摘要
第一部分研究為液相層析法結合感應耦合電漿質譜儀分析食品中sulfite (SO32-)、sulfate (SO42-) 與 thiosulfate (S2O32-) 三個硫物種。由於感應耦合電漿質譜儀分析硫時，氧氣及氮氣會造成嚴重的光譜干擾，因此藉由動態反應槽 (Dynamic reaction cell，DRC) 來減輕此影響。在層析方面，使用PRP-X100陰離子交換層析管柱有效的分離，沖堤液則為60 mM 硝酸銨及0.1% (v/v)甲醛與pH 7.0的混合溶液。霧化輸入裝置使用超音波霧化器，樣品分析前會經過加熱及冷凝步驟，將分析物表面的有機溶劑去除，有助於大幅提升分析物訊號並降低背景。本研究可於4.5分鐘內分離SO32-、SO42- 及S2O32-，所得偵測極限分別為3.4、3.1與3.7 ng mL-1，滯留時間、波峰高度與面積之相對標準偏差皆小於3.4% (n=5)。實驗以沖堤液硝酸銨作為萃取試劑，並使用超音波水浴振盪萃取，利用標準參考樣品NIST1573a Tomato Leaves驗證方法準確性後，應用於市售金針花及枸杞樣品中含硫化合物的分析應用。
第二部分研究為液相層析法結合感應耦合電漿質譜儀分析食米中TMAO (Triethylarsine oxide)、DMA (Dimethylarsinic acid)、MMA (Monomethylarsonic acid)、As(III) 和As(Ⅴ) 等砷物種。砷元素具有許多不同的物種形態，而形態的差異對於生物體作用及危害程度也大不相同，因此對於真實樣品進行物種分析，可更準確評估是否對於人體健康造成影響。實驗使用PRP-X100陰離子交換管柱分離，沖堤液為50 mM (NH4)2CO3、3% (v/v)甲醇與pH 9.0的混合溶液，並於DRC模式通入氧氣，將75As+ 反應成75As16O+，藉以避免40Ar35Cl+ 產生的光譜干擾，可於5分鐘內將TMAO、MMA、DMA及As(V)分離，偵測極限介於0.004-0.007 ng mL-1之間。研究使用0.2 M H2O2及0.1 M HNO3作為萃取試劑，將樣品中As(III) 氧化成As(V)，不僅可使物種分離解析度較佳，更方便精準計算無機砷物種的含量。最後將本方法應用於SRM 1568a Rice Flour標準參考樣品、糙米及米精樣品，驗證方法準確性及可行性。
關鍵詞：感應耦合電漿質譜儀、動態反應槽、液相層析法、硫、砷、食品

Abstract
First part of my research focused on high-performance liquid chromatography-inductively coupled plasma mass spectrometry (HPLC-ICP-MS) for the speciation of sulfur containing compound, namely sulfite (SO32-), sulfate (SO42-), and thiosulfate (S2O32-) in dry foods. However, there is a critical spectral interference in the analysis of sulfur by ICP-MS because of the oxygen and nitrogen gas in atmosphere nature. To resolve these problem, introducing dynamic reaction cell (DRC) coupled with ICP-MS followed by a chromatography was performed by using anion-exchange liquid chromatography with PRP-X100 column, using 60 mM ammonium nitrate (NH4NO3) and 0.1% (v/v) formaldehyde mixture at pH 7.0 as a mobile phase. The atomized input device was ultrasonic nebulizer. Before analyzing, the samples would employ desolvation and condensation process in order to remove the organic solvent which is adsorbed on the surface. These stringent procedures whereas significantly increase the analysis signal and decline the background. The overall analysis time this can be applied to within 4.5 minutes. The detection limits for SO32-, SO42-, and S2O32- were found to be 3.4, 3.1, and 3.7 ng mL-1, respectively. The relative standard deviations of the retention time, peak height, and peak area are all less than 3.4% (n=5). The samples were extracted with mobile phase by ultrasonic extraction method. The accuracy of this method was verified by the standard reference sample NIST1573a Tomato Leaves, and applied on the sulfur analysis of orange daylily and wolfberry.
Second part of my research focused on high-performance liquid chromatography-inductively coupled plasma mass spectrometry (HPLC-ICP-MS) for the speciation of arsenic, such as Triethylarsine oxide (TMAO), Dimethylarsinic acid (DMA), Monomethylarsonic acid (MMA), and also As(III)/As(V) which involved multiple rice samples. Arsenic occurs in a variety of chemical forms in natural environment, including organic and inorganic species. The different types of arsenic cause the distinct level of danger to humankind. Therefore, the qualitative analysis of individual species in real samples is an important issue to reveal the influences on human health. The chromatographed was performed by anion-exchange liquid chromatography with PRP-X100 column, using 50 mM ammonium carbonate ((NH4)2CO3) and 3% (v/v) methanol mixture at pH 9.0 as a mobile phase. The experimental setup introduced the DRC-ICP-MS as the element specific detector with oxygen as reaction gas transfer the mass of arsenic to 75As16O+ at m/z 91 in order to avoid the spectral interference on 40Ar35Cl+. The separation of arsenic species could be achieved less than 5 minutes and the detection limits were found to be 0.004-0.007 ng mL-1. Moreover, we used 0.2 M H2O2 and 0.1 M HNO3 mixture as extraction reagent to oxidize form As(III) to As(V), which is given better efficiency, and also proven that higher accuracy on calculating the concentration of individual inorganic arsenic species. Finally, this method was applied on SRM 1568a Rice Flour standard reference sample, brown rice, and rice cereal samples, in order to verify the accuracy and feasibility of this technique.
Keywords: HPLC-ICP-MS, Dynamic reaction cell, Sulfur, Arsenic, Food

