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  1. NTU Theses and Dissertations Repository
  2. 生物資源暨農學院
  3. 生物機電工程學系
請用此 Handle URI 來引用此文件: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/82157
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dc.contributor.advisor陳林祈(Lin-Chi Chen)
dc.contributor.authorYi-Yi Chenen
dc.contributor.author陳顗伊zh_TW
dc.date.accessioned2022-11-25T06:32:58Z-
dc.date.copyright2021-11-11
dc.date.issued2021
dc.date.submitted2021-08-23
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dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/82157-
dc.description.abstract"為了解決農業人口老齡化問題,智慧農業科技可將現有的生產經驗與知識保留並轉換為數位資訊,有利於建立專家系統以降低農業經營門檻與提高生產效率。本研究欲發展多離子感測試片進行高通量植物營養素組成分析之現場檢測平台,以找出較佳植物栽種條件及管控植物品質,故建立植物營養素檢測裝置。以植物工廠之水耕蔬菜作為感測樣本,自製固態離子選擇電極陣列試片 (solid-contact ion-selective electrode array chip, SCISE array chip) 作為感測器,搭配多通道電位感測模組,量測不同栽種條件下植物葉片汁液之離子濃度,並使用多變量統計分析離子組成找出植物之生理特性、健康狀態和品質等關聯。SCISE陣列試片可量測鉀、銨、鈣、鎂、氫、硝酸根、氯和鈉等八種離子濃度。為了檢測應用性,使用其量測未過濾植物汁液和養液 (濃度範圍:10-3~10-4M) ,並與離子分析儀 (IA-300) 過濾後的植物汁液和養液之結果比較,且該試片當天可重複使用至少30次。接著,以標準儀器量測之同光質不同養液栽種之植物葉片汁液之離子濃度,比較變異數分析 (ANOVA) 、多變量變異數分析 (MANOVA) 、主成分分析 (PCA) 和因素分析 (FA) 等統計分析之結果。我們發現FA可分群不同栽種條件之植物並找出栽種條件與生理特性之關係,透過盒鬚圖搭配AONVA鈉離子在統計存在顯著差異,因此為分群上的重要參數,有助於未來判斷不同栽種條件與品質管理。並以不同光質同養液栽種之植物驗證其結果,結果顯示不同光質比例應用於不同種類的蔬菜後可影響不同的生理特性,有助於預測光質對特定作物生理特性的影響並進而掌握品質。最後,使用逐步迴歸 (stepwise regression) 建立最適化模型和擬合公式,其結果有助於改良養液與光質配方,並可應用於發展專家系統。本研究發展植物營養素檢測裝置,可快速量測多種離子濃度並建立出代數值模型,未來可利用此技術判斷栽種條件之合宜性,並掌握植物生理特性和健康狀態,大到品質管理與產量提升。"zh_TW
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dc.description.tableofcontents致謝 i 中文摘要 ii Abstract iii 目錄 v 表目錄 ix 圖目錄 xi 第一章 緒論 1 1.1 前言 1 1.2 研究動機 2 1.3 研究目的 4 1.4 研究架構 5 第二章 文獻探討 6 2.1 環境對植物影響 6 2.1.1 營養素對植物的生理角色與功能 6 2.1.2 光對植物生長和二次代謝物 8 2.2 離子選擇電極應用於農業檢測 9 2.3多變量分析應用於農業 17 第三章 材料與實驗方法 18 3.1 實驗材料與儀器 18 3.1.1 實驗材料 18 3.1.3 實驗軟體 20 3.2 固態式離子選擇電極陣列製程與性能評估 21 3.2.1 網版印刷碳電極製作 21 3.2.2 離子電子傳導層製備 23 3.2.3 離子選擇薄膜製備 24 3.2.4 固態式離子選擇電極陣列性能評估 26 3.2.4.1 開環路電位量測 26 3.2.4.2 選擇性分析 26 3.3 系統建置 27 3.4 蔬菜樣本 29 3.4.1 蔬菜樣本製備 29 3.4.2 