Nitrone formation: A new strategy for the derivatization of aldehydes and its application on the determination of furfurals in foods by high performance liquid chromatography with fluorescence detection.
Nitrone formation: A new strategy for the derivatization of aldehydes and its application on the determination of furfurals in foods by high performance liquid chromatography with fluorescence detection.
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硝酮形成：醛衍生的新策略及其在高效液相色谱荧光检测法测定食品中糠醛中的应用。
DOI：
10.1016/j.talanta.2017.10.027
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发表时间：
2018
期刊：
影响因子：
6.1
通讯作者：
Hu Xiaosong
中科院分区：
文献类型：
--
作者：
Zhang Ao;Guan Zhaobing;Cai Hongwei;Huang Yiyong;Lin Yawei;Hu Xiaosong
建立了一种新的荧光试剂4-羟氨丙基-7-甲基香豆素（HAMC）生成硝酮的方法，并应用于食品中糠醛的高效液相色谱荧光检测糠醛样品在水性条件下在室温下在少于30分钟内通过HAMC衍生化，并且在没有额外纯化或提取的情况下进行直接HPLC-FLD分析。与其他常规方法相比，硝酮形成法对每个分析物产生单一色谱峰，从而使色谱图更简单，提高了整体灵敏度。方法的检出限低（0.08-0.1 nM），重复性好（日内RSD ≤ 4.2%，日间RSD ≤ 6.7%）。标准曲线的线性范围为0.2-4000 nM，相关系数良好（R ≥ 0.9989）。该方法已成功应用于蜂蜜和咖啡等食品样品中糠醛的测定。该方法准确度高，回收率在89.7%~ 106.7%之间。该方法简便、可靠、灵敏度高，为今后各种来源醛类化合物的研究提供了一种新的方法。
A nitrone formation method using a novel fluorescent reagent 4-hydroxylaminopropyl-7-methoxylcoumarin (HAMC) has been developed and applied for the determination of furfurals in foods using high performance liquid chromatography with fluorescence detection (HPLC-FLD).Furfurals samples were derivatized by HAMC in aqueous condition at room temperature in less than 30 min and were subjected to direct HPLC-FLD analysis without extra purification or extraction. Compared with other conventional methods, nitrone formation method produced single chromatographic peak for each analyte, leading to simpler chromatograms and enhancing the overall sensitivity. Low detection limits at sub-nM level (0.08–0.1 nM) and high repeatabilities (intra-day RSD ≤ 4.2% and inter-day RSD ≤ 6.7%) were achieved. The linear range of the calibration curve was 0.2–4000 nM with good correlation coefficients (R ≥ 0.9989). This method was successfully applied for furfurals determination in food samples, including honey and coffee. The accuracy was satisfactory with recoveries ranging from 89.7% to 106.7% Above all, this pre-column derivatization method is simple, reliable and highly sensitive, providing a promising way for future studies of aldehydes from various sources.