Application of Spectral Key Variable Selection in Non-Destructive Detection of the Qualities of Agricultural Products and Food
WANG Dong1, 3, WU Jing-zhu2*, HAN Ping1, 3*, WANG Kun2
1. Beijing Research Center for Agricultural Standards and Testing （BRCAST）, Beijing Academy of Agricultural and Forestry Sciences, Beijing 100097, China
2. Beijing Key Laboratory of Big Data Technology for Food Safety, Beijing Technology and Business University (BTBU), Beijing 100048, China
3. Laboratory of Quality & Safety Risk Assessment for Agro-Products (Beijing), Ministry of Agriculture and Rural Affairs, Beijing 100097, China
Abstract：The quality of agricultural products and food has always been one of the focuses of attention. The quality and safety of agricultural products and food are related to people’s health and related to social stability and even national security. In recent years, the safety incidents caused by the unqualified quality of agricultural products and food have attracted all social circles’ attention. The supervision of the quality of agricultural products and food has been the key point even difficulty in analysis and detection for a long time. Given a large population, the consumption of agricultural products and food is enormous in China. In the face of such a large number of the needs of non-destructive and rapid detection of agricultural products and food quality, spectroscopy analysis can provide a good solution for the non-destructive and rapid detection for agricultural products and food with the characteristics of fast, non-destructive, efficient, environmentally friendly, on-site testing. However, due to the large amount of data used in the traditional spectral analysis, it is time-consuming in developing calibration models and difficult to complete the online, high-throughput, non-destructive and rapid detection of the large number of agricultural products and food quality. On the other hand, the calculation of such a large number of data has also become one of the main bottlenecks limiting the efficiency of spectral analysis instruments, and the calculation of a large number of data also puts forward very high requirements for the hardware configuration of the instruments, which will increase the application cost of spectral analysis technology indirectly. In recent years, key variable selection has emerged and become a new hotspot of spectral analysis. According to the selection, calibration models can be developed by a few numbers of the key variables, which are of almost the same accuracy to the models developed by the full spectra. Thus it can improve the analytical instruments’ working efficiency effectively and reduce the application cost of the spectral analysis technology. It will also provide reliable technical support for the high-throughput detection of agricultural products and food quality and provide the scientific and technological support for meeting the increasing demand of the people for a better life. In this paper, the applications of spectral key variable selection in the non-destructive detection of grain and grain crops, vegetables, fruits, cash crops, meat, food quality and safety were reviewed. With summarizing others’ works in recent years, the applications of spectral key variable selection technology were summarized from the aspects of selection method, application scope, application effect, and so forth. Finally, the application of spectral key variable selection technology in non-destructive detection of agricultural products and food quality prospected from the aspects of the characteristics and trends of the variable selection methods, the stability and reliability and the practical significance of the selected variables.
王 冬, 吴静珠, 韩 平, 王 坤. 光谱关键变量筛选在农产品及食品品质无损检测中的应用进展[J]. 光谱学与光谱分析, 2021, 41(05): 1593-1601.
WANG Dong, WU Jing-zhu, HAN Ping, WANG Kun. Application of Spectral Key Variable Selection in Non-Destructive Detection of the Qualities of Agricultural Products and Food. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2021, 41(05): 1593-1601.
[1] Cortés V, Blasco J, Aleixos N, et al. Trends in Food Science & Technology, 2019, 85: 138.
[2] Naidoo L, Cho M A, Mathieu R, et al. ISPRS Journal of Photogrammetry and Remote Sensing, 2012, 69: 167.
[3] Xu S, Zhao Y, Wang M, et al. Catena, 2017, 157: 12 .
[4] Tang G, Hu J, Yan H, et al. Optik, 2016, 127(3): 1405.
[5] Song X Z, Huang Y, Tian K D, et al. Optik, 2020, 203: 164019.
[6] Liu D, Sun D W, Zeng X A. Food & Bioprocess Technology, 2014, 7: 307.
[7] Yun Y H, Wang W T, Deng B C, et al. Analytica Chimica Acta, 2015, 862: 14.
[8] Deng B C, Yun Y H, Cao D S, et al. Analytica Chimica Acta, 2016, 908: 63.
[9] Song X, Huang Y, Yan H, et al. Analytica Chimica Acta, 2016, 948: 19.
