Laser induced breakdown spectroscopy (LIBS) is a rapid optical spectroscopy technique for elemental determination, which has been used for quantitative analysis in many fields. However, the calibration involving atomic emission intensity and sample concentration, is still a challenge due to physical-chemical matrix effect of samples and fluctuations of experimental parameters. To overcome these problems, various chemometric data analysis techniques have been combined with LIBS technique. In this study, LIBS was used to show its potential as a routine analysis for Na measurements in bakery products. A series of standard bread samples containing various concentrations of NaCl (0.025%–3.5%) was prepared to compare different calibration techniques. Standard calibration curve (SCC), artificial neural network (ANN) and partial least square (PLS) techniques were used as calibration strategies. Among them, PLS was found to be more efficient for predicting the Na concentrations in bakery products with an increase in coefficient of determination value from 0.961 to 0.999 for standard bread samples and from 0.788 to 0.943 for commercial products.

中文翻译：

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烘焙产品中激光诱导击穿光谱不同校准技术的比较：关于 NaCl 测量

激光诱导击穿光谱（LIBS）是一种用于元素测定的快速光学光谱技术，已被用于许多领域的定量分析。然而，由于样品的物理化学基质效应和实验参数的波动，涉及原子发射强度和样品浓度的校准仍然是一个挑战。为了克服这些问题，各种化学计量数据分析技术已与 LIBS 技术相结合。在这项研究中，LIBS 被用来展示其作为烘焙产品中 Na 测量常规分析的潜力。制备了一系列含有不同浓度 NaCl (0.025%–3.5%) 的标准面包样品，以比较不同的校准技术。标准校准曲线 (SCC)，人工神经网络 (ANN) 和偏最小二乘 (PLS) 技术被用作校准策略。其中，PLS 被发现更有效地预测烘焙产品中的 Na 浓度，标准面包样品的测定系数值从 0.961 增加到 0.999，商业产品从 0.788 增加到 0.943。