Quantitative Analyses of Element Mn in Iron Using Portable Laser-induced Breakdown Spectroscopy with Algorithm of Background Removal Based on Wavelet Transform

Zeng, Qingdong; Zhi-heng, 朱志恒 Zhu; Fan, 邓凡 Deng; Xiang-li, 朱祥李 Zhu; Bo-yun, 王波云 Wang; Yong-jun, 肖永军 Xiao; Liang-bin, 熊良斌 Xiong; Hua-qing, 余华清 Yu; Lianbo, 郭连波 Guo; Xiangyou, 李祥友 Li

doi:10.3788/gzxb20184708.0847014

Cited by 2 publications

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“…[29][30] The low sensitivity and spectral resolution of these instruments have been circumvented by using some simple devices to increase the sensitivity and applying different spectral processing to extract the appropriate analytical information. [30][31][32] In this work, a low-cost LIBS system coupled with a sparkdischarge (SD) for authentication of the geographical origin of honey was evaluated, taking advantage of the speed and reliability of the LIBS and aiming to provide an accessible device for authentication and traceability of honey.…”

Section: Introductionmentioning

confidence: 99%

Protected geographical identification of honey by spark discharge-assisted laser-induced breakdown spectroscopy (LIBS)

Ferreira¹

2021

At.Spectrosc.

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Honey is a natural food that is valued worldwide for its nutritional and therapeutic values. Therefore, authentication of honey based on geographical origin is a guarantee of its genuine properties of honey. In this article, an evaluation of spark discharge-assisted laser-induced breakdown spectroscopy (SD-LIBS) for certification of the geographical origin of honey is reported. Forty-nine samples of multifloral honey produced in four Argentine provinces were considered. The results showed that best classification performance was obtained using smoothing, generalized least squares weighting (GLSW) and mean centering for spectral preprocessing, added to the k-nearest neighbor (k-NN) or Support Vector Machine (SVM) classification algorithms, which provided 100% of correct classification. More importantly, the results of Partial Least Squares -Discriminant Analysis (PLS-DA) pointed to N, Ca, K, Cu, Fe and Mn as key elements for the certification of geographical origin. In addition, the best indicator for verification of the source of honey was found to be in the assessment of the amount of N in honey. These findings confirm SD-LIBS as a promising tool for authentication of honey origin and quality, providing a simple, fast and environmentally friendly solution. The method can be useful for industry, the marketplace and other areas related to food authentication.

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