{"created":"2022-06-24T00:32:29.130163+00:00","id":2019331,"links":{},"metadata":{"_buckets":{"deposit":"6036c210-2171-4695-b2d5-cff91d62fcf0"},"_deposit":{"created_by":8,"id":"2019331","owner":"8","owners":[8],"owners_ext":{"displayname":"ryukyu_lib","username":null},"pid":{"revision_id":0,"type":"depid","value":"2019331"},"status":"published"},"_oai":{"id":"oai:u-ryukyu.repo.nii.ac.jp:02019331","sets":["1642838158423:1642838158860:1642838161450","1642838403551:1642838411479"]},"author_link":[],"control_number":"2019331","item_1617186331708":{"attribute_name":"Title","attribute_value_mlt":[{"subitem_1551255647225":"ICTを活用したマンゴー生産に関する研究","subitem_1551255648112":"ja"},{"subitem_1551255647225":"Research on mango production using ICT","subitem_1551255648112":"en"}]},"item_1617186419668":{"attribute_name":"Creator","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"城間, 康","creatorNameLang":"ja"},{"creatorName":"Shiroma, Yasushi","creatorNameLang":"en"}]}]},"item_1617186476635":{"attribute_name":"Access Rights","attribute_value_mlt":[{"subitem_1522299639480":"open access","subitem_1600958577026":"http://purl.org/coar/access_right/c_abf2"}]},"item_1617186626617":{"attribute_name":"Description","attribute_value_mlt":[{"subitem_description":"沖縄におけるマンゴー生産は日本国内で最も盛んであり、特に夏の果実として非常に人気が高い。県内の主要産地は「宮古島市、豊見城市、石垣市」等で、2018年の生産量も全国シェアは55％を誇り、売り上げは25億円であった。沖縄県はマンゴーを戦略的な農作物としてとらえており、ブランド化へ向けて生産振興を奨励している。しかしながら、マンゴーの生育過程は日光、温度およびその他の要因の変化による影響を受けやすく、育成において品質管理は個人の目視や経験によるカンが頼りとなっている。 現状のままでは、マンゴーを高品質で安定供給し続けることは困難であり、品質を保証するためには栽培管理を可視化し、簡便にする必要がある。\nこのような状況の中、近年では農業分野でもICT、IoT技術を導入し、センサー技術で環境パラメーターを取得して栽培管理を行う農家も増えてきた。また、企業農家ではパラメータの解析や、画像診断による特徴量解析で病気の特定する研究も盛んになっており、目覚ましい飛躍と遂げている。\nそこで、本研究ではICTセンサー技術を用いて環境の測定と制御を行い、天候不純等の自然環境に影響されにくいマンゴー生産の生産システムの開発を試みた。具体的には、CO_2施用技術と、LED補光システムを導入し、マンゴーの 光合成を活性化させ、果実の収穫時期の調整と品質の向上を図った。\nまた、沖縄県産マンゴーが付加価値のある農産物としてブランドを確立していくには、マンゴーが適正な等級で消費者に販売することが求められ、現在はJA (日本農業協同組合) おきなわが等級判別用に簡易基準表を用意し、果実の色合いに基づいて等級を決定している。しかし、現場の判別は人間が目視で行っているために主観的になり、品質が均一ではないことが問題になっている。\nそこで本研究では、マンゴーの等級を客観的に評価するために、コンピュータビジョンによる判別法を導入し、マンゴーの果皮における色情報を用いた等級判別法を提案した。取得した画像データからマンゴーを分類する指標を明らかにするために、果皮のヒストグラムを特徴量として作成し、閾値を決定するアルゴリズムを構築した。さらに機械学習を用い、判別誤差を考慮した判別メソッドとしてB-kNN法を用い、精度の高い判別を実現した。","subitem_description_language":"ja","subitem_description_type":"Abstract"},{"subitem_description":"The production of mangoes in Okinawa is the most active successful in Japan and is especially popular as a summer fruit. The main production areas in the prefecture are Miyakojima City, Tomigusuku City, Ishigaki City etc. The production volume in 2018 boasted a 55% share of the national market with sales of 2.5 billion yen. Okinawa Prefecture considers mangoes to be a strategic agricultural crop and is encouraging the promotion of its production toward branding. However, the growth process of mangoes is susceptible to changes in sunlight, temperature and other factors. Moreover, the quality control in cultivation relies on personal observation and experience. As it is difficult to maintain a stable supply of high-quality mangoes, the cultivation management must be visualized and simplified in order to guarantee quality.\nUnder these circumstances, in recent years, ICT and IoT technologies have been introduced in the agricultural sector. Many farmers are using sensor technology to acquire environmental parameters for cultivation management. In addition, corporate farmers have made a remarkable leap forward in their research to identify diseases by analyzing parameters and feature analysis through image diagnosis.\nIn this study, we attempted to develop a production system for mango production that is not easily affected by the natural environment, such as impure weather, by measuring and controlling the environment using IoT sensor technology. Specifically, CO_2 application technology and an LED supplementary lighting system were introduced to activate photosynthesis in mangoes, adjust the fruit harvest time, and improve quality.