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.
CITATION STYLE
Zhao, Z., Chen, L., Liu, F., Zhou, F., Peng, J., & Sun, M. (2020). Fast classification of geographical origins of honey based on laser-induced breakdown spectroscopy and multivariate analysis. Sensors (Switzerland), 20(7). https://doi.org/10.3390/s20071878
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