Method for identifying acacia honey adulterated by resin absorption: HPLC-ECD coupled with chemometrics
Method for identifying acacia honey adulterated by resin absorption: HPLC-ECD coupled with chemometrics
复制标题
树脂吸附鉴别金合欢蜂蜜掺假的方法：HPLC-ECD 结合化学计量学
DOI：
10.1016/j.lwt.2019.108863
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发表时间：
2020
影响因子：
6
通讯作者：
曹炜
中科院分区：
文献类型：
--
作者：
王倩;赵浩安;祝敏;张锦锦;程妮;曹炜
蜂蜜掺假是一个普遍的安全和质量问题。树脂技术作为一种新的掺假技术，可以去除或减少蜂蜜中的有害物质，制造出不合格的蜂蜜，使不合格的产品进入市场。因此，识别这种掺假产品是非常重要的。本文采用HPLC-ECD结合化学计量学方法对大孔吸附树脂处理后的洋槐蜜进行了鉴别。分析了金合欢蜂蜜的理化特性，并对金合欢蜂蜜进行了树脂处理。建立了蜂蜜样品的色谱指纹图谱，并采用主成分分析（PCA）和正交投影-潜在结构判别分析（OPLS-DA）对样品进行分析。结果表明，可以区分生相思蜜和树脂处理的蜂蜜。综上所述，采用HPLC-ECD结合化学计量学方法可以检测树脂工艺的洋槐蜜掺假。
Honey adulteration is a general safety and quality concern. Resin technology, as a new kind of adulteration, could remove or reduce harmful substances in honey to create substandard honey, which would enable substandard products to enter the market. Thus, it is urgently important to identify such adulterated products. In this work, raw acacia honey treated with macroporous adsorption resins (MARs) was distinguished by HPLC-ECD coupled with chemometrics. The physicochemical characterization of raw acacia honey and acacia honey treated with resins were analyzed. Furthermore, the chromatography fingerprints of honey samples were established, and samples were analyzed using principal component analysis (PCA) and orthogonal projections to latent structures discriminant analysis (OPLS-DA). The results indicated that raw acacia honey could be distinguished from the resin-treated honey. In summary, adulteration of acacia honey with resin technology could be detected by HPLC-ECD combined with chemometrics.
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影响因子：
1.7
作者：
Bini Wang;W. Cao;Huilan Gao;Mingtao Fan;Jianbin Zheng
通讯作者：
Bini Wang;W. Cao;Huilan Gao;Mingtao Fan;Jianbin Zheng
影响因子：
1.8
作者：
Downey, G;Fouratier, V;Kelly, JD
通讯作者：
Kelly, JD
影响因子：
8.8
作者：
Qi Jia;Shifeng Yu;N. Cheng;Liming Wu;Jiajia Jia;X. Xue;W. Cao
通讯作者：
Qi Jia;Shifeng Yu;N. Cheng;Liming Wu;Jiajia Jia;X. Xue;W. Cao
影响因子：
6.1
作者：
Ruiz-Matute, A. I.;Soria, A. C.;Sanz, M. L.
通讯作者：
Sanz, M. L.
影响因子：
3.9
作者：
Wang, Jun;Kliks, Michael M.;Li, Qing X.
通讯作者：
Li, Qing X.