開發磁性金屬有機骨架材料作為新興吸附劑檢測茶飲中新興汙染物parabens之殘留

Please use this identifier to cite or link to this item: https://ir.lib.ncu.edu.tw/handle/987654321/97363

Title:	開發磁性金屬有機骨架材料作為新興吸附劑檢測茶飲中新興汙染物parabens之殘留
Authors:	徐珮瑄;Hsu, Pei-Hsuan
Contributors:	化學學系
Keywords:	防腐劑;對羥基苯甲酸酯;磁性金屬有機骨架材料;磁性固相萃取法;新興汙染物;Preservative;para-hydroxybenzoates;Magnetic matel-organic frameworks;Magnetic solid phase extraction;Emerging Contaminants
Date:	2025-06-18
Issue Date:	2025-10-17 11:11:36 (UTC+8)
Publisher:	國立中央大學
Abstract:	新興汙染物—Parabens是一種常見的防腐劑，由於其具有效的抗菌能力、化學穩定性佳、生產成本低、致敏頻率低等優點，已被廣泛運用於日常生活用品與食品中，然而其為疑似內分泌干擾物質與持久性化合物，會對人類健康與生態環境帶來負面影響。此外，飲料店茶飲已成為現代人日常生活中不可或缺的一部分，因此選擇茶飲作為樣品，有助於監測日常消費品中Parabens使用之情況。本研究主要在開發一種高效、快速、簡單、低成本且環境友善之檢測方法，用於分析飲料店茶樣中Parabens之殘留。透過新興多孔材料—磁性金屬有機骨架材料Fe3O4@ZIF-67作為吸附劑結合磁性固相萃取法(MSPE)進行樣品前處理，此法同時具有高效的吸附性能和良好的分離特性，並展現節約能源、節省時間、操作簡單、溶劑使用量少等優勢，再搭配靈敏度高之超高效液相層析儀串聯電灑游離法(-)四極桿飛行時間式質譜儀(UHPLC-ESI(-)-QTOF-MS)儀器進行檢測，及利用高解析汲取離子層析圖模式(hrXIC)提升目標待測物之訊雜比(S/N)，從而有效檢測茶樣中七種防腐劑成分Parabens之殘留。於樣品前處理中，本研究同時利用單因子探討非數值因子以及Box-Behnkne Design(BBD)實驗設計探討數值因子之最佳化萃取條件，藉此提高目標待測物的萃取效率。本研究所開發之方法其偵測極限(LOD)範圍介於0.001-0.08 ng/mL；Intra day及Inter day之相對標準偏差RSD ≤ 5%，展現出優良的靈敏度及精密度，且檢量線之R2值皆大於0.9959，真實茶樣之萃取回收率介於93-116%，藉此可證實本研究具有良好的再現性、穩定性與準確性。最後透過Fe3O4@ZIF-67-MSPE前處理法結合UHPLC-ESI(-)-QTOF-MS進行飲料店茶飲的檢測，成功檢測出防腐劑MeP和BzP之微量殘留。;Contaminants of emerging concern—Parabens are a common preservative. Due to their effective antimicrobial ability, good chemical stability, low production cost, and low frequency of sensitization, they have been widely used in daily necessities and foods. However, parabens have also been classified as endocrine disrupting chemicals (EDCs) and biorefractory compounds which can be easily accumulated in nature, so they can simultaneously have adverse effects on both the ecosystem and human health. Furthermore, tea drinks in beverage shops have become an integral part of the daily life of Taiwan society, so selecting tea beverages as samples aids in monitoring the use of parabens in daily consumer products. The purpose of this study is to develop an efficient, rapid, simple , low-cost ,and environmentally friendly detection method for analyzing the residues of parabens in tea samples from beverage shops. In this study, we synthesized magnetic metal-organic frameworks—Fe3O¬4@ZIF-67 as an adsorbent which is a group of emerging porous materials, then combined with magnetic solid-phase extraction (MSPE) for sample pretreatment. This method concurrently exhibits high adsorption efficiency and good separation characteristics, along with advantages such as energy and time savings, simple operation, and less solvent used. Subsequently, ultra-high performance liquid chromatography electrospray ionization(-)-quadrupole time-of-flight mass spectrometry(UHPLC-ESI(-)-QTOF-MS) was applied for detection, and in conjunction with high-resolution extraction ion chromatograms (hrXIC) technique to increase the signal-to-noise ratio (S/N). Therefore, it can effectively detect seven selected parabens from tea beverage samples. In sample pretreatment, this study used both one-factor-at-a-time to explore the optimal extraction conditions of non-numerical factors and experimental design software Box-Behnkne Design (BBD) to explore the optimal extraction parameters of numerical factors, thereby improving the extraction efficiency of the target analytes. The method developed in this study provided low limit of detection (LOD), ranging from 0.001-0.08 ng/mL, and showed excellent sensitivity. Precision was assessed using intra day and inter day analysis, which relative standard deviation (RSD) was all less than 5% with excellent precision. The linearities of R2 was large than 0.9959 and the extraction recovery was between 93% and 116%, confirming that this study exhibits good reproducibility, stability, and accuracy. In conclusion, the developed Fe3O4@ZIF-67-MSPE sample preparation method combined with UHPLC-ESI(-)-QTOF-MS was successfully applied to detect parabens residues in tea samples from beverage shops.
Appears in Collections:	[Graduate Institute of Chemistry] Electronic Thesis & Dissertation

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