[10] WANG Zhong-yi, HOU Rui-feng, HUANG Lan, et al(王忠义, 侯瑞锋, 黄 岚, 等). Transactions of the Chinese Society of Agricultural Engineering(农业工程学报), 2007, 23(5): 1.
[11] LI Xiao-qin(李晓勤). Journal of Agricultural Mechanization Research(农机化研究), 2009, 31(7): 104.
[12] YANG Sai, ZHU Qi-bing, HUANG Min(杨 赛, 朱启兵, 黄 敏). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2017, 37(3): 990.
[13] Wang Lu, Pu H, Sun D W, et al. Food Analytical Methods, 2015, 8(6): 1535.
[14] Adam E, Deng H, Odindi J, et al. Journal of Spectroscopy, 2017, 2017: 1.
[15] Wang Z, Chen J, Fan Y, et al. Computers and Electronics in Agriculture, 2020, 169: 105160.
[16] Gao J, Nuyttens D, Lootens P, et al. Biosystems Engineering, 2018, 170: 39.
[17] HUAN Ke-wei, LIU Xiao-xi, WANG Xin, et al(宦克为, 刘小溪, 王 欣, 等). Journal of Changchun University of Science and Technology·Natural Science Edition(长春理工大学学报·自然科学版), 2014, 37(5): 146.
[18] Liang L, Di L, Huang T, et al. Remote Sensing, 2018, 10：1940.
[19] Su W H, Sun D W. Institute of Food Technologists, 2018, 17: 220.
[20] Liu F, Jin Z L, Naeem M S, et al. Food and Bioprocess Technology, 2011, 4: 1314.
[21] Zhang Chu, Kong W, Liu F, et al. Heliyon, 2015, 2(1)：e00064.
[22] LUO Wei, DU Yan-zhe, ZHANG Hai-liang(罗 微, 杜焱喆, 章海亮). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2016, 36(11): 3536.
[23] Brito A L B, Araújo D A, Pontes M J C, et al. Analytical Methods, 2015, 7(5): 1890.
[24] Su W H, Bakalis S, Sun D W. Biosystems Engineering, 2019, 180: 70 .
[25] Dacal-Nieto A, Formella A, Carrión P, et al. Lecture Notes in Computer Science, 2011, 6855: 180.
[26] Cen H, Lu R, Zhu Q, et al. Postharvest Biology and Technology, 2016, 111: 352.
[27] Pedro A M K, Ferreira M M C. Analytical Chemistry, 2005, 77(8): 2505.
[28] Wu D, Chen X, Zhu X, et al. Analytical Methods, 2011, 3: 1790.
[29] Xiao K, Liu Q, Wang L, et al. LWT—Food Science and Technology, 2020, 122: 109030.
[30] Mollazade K. Food Analytical Methods, 2017, 10: 2743.
[31] WANG Zhuan-wei, CHI Qian, GUO Wen-chuan, et al(王转卫, 迟 茜, 郭文川, 等). Transactions of the Chinese Society for Agricultural Machinery(农业机械学报), 2018, 49(5): 348.
[32] Che W, Sun L, Zhang Q, et al. Computers and Electronics in Agriculture, 2018, 146: 12.
[33] Dong J, Guo W. Food Analytical Methods, 2015, 8(10): 2635.
[34] Li J, Tian X, Huang W, et al. Food Analytical Methods, 2016, 9(11): 3087.
[35] Li J, Zhang H, Zhan B, et al. Infrared Physics & Technology, 2020, 104: 103154.
[36] Zhang D, Xu L, Liang D, et al. Food Analytical Methods, 2018, 11: 2336.
[37] Guo W, Gu J, Liu D, et al. Computers and Electronics in Agriculture, 2016, 123: 297.
[38] Zhang B, Li J, Fan S, et al. Computers and Electronics in Agriculture, 2015, 114: 14.
[39] Yu K Q, Zhao Y R, Liu Z Y, et al. Food & Bioprocess Technology, 2014, 7: 3077.
[40] Huang L, Zhou Y, Meng L, et al. Food Chemistry, 2017, 224: 1.
[41] Zhao Y R, Yu K Q, He Y. Journal of Analytical Methods in Chemistry, 2015, 2015(2): 343782.
[42] Abdel-Rahman EM, Ahmed FB, Ismail R. International Journal of Remote Sensing, 2013, 34(2): 712.
