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Quantitative models for detecting the presence of lead in turmeric using Raman spectroscopy

机译:使用拉曼光谱检测姜黄中铅存在的定量模型

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摘要

The current study presents a novel methodology to quantify lead in Turmeric using Raman spectroscopy. In this study, Partial Least Squares Regression (PLSR) was used for the quantification of lead. For calibration purposes, different amounts of lead were added to Turmeric samples encompassing a concentration range between 4 and 25 mu g g(-1). Since lead does not show any Raman band, for the purposes of this study, a complex was formed, its solvent was evaporated and the complex solid samples were registered with a Raman instrument. Raman measurements were performed in two different modes, -diffuse reflectance and transmission-. The PLSR models developed from Raman spectra of two data acquisition modes were evaluated in order to determine the suitability of both acquisition modes for quantifying lead content. The results indicated that diffuse reflectance showed better performance in terms of accuracy and robustness with a bias of 0.55 mu g g(-1), a relative standard error of prediction (RSEP) of 8.5% and a correlation between the predicted and reference values (R-2) of 0.967. Despite the low lead concentration in the samples, the proposed model allows the quantification of the lead content in a fast and simple way.
机译:目前的研究呈现了使用拉曼光谱法测量姜黄中铅的新方法。在该研究中,部分最小二乘回归(PLSR)用于定量铅。为了校准目的,将不同量的铅加入到包含4-25μg(-1)之间的浓度范围的姜黄样品中。由于铅不显示任何拉曼带,出于该研究的目的,形成复合物,蒸发溶剂,并将复合的固体样品用拉曼仪器注册。拉曼测量以两种不同的模式进行, - 脱凡士反射和传输。评估由两种数据采集模式的拉曼光谱显影的PLSR模型,以确定用于量化铅含量的采集模式的适用性。结果表明,弥散反射率在精度和稳健性方面表现出更好的性能,偏差为0.55μg(-1),预测(RSEP)的相对标准误差为8.5%,并且预测和参考值之间的相关性(R -2)0.967。尽管样品中的铅浓度低,所提出的模型允许以快速简单的方式定量铅含量。

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