Identification of Pork Parts Based on LIBS Technology Combined With PCA-SVM Machine Learning

Yu-ting XU; Hao-ran SUN; Xun GAO; Kai-min GUO; Jing-quan LIN

doi:10.3964/j.issn.1000-0593(2021)11-3572-05

Journals >Spectroscopy and Spectral Analysis >Volume 41 >Issue 11 >Page 3572 > Article

Spectroscopy and Spectral Analysis
Vol. 41, Issue 11, 3572 (2021)

Identification of Pork Parts Based on LIBS Technology Combined With PCA-SVM Machine Learning

Yu-ting XU^1,*, Hao-ran SUN^2,2;, Xun GAO^{1,1; *;}, Kai-min GUO^{3,3; *;}, and Jing-quan LIN^1,1;

Author Affiliations

¹1. College of Science, Changchun University of Science and Technology, Changchun 130022, China

²2. College of Mechanical and Electrical Engineering, Changchun University of Technology, Changchun 130012, China

³3. College of Physical Science and Technology, Baotou Normal University, Baotou 014030, China

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DOI: 10.3964/j.issn.1000-0593(2021)11-3572-05 Cite this Article

Yu-ting XU, Hao-ran SUN, Xun GAO, Kai-min GUO, Jing-quan LIN. Identification of Pork Parts Based on LIBS Technology Combined With PCA-SVM Machine Learning[J]. Spectroscopy and Spectral Analysis, 2021, 41(11): 3572 Copy Citation Text

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Fig. 1. LIBS experimental setup

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Fig. 2. LIBS spectrograms of four pork parts

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Fig. 3. Principal component contribution rate and cumulative contribution rate

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Fig. 4. Scatter plots of four pork tissues

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Fig. 5. PCA-SVM classification recognition confusion matrix for pork parts

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