Traceability of honey is highly required by consumers and food administration with the consideration of food safety and quality. In this study, a technique named laser-induced breakdown spectroscopy (LIBS) was used to fast trace geographical origins of acacia honey and multi-floral honey. LIBS emissions from elements of Mg, Ca, Na, and K had significant differences among different geographical origins. The clusters of honey from different geographical origins were visualized with principal component analysis. In addition, support vector machine (SVM) and linear discrimination analysis (LDA) were used to quantitively classify the origins. The results indicated that SVM performed better than LDA, and the discriminant results of multi-floral honey were better than acacia honey. The accuracy and mean average precision for multi-floral honey were 99.7% and 99.7%, respectively. This study provided a fast approach for geographical origin classification, and might be helpful for food traceability.

中文翻译：

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基于激光诱导击穿光谱和多元分析的蜂蜜地理起源快速分类。

考虑到食品安全性和质量，消费者和食品管理部门非常需要蜂蜜的可追溯性。在这项研究中，一种称为激光诱导击穿光谱法（LIBS）的技术被用于快速追踪相思蜂蜜和多花蜂蜜的地理起源。Mg，Ca，Na和K元素的LIBS排放在不同地理来源之间存在显着差异。通过主成分分析将来自不同地理来源的蜂蜜簇可视化。此外，使用支持向量机（SVM）和线性判别分析（LDA）对来源进行定量分类。结果表明，支持向量机的性能优于LDA，而多花蜂蜜的判别结果优于阿拉伯胶。多花蜂蜜的准确度和平均平均准确度为99。分别为7％和99.7％。这项研究提供了一种快速的地理来源分类方法，可能有助于食品的可追溯性。