• Spectroscopy and Spectral Analysis
  • Vol. 37, Issue 12, 3859 (2017)
JIANG Bo1、2, HUANG Jian-hua3, and LIU Wei3
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
  • 3[in Chinese]
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    DOI: 10.3964/j.issn.1000-0593(2017)12-3859-06 Cite this Article
    JIANG Bo, HUANG Jian-hua, LIU Wei. Multi-Element Analysis of Wild Chinese Honeylocust Fruit by Inductively Coupled Plasma Tandem Mass Spectrometry (ICP-MS/MS)[J]. Spectroscopy and Spectral Analysis, 2017, 37(12): 3859 Copy Citation Text show less

    Abstract

    An analysis method was developed to detect trace elements in Chinese Honeylocust Fruit by using inductively coupled plasma tandem mass spectrometry (ICP-MS/MS). All samples were microwave digested by using (HNO3+H2O2+HCl). In the MS/MS mode, the polyatomic interferences were eliminated by the utilization of O2 mass shift, O2 on-mass, and NH3 mass shift with O2 or NH3 in the collision/reaction cell of the ICP-MS/MS. The analytical results of proposed method were validated by analysis of the national standard reference samples of green tea (GBW10052) and celery (GBW10048), which showed good agreement with the certified values, RSD≤7.8%. Furthermore, 12 trace elements (V, Cr, Co, Cu, Zn, Fe, Mn, Ni, As, Cd, Hg, and Pb) in these samples collected from Yunnan and Chongqing Wuling Mountain, were detected by proposed analyzed method. The detection limits of the analytes were in the range of 0.29~21.36 ng·L-1. The analytical results showed that Fe and Zn elements were rich in these wild samples, while heavy elements in these samples were lower than limitation standard of Chinese pharmacopoeia. This study can be used to estimate the trace element and quality of wild honey locust. Also, this study can provide scientific methods and data for the safety assessment and regulation of trace elements in Chinese Honeylocust Fruit.
    JIANG Bo, HUANG Jian-hua, LIU Wei. Multi-Element Analysis of Wild Chinese Honeylocust Fruit by Inductively Coupled Plasma Tandem Mass Spectrometry (ICP-MS/MS)[J]. Spectroscopy and Spectral Analysis, 2017, 37(12): 3859
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