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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 陳玟伶(Wen-Ling Chen) | |
| dc.contributor.author | Hsuan-Yu Tai | en |
| dc.contributor.author | 戴亘淯 | zh_TW |
| dc.date.accessioned | 2022-11-25T05:33:44Z | - |
| dc.date.available | 2027-02-07 | |
| dc.date.copyright | 2022-02-21 | |
| dc.date.issued | 2022 | |
| dc.date.submitted | 2022-02-07 | |
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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/81993 | - |
| dc.description.abstract | "2019年4月位於雲林縣的六輕石油化學工業區因丁烷外洩，發生火災氣爆事件，濃煙擴散至雲林縣與彰化縣鄰近的農業生產區。本研究應用非目標分析法調查災後六輕周圍農地所生產的稻米中小分子化學輪廓（small-molecule profiles）隨時間與空間變化的趨勢，以探討化學災害對農業生產環境的影響。 本研究自火災發生後，於雲林縣與彰化縣共15處農地連續收集四個採收期的糙米樣本（n=28）。所有樣本經溶劑萃取與管柱淨化後，利用液相層析－四極桿／飛行時間質譜系統獲取小分子化合物（m/z 70−1,100）之分子離子與碎片離子資訊，並透過分子波峰提取步驟保留絕對高度≥1,000 counts的波峰。小分子波峰經過總面積標準化後，以偏最小平方判別法（partial least squares-discriminant analysis, PLS-DA）分析整體化合物時空分布趨勢，再篩選出相對濃度在組間具有顯著差異（p<0.05、|log2 (fold change)|>1.5且|p[corr]|>0.6、|p[1]|>5）的特徵化合物，最後透過比對化學資料庫之準確質量與碎片離子完成特徵化合物鑑定。 PLS-DA模式成功鑑別了不同採收期的水稻。在生長過程中直接遭遇化學災害（災後3個月採收）的稻米小分子化學輪廓與後續種植的稻米顯然不同（正離子模式R2=1.000、Q2=0.981；負離子模式R2=1.000、Q2=0.943）。將這批直接遭遇災害的樣本進一步進行空間分析，亦發現小分子化學輪廓在爆炸點15公里內外有所差異（正離子模式R2=0.983、Q2=0.402；負離子模式R2=0.951、Q2=0.286）。候選特徵化合物篩選結果，有83個化合物之相對量隨距離而改變。我們鑑定出其中18種特徵化合物，發現大多數為水稻的內生性物質，如脂肪酸、磷脂質、胺基酸等。化學災害可能啟動水稻防禦機制，影響次級代謝產物在稻米中的分布、以及稻米細胞與組織組成，繼而干擾水稻生長與環境適應能力。 本研究證實非目標分析方法適用於調查化學災害對農業環境的影響。歷時2年的研究成果顯示化學災害可能衝擊周圍農業環境、改變農作物小分子代謝與分布。應持續監測農業環境並建立背景資料，以利災害準備與應變。" | zh_TW |
| dc.description.provenance | Made available in DSpace on 2022-11-25T05:33:44Z (GMT). No. of bitstreams: 1 U0001-0702202200381500.pdf: 6762770 bytes, checksum: 7c5b442e381585a16def26506581067e (MD5) Previous issue date: 2022 | en |
| dc.description.tableofcontents | 誌謝 I 中文摘要 II Abstract III 目 錄 V 圖目錄 VII 表目錄 XI 第一章 前言 1 1.1 研究背景與動機 1 1.2 六輕工業區歷年的化學災害事件 3 1.3 化學災害對農業環境之影響案例 5 1.4 臺灣水稻栽種現況 6 1.5 稻米的食品安全議題 6 1.6 代謝體學於稻米鑑別之應用 8 1.7 應用高解析質譜法執行非目標分析 9 1.8 非目標分析技術與流程 9 1.8.1 資料擷取 10 1.8.2 多變量分析 10 1.8.3 化合物鑑定 12 第二章 研究目的與研究流程 14 第三章 材料與方法 16 3.1 化學品、實驗器材與儀器設備 16 3.1.1 化學品 16 3.1.2 實驗器材 16 3.1.3 儀器設備 17 3.2 樣本採集與前處理 17 3.3 高解析質譜資料擷取 20 3.4 資料處理與分析 22 3.4.1 波峰提取 22 3.4.2 資料分析與變項篩選 25 3.5 小分子化合物鑑定 25 3.6 品質保證與品質管制 28 第四章 結果與討論 29 4.1 樣本採集結果 29 4.2 高解析質譜資料擷取結果 33 4.3 分析方法再現性 36 4.4 分子波峰提取結果 36 4.5 多變量分析 43 4.5.1 糙米中小分子化學輪廓的時間分布 43 4.5.2 糙米中小分子化學輪廓的空間分布 46 4.6 候選特徵化合物之篩選結果 50 4.7 特徵化合物鑑定結果 54 4.7.1 脂肪酸及其衍生物 59 4.7.2 其它有機酸及其衍生物 60 4.7.3 稻米中的污染物與殘留物 60 第五章 結論 73 參考文獻 74 附錄 88 附錄一、採樣農地與周圍環境示意圖 88 附錄二、實驗器材與儀器設備 90 附錄三、利用單變量與多變量分析方法篩選出的候選特徵化合物 92 | |
| dc.language.iso | zh-TW | |
| dc.subject | 小分子化學輪廓 | zh_TW |
| dc.subject | 化學災害 | zh_TW |
| dc.subject | 高解析質譜法 | zh_TW |
| dc.subject | 非目標分析 | zh_TW |
| dc.subject | 農業環境 | zh_TW |
| dc.subject | agricultural environment | en |
| dc.subject | high-resolution mass spectrometry | en |
| dc.subject | untargeted analysis | en |
| dc.subject | chemical disaster | en |
| dc.subject | small-molecule profiles | en |
| dc.title | 受化學災害事件衝擊的稻米中小分子有機物化學輪廓之時空變化趨勢研究 | zh_TW |
| dc.title | Spatial and temporal trends of the small-molecule profiles of rice impacted by a chemical disaster | en |
| dc.date.schoolyear | 110-1 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 洪挺軒(Joe-Air Jiang),蔡孟勳(Yan-Fu Kuo),魏嘉徵,詹長權 | |
| dc.subject.keyword | 化學災害,農業環境,小分子化學輪廓,非目標分析,高解析質譜法, | zh_TW |
| dc.subject.keyword | chemical disaster,agricultural environment,small-molecule profiles,untargeted analysis,high-resolution mass spectrometry, | en |
| dc.relation.page | 94 | |
| dc.identifier.doi | 10.6342/NTU202200314 | |
| dc.rights.note | 同意授權(限校園內公開) | |
| dc.date.accepted | 2022-02-09 | |
| dc.contributor.author-college | 公共衛生學院 | zh_TW |
| dc.contributor.author-dept | 食品安全與健康研究所 | zh_TW |
| dc.date.embargo-lift | 2027-02-07 | - |
| 顯示於系所單位： | 食品安全與健康研究所 | |
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