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Accuracy Improvement of Geographical Indication of Rice By Laser-Induced Breakdown Spectroscopy Using Support Vector Machine with Multi-Spectral Line

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Journal of Applied Spectroscopy Aims and scope

Mislabeling and adulteration are problems in the food industry. Considering the frequent occurrence of safety affairs in agricultural products, it is necessary to establish a traceability system for the quality and safety of agricultural products. The aim of the present study was to establish a rapid detection method for distinguishing rice samples from ten different products of geographical indication in China using laser-induced breakdown spectroscopy (LIBS). A support vector machine (SVM) is used to calculate the recognition rate of single spectral lines and multi-spectral lines of the geographic origins of rice. The adjusting spectral weighting of the multi-spectral line composition of mineral metal elements is higher, which can effectively improve the identification rate of the origin of the rice. The results show that the classification accuracies of single spectral line recognition and multi-spectral line recognition are 90.8 and 94.6%, respectively. It can be concluded that the LIBS technique combined with SVM should be a promising tool for rapidly distinguishing different geographic origins of rice.

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Authors and Affiliations

  1. Institute of Electronics, Changzhou College of Information Technology, Changzhou, Jiangsu, China

    P. Yang, H. T. Liu, Z. L. Nie & X. N. Qu

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  1. P. Yang
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  2. H. T. Liu
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  3. Z. L. Nie
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  4. X. N. Qu
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Correspondence to P. Yang.

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Abstract of article is published in Zhurnal Prikladnoi Spektroskopii, Vol. 89, No. 3, p. 434, May–June, 2022.

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Yang, P., Liu, H.T., Nie, Z.L. et al. Accuracy Improvement of Geographical Indication of Rice By Laser-Induced Breakdown Spectroscopy Using Support Vector Machine with Multi-Spectral Line. J Appl Spectrosc 89, 579–585 (2022). https://doi.org/10.1007/s10812-022-01397-3

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  • DOI: https://doi.org/10.1007/s10812-022-01397-3

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