• Spectroscopy and Spectral Analysis
  • Vol. 38, Issue 10, 3295 (2018)
I Rehan1、*, K Rehan1、2, S Sultana3, and R Muhammad1
Author Affiliations
  • 1Department of Applied Physics, Federal Urdu University of Arts, Science and Technology, Islamabad 44000, Pakistan
  • 2State Key Laboratory of Magnetic Resonance and Atomic & Molecular Physics, Wuhan Institute of Physics and Mathematics, Chinese Academy of Sciences, Wuhan 430071, China
  • 3Department of Chemistry, Islamia College University, Peshawar 25120, Pakistan
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    DOI: 10.3964/j.issn.1000-0593(2018)10-3295-08 Cite this Article
    I Rehan, K Rehan, S Sultana, R Muhammad. Laser Induced Breakdown Spectroscopy for Comparative Quantitative Analysis of Betel Leaves from Pakistan[J]. Spectroscopy and Spectral Analysis, 2018, 38(10): 3295 Copy Citation Text show less

    Abstract

    Laser induced breakdown Spectroscopy (LIBS) was applied for the elemental analysis and exposure of the heavy metals in betel leaves in air. Pulsed Nd∶YAG (1064 nm) in conjunction with a suitable detector (LIBS 2000+, Ocean Optics, Inc) having the optical resolution of 0.06 nm was used to record the emission spectra from 220 to 720 nm. Elements like Al, Ba, Ca, Cr, Cu, P, Fe, K, Mg, Mn, Na, P, S, Sr, and Zn were found to present in the samples. The relative abundances of the observed elements were calculated through standard calibration curve method, integrated intensity ratio method, and weight percentage LIBS approach. LIBS findings were validated by comparing its results with the results obtained using a typical analytical technique of Inductively Coupled plasma-optical emission spectroscopy (ICP-OES). Limit of detection (LOD) of the LIBS system was also estimated for heavy metals. The experience gain through this work implies that LIBS could be highly applicable for testing the quality and purity of food products.
    I Rehan, K Rehan, S Sultana, R Muhammad. Laser Induced Breakdown Spectroscopy for Comparative Quantitative Analysis of Betel Leaves from Pakistan[J]. Spectroscopy and Spectral Analysis, 2018, 38(10): 3295
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