[43] Zhang D, Xu L, Wang Q, et al. Food Analytical Methods, 2019, 12: 136.
[44] Hu R, Zhang L, Yu Z, et al. Infrared Physics and Technology, 2019, 109: 102999.
[45] Mithun B S, Sujit S, Karan B, et al. Proc. SPIE, 2018, 10665: 106650T.
[46] BAO Yi-dan, CHEN Na, HE Yong, et al(鲍一丹, 陈 纳, 何 勇, 等). Optics and Precision Engineering(光学精密工程), 2015, 23(2): 349.
[47] Zheng K, Li Q, Wang J, et al. Chemometrics and Intelligent Laboratory Systems, 2012, 112: 48.
[48] MAI Shu-kui, YANG Yang, ZHAO Xiao-bo, et al(买书魁, 杨 洋, 赵小波, 等). Food Science and Technology(食品科技), 2019, 44(2): 301.
[49] CHEN Bin, LU Bing, LU Dao-li(陈 斌, 卢 丙, 陆道礼). Modern Food Science and Technology(现代食品科技), 2015, 31(8): 286.
[50] Sun J, Zhou X, Hu Y, et al. Computers and Electronics in Agriculture, 2019, 160: 153.
[51] Masemola C, Cho M A. International Journal of Remote Sensing, 2019, 40(17-18): 6841.
[52] GENG Xiang, GUI Jia-xiang, SUN Tong, et al(耿 响, 桂家祥, 孙 通, 等). Shanghai Textile Science and Technology(上海纺织科技), 2015, 43(8): 80.
[53] Yuan T, Zhao Y, Zhang J, et al. Scientific Reports, 2018, 8: 89.
[54] Xie C, Xu N, Shao Y, et al. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 2015, 149: 971.
[55] Kamruzzaman M, ElMasry G, Sun D W, et al. Food Chemistry, 2013, 141(1): 389.
[56] Xu J L, Riccioli C, Sun D W. Journal of Food Engineering, 2016, 196: 170.
[57] MA Shi-bang, PENG Yan-kun, XU Yang, et al(马世榜, 彭彦昆, 徐 杨, 等). Journal of Jiangsu University·Natural Science Edition(江苏大学学报·自然科学版), 2013, 34(1): 44.
[58] Pu H, Sun DW, Ma J, et al. Journal of Food Engineering, 2014, 143(Dec.): 44.
[59] WANG Wen-xiu, PENG Yan-kun, ZHENG Xiao-chun, et al(王文秀, 彭彦昆, 郑晓春, 等). Transactions of the Chinese Society for Agricultural Machinery(农业机械学报), 2017, 48(9): 303.
[60] Jia B, Yoon SC, Zhuang H, et al. Journal of Food Engineering, 2017, 208(Sep.): 57.
[61] CUI Teng-fei, YANG Xiao-yu, DING Jia-xing, et al(崔腾飞, 杨晓玉, 丁佳兴, 等). Science and Technology of Food Industry(食品工业科技), 2018, 39(5): 13.
[62] Wu D, Shi H, He Y, et al. Journal of Food Engineering, 2013, 119(3): 680.
[63] He H J, Sun D W. LWT—Food Science and Technology, 2015, 62: 11.
[64] Cheng J H, Sun D W. LWT—Food Science and Technology, 2015, 62(2): 1060.
[65] Li Y, Guo Y, Liu C, et al. Food Analytical Methods, 2016, 10(6): 1.
[66] Wu D, Nie P, He Y, et al. Food & Bioprocess Technology, 2012, 5(4): 1402.
[67] WEN Zhen-cai, SUN Tong, XU Peng, et al(温珍才, 孙 通, 许 朋, 等). Journal of Jiangsu University·Natural Science Edition(江苏大学学报·自然科学版), 2015, 36(6): 673.
[68] Jiang H, Zhang H, Chen Q, et al. Molecular and Biomolecular Spectroscopy, 2015, 149: 1.
[69] XIONG Ya-ting, LI Zong-peng, WANG Jian, et al(熊雅婷, 李宗朋, 王 健, 等). Food and Fermentation Industries(食品与发酵工业), 2015, 41(3): 185.
[70] Zhao X, Wang W, Ni X, et al. Applied Sciences, 2018, 8(7): 1076.
[71] Wang J, Wang J, Zhang X, et al. Journal of Food Quality, 2018, 2018: 3136516.
