Classification of Changbai Mountains Pork Based on Laser-Induced Breakdown Spectroscopy
LIN Xiao-mei1, SUN Hao-ran2, XU Yu-ting3, LIN Jing-jun2, WANG Yue4, WANG Zhen-xing4, GAO Xun3*
1. Department of Electronics and Electrical Engineering, Changchun University of Technology, Changchun 130012, China
2. Department of Mechanical and Electrical Engineering, Changchun University of Technology, Changchun 130012, China
3. School of Science, Changchun University of Science and Technology, Changchun 130022, China
4. Department of Thoracic Surgery, China-Japan Union Hospital of Jilin University, Changchun 130033, China
Abstract：The internal structure of pork is complex, the matrix effect is strong, the components of each part are similar, so it is not easy to distinguish. Combined with laser-induced breakdown spectroscopy, the classification accuracy is improved by spectral analysis. Five different parts of Changbai Mountains Pork (tenderloin, plum blossom, hind leg, front leg and streaky pork) were used as the samples to be tested. The feasibility of identifying pork fat, muscle and their different parts by laser-induced breakdown spectroscopy was explored by means of cold storage, slice and other pretreatment methods. Firstly, by collecting LIBS spectral line information of fat pork samples and muscle samples, it is found that Mg, K, Fe, Cu, CA, Na and other elements are abundant in pork, and C—N bond is found in the spectrum of fat samples. Compared with LIBS spectral line information of muscle samples, the background and noise signal of the spectral line information of fat samples are greatly disturbed due to the influence of their internal moisture and organic matter composition. There are some differences, which indicates that LIBS can be used to distinguish adipose tissue from muscle tissue. Through the detection of the LIBS characteristic spectral intensity of the target elements Ca, Na, Mg, K and Al, the ratios of mg/Ca, Al/Ca, Na/Ca and K/Ca were calculated. It was found that the distribution of element ratio of Na/Ca and K/Ca was significantly different from that of Al/Ca and Mg/ca. On this basis, according to the ratio of Na/Ca and K/Ca, the decision threshold of element distribution of pork was calculated [(1-α)=90%]. It is found that Na/Ca and K/CA can reflect the distribution of elements more clearly than Al/Ca and Mg/ca. The threshold value of the ratio distribution can be used to distinguish different parts of pork. Taking the front leg meat and the back leg meat as an example, the Na/Ca and K/Ca ratios of the front leg meat were 1.29～1.58 and 0.31～0.42 respectively, and the Na/Ca and K/Ca ratios of the back leg meat were 0.98～1.18 and 0.15～0.23 respectively. There was no obvious overlap in the distribution of element ratio. Finally, in order to improve the reliability of LIBS technology in the classification of different tissues of pork, the spectral element intensity ratio data and principal component analysis method are combined, which can basically achieve the classification of various parts of pork, indicating that the element characteristic spectral line intensity ratio has certain prediction accuracy in the classification of various parts of pork. The whole work has proved that it is feasible to use laser-induced breakdown spectroscopy in qualitative analysis of pork, such as classification and identification, which is expected to be suitable for other biological tissue detection and analysis.
Key words：Laser induced breakdown spectroscopy (LIBS); Classification of pork parts; Element intensity ratio; Principal component analysis
林晓梅，孙浩然，许毓婷，林京君，王 跃，王振兴，高 勋. 基于激光诱导击穿光谱对长白山黑猪肉部位分类[J]. 光谱学与光谱分析, 2021, 41(01): 299-304.
LIN Xiao-mei, SUN Hao-ran, XU Yu-ting, LIN Jing-jun, WANG Yue, WANG Zhen-xing, GAO Xun. Classification of Changbai Mountains Pork Based on Laser-Induced Breakdown Spectroscopy. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2021, 41(01): 299-304.
[1] RAO Gang-fu, WANG Cai-hong，HUANG Lin，et al(饶刚福, 王彩虹, 黄 林，等). Chinese Journal of Analysis Laboratory（分析实验室），2017，36(4): 70.
[2] Sacristán D, Rossel R A V, Recatalá L. Geoderma, 2016, 265: 6.
[3] Tu Y, Ju S, Wang P. Spectroscopy Letters, 2016, 49(4): 8.
[4] Gaudiuso R, Ewusi-Annan E, Melikechi N，et al. Spectrochimica Acta Part B: Atomic Spectroscopy，2018，146: 106.
[5] Chen X, Li X, Yu X，et al. Spectrochimica Acta Part B: Atomic Spectroscopy，2018，139: 63.
[6] Ghasemi F, Parvin P, Motlagh N S H，et al. Applied Optics, 2016, 55(29): 8227.
[7] Francisco J, Fortes & Maria D, Perez-Carcelesetal. International Journal of Legal Medicine, 2015, 129(4): 807.
[8] Gill R K, Smith Z J, Lee Cetetal. Journal of Biophotonics，2016, 9(1-2): 171.
[9] Li X H, Yang S B, Fan R W, et al. Optics and Laser Technology, 2018, 102: 233.
[10] Yueh F Y, Zheng H B, Singh J P, et al. Spectrochimica Acta Part B: Atomic Spectroscopy, 2009, 64: 1059.
[11] Bilge G, Velioglu H M, Sezer B，et al. Meat Science, 2016, 119(9): 118.
[12] Yao M Y, Rao G F，Huang L, et al. Applied Optics, 2017, 56(29): 8148.
[13] Huang H, Yang L M, Bai S，et al. Journal of Biomedical Optics, 2015, 8972(1): 115.
