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  1. NTU Theses and Dissertations Repository
  2. 生物資源暨農學院
  3. 生物產業傳播暨發展學系
請用此 Handle URI 來引用此文件: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/101489
完整後設資料紀錄
DC 欄位值語言
dc.contributor.advisor王俊傑zh_TW
dc.contributor.advisorChun-Chieh Wangen
dc.contributor.author黃郁哲zh_TW
dc.contributor.authorYu-Che Huangen
dc.date.accessioned2026-02-04T16:11:35Z-
dc.date.available2026-02-05-
dc.date.copyright2026-02-04-
dc.date.issued2026-
dc.date.submitted2026-01-29-
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dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/101489-
dc.description.abstract在氣候變遷加劇與極端氣候事件頻繁發生的背景下,植物病害的發生型態與防治難度日益提升,對全球糧食安全與農業永續發展造成重大挑戰。水稻(Oryza sativa L.)作為全球重要的糧食作物之一,其病害研究不僅攸關糧食供應穩定,亦反映農業科學在病原防治、分子生物技術與跨領域整合上的發展趨勢。本研究結合資訊計量分析與方法,探討近二十年水稻病害研究中,研究議題之連結特徵、研究人才之合著關係,以及兩者之間的跨層交互影響。自Web of Science資料庫為資料來源,採用指數隨機圖模型進行多層次網絡分析,研究結果顯示,水稻病害研究議題共現網絡呈現顯著的非隨機性與核心—邊陲結構,其中以「稻熱病」、「抗病基因鑑定與圖譜建構」及「基因表現與轉殖研究」構成長期研究核心,並高度整合分子植物病理與遺傳研究取向;而研究人才合著網絡同樣呈現核心—邊陲結構,少數高產出研究人才主導高強度且穩定的合著關係,其中,研究議題相似性為促進穩定合著之關鍵因素。相較之下,「抗病基因鑑定與圖譜建構」與「基因表現與轉殖研究」之研究議題於文獻層級雖具高度共現,但未必能直接轉化為研究人才層級的實際合著;研究人才實際形成穩定合著關係者,多集中於方法與研究流程具高度連續性的研究議題組合,如「稻熱病」與「抗病基因鑑定與圖譜建構」,或是「病毒性病害」與「基因表現與轉殖研究」。因此,本研究結果可作為未來學術資源配置、研究議題規劃及跨研究議題合著模式之實證依據。zh_TW
dc.description.abstractAgainst the backdrop of intensifying climate change and the increasing frequency of extreme weather events, the occurrence patterns and control difficulties of plant diseases are becoming more complex, posing significant challenges to global food security and sustainable agricultural development. As one of the world’s most important food crops, research on rice (Oryza sativa L.) diseases is not only crucial for maintaining food supply stability but also reflects broader development trends in agricultural science, particularly in pathogen control, molecular biotechnology, and interdisciplinary integration. This study combines informatics analysis methods to explore the interconnected characteristics of research topics, co-authorship relationships among researchers, and the cross-level interactions between these two dimensions in rice disease research over the past two decades. Using data from the Web of Science database and employing an exponential random graph model for multi-level network analysis, the study reveals that the co-occurrence network of rice disease research topics exhibits significant non-randomness and a core–periphery structure. “rice blast,” “identification and mapping of disease resistance genes,” and “gene expression and transgenic research” constitute long-term research cores, highly integrating molecular plant pathology and genetic research orientations. Similarly, the co-authorship network of researchers also demonstrates a core–periphery structure, in which a small number of highly productive researchers dominate strong and stable co-authorship relationships. Research topic similarity is a key factor in promoting stable co-authorship. In contrast, although the research topics of “identification and mapping of disease