目錄
論文審定書 i
謝誌 ii
摘要 iii
Abstract iv
目錄 vi
圖目錄 viii
表目錄 x

第一章 液相層析結合感應耦合電漿質譜儀於食品中含硫化合物之分析應用
壹、前言 1
一、研究背景 1
二、動態反應槽簡介 3
貳、實驗部分 5
一、儀器裝置 5
二、藥品及溶液的配製 9
參、實驗過程 10
一、液相層析分離條件探討 10
二、超音波霧化器系統最適化探討 10
三、DRC-ICP-MS系統最適化探討 10
四、再現性、校正曲線與偵測極限的預估 11
五、真實樣品分析 12
肆、結果與討論 16
一、液相層析分離條件探討 16
二、超音波霧化器系統最適化探討 22
三、DRC-ICP-MS系統最適化探討 26
四、再現性、校正曲線與偵測極限的預估 34
五、萃取條件最適化 34
六、真實樣品分析 37
伍、結論 48
陸、參考文獻 49

第二章 液相層析結合感應耦合電漿質譜儀於食米中砷化合物之分析應用
壹、前言 54
貳、實驗部分 57
一、儀器裝置 57
二、藥品及溶液的配製 59
參、實驗過程 63
一、液相層析分離條件探討 63
二、DRC-ICP-MS系統最適化探討 63
三、再現性、校正曲線與偵測極限的預估 64
四、真實樣品分析 64
肆、結果與討論 69
一、液相層析分離條件探討 69
二、DRC-ICP-MS系統最適化探討 77
三、再現性、校正曲線與偵測極限的預估 80
四、萃取條件最適化 85
五、真實樣品分析 90
伍、結論 100
陸、參考文獻 101

圖目錄
第一章 液相層析結合感應耦合電漿質譜儀於食品中含硫化合物之分析應用
圖1-1超音波霧化器裝置圖 7
圖1-2 HPLC-USN-DRC-ICP-MS之系統圖 8
圖1-3實驗流程圖 14
圖1-4樣品萃取流程圖 15
圖1-5沖堤液pH值對於層析的影響 17
圖1-6沖堤液中NH4NO3濃度對於層析的影響 18
圖1-7沖堤液流速對於層析的影響 20
圖1-8載流氣體流速對硫訊號與背景之影響 23
圖1-9去溶劑管溫度對硫訊號與背景之影響 24
圖1-10冷凝管溫度對硫訊號與背景之影響 25
圖1-11改變O2反應氣體流速對硫訊號與背景之影響 27
圖1-12改變Rpq值對硫訊號與背景之影響 28
圖1-13改變AFV值對硫訊號與背景之影響 30
圖1-14改變電漿輸出功率對硫訊號與背景之影響 31
圖1-15比較DRC系統對分析物之增益效果 33
圖1-16比較使用超音波振盪與微波輔助萃取不同溫度之萃取效率 38
圖1-17萃取時間對於萃取效率之影響 39
圖1-18 NIST1573a Tomato Leaves 標準參考樣品萃取液層析圖 41
圖1-19金針花樣品1萃取液層析圖 43
圖1-20金針花樣品2萃取液層析圖 44
圖1-21枸杞樣品萃取液層析圖 46

