coar/version/c_970fb48d4fbd8a85","subitem_version_type":"VoR"}]},"item_title":"Study on Nondestructive Assessment of Fruit Sweetness with Multispectral Sensors","item_type_id":"40002","owner":"13","path":["1753936243499"],"pubdate":{"attribute_name":"PubDate","attribute_value":"2024-08-08"},"publish_date":"2024-08-08","publish_status":"0","recid":"2000021","relation_version_is_last":true,"title":["Study on Nondestructive Assessment of Fruit Sweetness with Multispectral Sensors"],"weko_creator_id":"13","weko_shared_id":-1},"updated":"2026-01-16T01:21:21.684405+00:00"}