\nIn addition, in order to Okinawa mangoes to establish a brand as a value-added agricultural product, they must be sold to consumers in the proper grade. Currently, JA Okinawa (Japan Agricultural Cooperative) preparing a simple standard chart for grade determination and the grade is determined based on the color of the fruit.\nHowever, since the identification is done manually by humans, it is subjective and the quality is not uniform, which is a problem.\nIn this study, we introduced a computer vision-based discrimination method to objectively evaluate the grade of mangoes and proposed a grading method using color information in mango skins. In order to clarify the index for classify mangoes from the acquired image data, a histogram of the rind was created as a feature and an algorithm to determine the threshold was constructed. Furthermore, using machine learning, the B-kNN method was used as a discriminant method considering the discrimination error and highly accurate discrimination was achieved.","subitem_description_language":"en","subitem_description_type":"Abstract"}]},"item_1617186643794":{"attribute_name":"Publisher","attribute_value_mlt":[{"subitem_1522300295150":"ja","subitem_1522300316516":"琉球大学"},{"subitem_1522300295150":"en","subitem_1522300316516":"University of the Ryukyus"}]},"item_1617186702042":{"attribute_name":"Language","attribute_value_mlt":[{"subitem_1551255818386":"jpn"}]},"item_1617187087799":{"attribute_name":"Dissertation Number","attribute_value_mlt":[{"subitem_1551256171004":"甲第419号"}]},"item_1617187112279":{"attribute_name":"Degree Name","attribute_value_mlt":[{"subitem_1551256126428":"博士（工学）","subitem_1551256129013":"ja"}]},"item_1617187136212":{"attribute_name":"Date Granted","attribute_value_mlt":[{"subitem_1551256096004":"2022-03-18"}]},"item_1617258105262":{"attribute_name":"Resource Type","attribute_value_mlt":[{"resourcetype":"doctoral thesis","resourceuri":"http://purl.org/coar/resource_type/c_db06"}]},"item_1617265215918":{"attribute_name":"Version Type","attribute_value_mlt":[{"subitem_1522305645492":"VoR","subitem_1600292170262":"http://purl.org/coar/version/c_970fb48d4fbd8a85"}]},"item_1617605131499":{"attribute_name":"File","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_access","date":[{"dateType":"Available","dateValue":"2022-06-24"}],"filename":"rikoken419abstract.pdf","filesize":[{"value":"414 KB"}],"mimetype":"application/pdf","url":{"objectType":"abstract","url":"https://u-ryukyu.repo.nii.ac.jp/record/2019331/files/rikoken419abstract.pdf"},"version_id":"f111fb64-932d-4435-8d08-69c020ab2144"},{"accessrole":"open_access","date":[{"dateType":"Available","dateValue":"2022-06-24"}],"filename":"rikoken419review.pdf","filesize":[{"value":"5.8 MB"}],"mimetype":"application/pdf","url":{"objectType":"other","url":"https://u-ryukyu.repo.nii.ac.jp/record/2019331/files/rikoken419review.pdf"},"version_id":"863c11f2-bacc-48b9-b369-e51c164029bb"},{"accessrole":"open_access","date":[{"dateType":"Available","dateValue":"2022-06-24"}],"filename":"rikoken419text.pdf","filesize":[{"value":"4.8 MB"}],"mimetype":"application/pdf","url":{"objectType":"fulltext","url":"https://u-ryukyu.repo.nii.ac.jp/record/2019331/files/rikoken419text.pdf"},"version_id":"1ad140da-8dc2-4d9b-b091-ae0985072791"}]},"item_1617944105607":{"attribute_name":"Degree Grantor","attribute_value_mlt":[{"subitem_1551256015892":[{"subitem_1551256027296":"18001","subitem_1551256029891":"kakenhi"}],"subitem_1551256037922":[{"subitem_1551256042287":"琉球大学","subitem_1551256047619":"ja"}]}]},"item_title":"ICTを活用したマンゴー生産に関する研究","item_type_id":"59","owner":"8","path":["1642838161450","1642838411479"],"pubdate":{"attribute_name":"PubDate","attribute_value":"2022-06-24"},"publish_date":"2022-06-24","publish_status":"0","recid":"2019331","relation_version_is_last":true,"title":["ICTを活用したマンゴー生産に関する研究"],"weko_creator_id":"8","weko_shared_id":-1},"updated":"2022-06-24T01:32:50.601279+00:00"}