第二章 液相層析結合感應耦合電漿質譜儀於食米中砷化合物之分析應用
圖2-1 HPLC-DRC-ICP-MS系統圖 58
圖2-2砷物種之結構式 61
圖2-3砷物種於各pH值環境下之化學式及pKa値 62
圖2-4實驗流程圖 67
圖2-5樣品萃取流程圖 68
圖2-6改變沖堤液pH值對層析分離的影響 70
圖2-7改變沖堤液中 (NH4)2CO3濃度對層析分離的影響 72
圖2-8改變沖堤液中甲醇濃度對層析分離的影響 73
圖2-9改變沖堤液流速對層析分離的影響 75
圖2-10注入2 ng mL-1砷標準品及20 µg mL-1氯離子之層析圖 78
圖2-11改變O2反應氣體流速對砷訊號與背景之影響 79
圖2-12改變Rpq值對砷訊號與背景之影響 81
圖2-13改變AFV值對砷訊號與背景之影響 82
圖2-14不同模式下砷物種之層析圖 84
圖2-15萃取溫度對糙米樣品中砷的萃取效率 88
圖2-16萃取時間對糙米樣品中砷的萃取效率 89
圖2-17 SRM 1568a Rice Flour萃取液層析圖 92
圖2-18糙米樣品1萃取液層析圖 95
圖2-19糙米樣品2萃取液層析圖 96
圖2-20米精樣品萃取液層析圖 98

表目錄
第一章 液相層析結合感應耦合電漿質譜儀於食品中含硫化合物之分析應用
表1-1 以四極柱式ICP-MS測定硫元素之質量重疊干擾 11
表1-2微波消化升溫程式條件 12
表1-3沖堤液流速對32S16O波峰高度之S/B的影響 21
表1-4沖堤液流速對34S16O波峰高度之S/B的影響 21
表1-5硫物種分析在HPLC-USN-DRC-ICP-MS系統最適化條件 32
表1-6以HPLC-USN-DRC-ICP-MS測定硫物種之滯留時間及訊號再現性 35
表1-7以HPLC-USN-DRC-ICP-MS測定硫物種之校正曲線與偵測極限 35
表1-8硫物種偵測極限之比較 (ng mL-1) 36
表1-9以HPLC-USN-DRC-ICP-MS測定NIST1573a樣品中硫物種之含量 42
表1-10以HPLC-USN-DRC-ICP-MS測定金針花樣品中硫物種之含量 45
表1-11以HPLC-USN-DRC-ICP-MS測定枸杞樣品中硫物種之含量 47

第二章 液相層析結合感應耦合電漿質譜儀於食米中砷化合物之分析應用
表2-1砷物種化合物之半數致死量 56
表2-2微波消化升溫程式條件 65
表2-3沖堤液中甲醇濃度對75As波峰高度之S/B的影響 74
表2-4沖堤液中甲醇濃度對75As波峰積分面積之S/B的影響 74
表2-5沖堤液流速對75As波峰高度之S/B的影響 76
表2-6沖堤液流速對75As波峰積分面積之S/B的影響 76
表2-7砷物種分析在HPLC-DRC-ICP-MS系統最適化條件 83
表2-8以HPLC-DRC-ICP-MS測定砷物種之滯留時間及訊號再現性 86
表2-9以HPLC-DRC-ICP-MS測定砷物種之校正曲線與偵測極限 86
表2-10砷物種偵測極限之比較 (ng mL-1) 87
表2-11以HPLC-DRC-ICP-MS測定SRM 1568a中砷物種之含量 93
表2-12比較各研究中，SRM 1568a Rice Flour中砷物種之含量 94
表2-13以HPLC-DRC-ICP-MS測定糙米樣品中砷物種之含量 97
表2-14以HPLC-DRC-ICP-MS測定米精樣品中砷物種之含量 99

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第二章
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