Evaluation of Sample Preparation Methods for the Classification of Children’s Ca–Fe–Zn Oral Liquid by Libs

IF 0.8 4区 化学 Q4 SPECTROSCOPY Journal of Applied Spectroscopy Pub Date : 2024-03-08 DOI:10.1007/s10812-024-01708-w
Weiping Xie, Gangrong Fu, Jiang Xu, Min Zeng, Qi Wan, Xiaoying Yao, Ping Yang, Mingyin Yao
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Abstract

Different manufacturers do not produce the same quality of children’s Ca–Fe–Zn oral liquid due to different production materials and processes. To improve the phenomenon of counterfeit and imitation oral liquid on the market and effectively monitor its quality, laser-induced breakdown spectroscopy (LIBS) fingerprinting with sample preparation methods can provide a tool for real-time and rapid detection of oral liquids. The sample preparation methods include filter paper adsorption (FPA), filter paper adsorption with elemental Cu (FPA with Cu), adding dropwise to glass slides (ADS), adding dropwise to glass slides with elemental Cu (ADS with Cu), and gel preparation (GP). This work collected LIBS spectrum of oral liquids from eight manufacturers. The model for eXtreme Gradient Boosting (XGBoost) was constructed for classifying oral liquids based on five sample preparation methods. The accuracy was 91.25, 94.17, 55.42, 91.25, and 91.29%, respectively. The results show that the FPA method is more straightforward, efficient, and less affected by the specificity of the color of the sample. Both ADS and GP are susceptible to the color characteristics of the sample and are not well suited to the direct detection of transparent liquids. This work demonstrated that oral liquids could be discriminated by analyzing LIBS spectrum combined with the XGBoost model. Additionally, sample preparation, like the simple FPA method, can improve the accuracy of LIBS classification.

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评估用 Libs 对儿童钙铁锌口服液进行分类的样品制备方法
由于生产材料和工艺的不同,不同厂家生产的儿童钙铁锌口服液质量并不相同。为改善市场上假冒伪劣口服液的现象,有效监控其质量,激光诱导击穿光谱(LIBS)指纹图谱结合样品制备方法可为口服液的实时快速检测提供工具。样品制备方法包括滤纸吸附法(FPA)、滤纸吸附加铜元素法(FPA with Cu)、滴加玻璃载玻片法(ADS)、滴加玻璃载玻片加铜元素法(ADS with Cu)和凝胶制备法(GP)。这项工作收集了八家制造商生产的口服液的 LIBS 光谱。根据五种样品制备方法,构建了用于口服液分类的极梯度提升(XGBoost)模型。准确率分别为 91.25%、94.17%、55.42%、91.25% 和 91.29%。结果表明,FPA 方法更简单、高效,受样品颜色特异性的影响较小。ADS 和 GP 都容易受样品颜色特征的影响,不太适合直接检测透明液体。这项工作证明,通过分析 LIBS 光谱和 XGBoost 模型,可以对口服液进行鉴别。此外,样品制备(如简单的 FPA 方法)也能提高 LIBS 分类的准确性。
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来源期刊
CiteScore
1.30
自引率
14.30%
发文量
145
审稿时长
2.5 months
期刊介绍: Journal of Applied Spectroscopy reports on many key applications of spectroscopy in chemistry, physics, metallurgy, and biology. An increasing number of papers focus on the theory of lasers, as well as the tremendous potential for the practical applications of lasers in numerous fields and industries.
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