resistance genes” and “gene expression and transgenic research” show high co-occurrence at the literature level, this does not necessarily translate directly into actual co-authorship at the researcher level. Researchers who form stable co-authorship relationships tend to focus on combinations of research topics with highly continuous methods and research processes, such as “rice blast” and “identification and mapping of disease resistance genes,”or “viral diseases” and “gene expression and transgenic research.” Therefore, the findings of this study provide empirical evidence to inform future academic resource allocation, research topic planning, and the development of cross-topic co-authorship models.en
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dc.description.tableofcontents謝辭 i
中文摘要 ii
Abstract iii
目次 v
圖次 viii
表次 ix
第壹章 緒論 1
第一節 研究背景 1
第二節 研究動機 3
第三節 研究目的 5
第四節 名詞解釋 7
第貳章 文獻探討 8
第一節 水稻病害與其相關研究議題 8
一、 水稻與其常見病害 8
二、 水稻病害鑑定、監測與防治 14
三、 水稻病害研究議題的網絡結構 17
第二節 指數隨機圖模型相關研究 25
一、 指數隨機圖模型介紹 25
二、 單層次指數隨機圖模型 26
三、 多層次指數隨機圖模型 27
四、 指數隨機圖模型相關內生變數 29
第三節 資訊計量與研究人才合著 31
一、 資訊計量相關研究 31
二、 團隊科學 35
三、 跨學科合作 36
四、 研究人才的網絡結構 37
第參章 研究方法 46
第一節 資料蒐集與清理 46
一、 資料蒐集 46
二、 資料清理 47
三、 研究議題與研究人才資料集 48
第二節 資訊計量分析 49
一、 研究議題分類架構 49
二、 水稻病害研究議題共現網絡之分析方法 52
三、 水稻病害研究人才合著網絡之分析方法 53
四、 水稻病害研究議題與研究人才之分析方法 53
第三節 ERGM相關變數指標計算 54
一、 研究議題與研究人才之內生變數計算方法 54
二、 研究議題與研究人才之節點屬性共變項計算方法 66
三、 研究議題共現網絡之外生變數計算方法 69
四、 研究人才合著網絡之外生變數計算方法 71
第四節 MPNet診斷與分析 75
一、 水稻病害研究議題共現網絡之ERGM分析 75
二、 水稻病害研究人才合著網絡之ERGM分析 78
三、 水稻病害研究議題與研究人才之MLERGM分析 80
第肆章 研究結果 82
第一節 水稻病害研究議題間互相連結之特徵 82
一、 水稻病害研究議題互相連結之內生變數特徵 82
二、 水稻病害研究議題之單一研究議題與研究議題對之特徵 87
三、 水稻病害研究議題之研究議題熱門度特徵 89
四、 水稻病害研究議題之共現頻率特徵 91
五、 水稻病害研究議題之時間相近性特徵 94
第二節 水稻病害研究人才間合著關係之特徵 100
一、 水稻病害研究人才合著關係之內生變數特徵 100
二、 水稻病害研究人才之學術發表量特徵 102
三、 水稻病害研究人才之研究年齡特徵 109
四、 水稻病害研究人才之研究議題相似性特徵 111
五、 水稻病害研究人才之合著次數特徵 114
第三節 水稻病害研究議題共現與研究人才合著關係的連結 117
一、 議題與人才網絡之XStar3A及XStar3B結構特徵 117
二、 議題與人才網絡之X4Cycle、XACA及XECA結構特徵 121
三、 議題與人才網絡之XAECA、XECB及XAECB結構特徵 124
第伍章 結論與建議 131
第一節 研究結論 131
第二節 研究建議與限制 134
參考文獻 137
附錄 167
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dc.language.isozh_TW-
dc.subject水稻病害-
dc.subject研究議題-
dc.subject研究人才-
dc.subject連結特徵-
dc.subject合著關係-
dc.subjectrice diseases-
dc.subjectresearch topics-
dc.subjecttalent-
dc.subjectconnection characteristics-
dc.subjectco-authorship-
dc.title水稻病害研究議題與研究人才合著連結zh_TW
dc.titleLinking Research Topics and Talent Co-authorship in the Study of Rice Diseasesen
dc.typeThesis-
dc.date.schoolyear114-1-
dc.description.degree碩士-
dc.contributor.oralexamcommittee董蕙茹;薛招治zh_TW
dc.contributor.oralexamcommitteeHuei-Ru Dong;Chao-Chih Hsuehen
dc.subject.keyword水稻病害,研究議題研究人才連結特徵合著關係zh_TW
dc.subject.keywordrice diseases,research topicstalentconnection characteristicsco-authorshipen
dc.relation.page178-
dc.identifier.doi10.6342/NTU202600413-
dc.rights.note同意授權(全球公開)-
dc.date.accepted2026-01-30-
dc.contributor.author-college生物資源暨農學院-
dc.contributor.author-dept生物產業傳播暨發展學系-
dc.date.embargo-lift2026-02-05-
顯示於系所單位:生物產業傳播暨發展學系

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