鮮重量測 29 3.4.3 種植條件 29 3.4.3.1 不同養液處理週數之香波綠萵苣試驗 29 3.4.3.2 不同紅藍比之紅酸模試驗 30 3.4.3.3 不同光質之鳳仙羽衣甘藍試驗 32 3.4.3.4 不同光質之香波綠萵苣試驗 33 3.5 量測分析 35 3.5.1 三點校正法換算濃度 35 3.5.2 數據統計分析 36 3.5.2.1 變異數分析 36 3.5.2.2 多變量變異數分析 37 3.5.2.3 主成分分析 38 3.5.2.4 因素分析 39 3.5.2.5 逐步迴歸 41 第四章 結果與討論 42 4.1 固態式離子選擇電極陣列試片感測性能評估 42 4.1.1 固態式離子選擇電極之靈敏度與選擇性 42 4.1.2 固態式離子選擇電極之電位差值重複性 46 4.1.3 與儀器比對不同應用標的之離子濃度 49 4.2 以已知養液配方與植物體內離子濃度探索不同統計分析方法 52 4.2.1 分析植物體內離子濃度與種植條件之關係 53 4.2.2 透過植物體內離子濃度分析種植條件與生理特性之關係 58 4.2.2.1 多變量變異數分析 58 4.2.2.2 主成分分析 60 4.2.2.3 因素分析 63 4.3 驗證分析方法並找出不同光質與植物生理特性關係 68 4.3.1 利用因素分析於不同光質栽種之植物 68 4.3.1.1 不同光質之紅酸模與生理特性之關係 68 4.3.1.2 不同光質之羽衣甘藍與生理特性之關係 73 4.3.1.3 不同光質之香波綠萵苣與生理特性之關係 77 4.3.2 變異數分析於不同光質之植物 81 4.3.2.1 不同光質之紅酸模葉片離子濃度 81 4.3.2.2 不同光質之羽衣甘藍葉片離子濃度 86 4.3.2.3 不同光質之香波綠萵苣葉片離子濃度 91 4.4 建立植物栽種條件最適化模型 95 4.4.1 不同栽種條件之最適化模型 96 4.4.2 以較高鮮重建立最適化模型 97 4.4.3 以特定光質建立光質最適化預測模型 99 4.4.3.1 紅酸模最適化模型 100 4.4.3.2 羽衣甘藍最適化模型 101 4.4.3.3 香波綠萵苣最適化模型 103 第五章 結論與未來展望 106 5.1 結論 106 5.2 未來展望與建議 107 參考文獻 108
dc.language.isozh-TW
dc.subject汁液分析zh_TW
dc.subject植物工廠zh_TW
dc.subject營養素分析zh_TW
dc.subject固態式離子選擇電極zh_TW
dc.subject多變量統計zh_TW
dc.subjectnutrient analysisen
dc.subjectsolid-state ion-selective electrodeen
dc.subjectmultivariate statisticsen
dc.subjectsap analysisen
dc.subjectplant factoryen
dc.title固態離子選擇電極陣列於水耕作物之營養素組成分析zh_TW
dc.titleNutrient Composition Analysis for Hydroponic Crops by Solid-state Ion-Selective Electrode Arraysen
dc.date.schoolyear109-2
dc.description.degree碩士
dc.contributor.coadvisor方煒(Wei Fang)
dc.contributor.oralexamcommittee林淑怡(Hsin-Tsai Liu),陳倩瑜(Chih-Yang Tseng),林毓雯
dc.subject.keyword植物工廠,營養素分析,固態式離子選擇電極,多變量統計,汁液分析,zh_TW
dc.subject.keywordplant factory,nutrient analysis,solid-state ion-selective electrode,multivariate statistics,sap analysis,en
dc.relation.page119
dc.identifier.doi10.6342/NTU202102586
dc.rights.note未授權
dc.date.accepted2021-08-23
dc.contributor.author-college生物資源暨農學院zh_TW
dc.contributor.author-dept生物機電工程學系zh_TW
dc.date.embargo-lift2026-08-23-
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