|
|
|
|
|
|
Integrated Detection of Foodborne Pathogens by In-Situ Infrared Spectroscopy Based on ZnSe Film Transmission Method |
LIU Yan-yan1, TAO Ning-ping1, 2, 3, WANG Xi-chang1, 2, 3, LU Ying1, 2, 3*,XU Chang-hua1, 2, 3* |
1. College of Food Sciences & Technology, Shanghai Ocean University, Shanghai 201306, China
2. Shanghai Engineering Research Center of Aquatic-Product Processing & Preservation, Shanghai 201306, China
3. Ministry of Agriculture, National R & D Branch Center for Freshwater Aquatic Products Processing Technology (Shanghai), Shanghai 201306, China |
|
|
Abstract Foodborne pathogens are predominant factors affecting human health. Due to the species diversity of foodborne pathogens and the complicity and time-consuming of traditional techniques, a rapid and accurate foodborne pathogen detecting technology is urgently needed. For the traditional infrared spectroscopic techniques, samples need to be lyophilized (about 2 days) before being pressed into a KBr pellet. Therefore, it is not conducive to fast and high-throughput detection. In this study, a developed ZnSe film transmission method was employed to drop samples on the ZnSe window directly, and an in-situ detection was carried out after low-temperature drying without long lyophilization process. The whole detection process was completed within 50 min. Meanwhile, only small sample volume (10 μL) was needed and the adverse effects of KBr pressed pellet method (e. g., size of abrasive particles, thickness error, easy fragmentation and moisture absorption) were avoided. In the meantime, by comparing the four foodborne pathogens (Escherichia coli DH5α, Salmonella enteritidis CMCC 50041, Vibrio cholerae SH04, Staphylococcus aureus SH10) with the conventional KBr pressed pellet method, the number of peaks in second derivative infrared (SD-IR) spectroscopy obtained by the ZnSe film transmission method (1 500~900 cm-1) significantly increased (ZnSe film transmission method: 81, KBr pressed pellet method: 58) under the same peak threshold detection (transmittance >0.05%) and broad single peaks or inconspicuous double peaks in the KBr pressed pellet method could be split into two or more peaks (Escherichia coli DH5α: 1 441, 1 391, 1 219 cm-1 etc; Salmonella enteritidis CMCC 50041: 1 490, 1 219, 1 025 cm-1; Vibrio cholerae SH04: 1 441, 1 219 cm-1; Staphylococcus aureus SH10: 1 491, 1 397, 1 219 cm-1) with higher peak intensity (1 119, 1 085, 915 cm-1 etc.). Therefore, it had been demonstrated that spectral resolution and the signal to noise ratio in the ZnSe film transmission method were significantly improved. The in-situ infrared spectroscopy based on ZnSe film transmission method has great potential for the rapid and high-throughput detection of common foodborne pathogens in food.
|
Received: 2020-01-13
Accepted: 2020-04-15
|
|
Corresponding Authors:
LU Ying,XU Chang-hua
E-mail: y-lu@shou.edu.cn;chxu@shou.edu.cn
|
|
[1] CHEN Xiu-qin, HUANG Mei-qing, ZHENG Min, et al(陈秀琴,黄梅清,郑 敏,等). Fujian Journal of Agricultural Sciences(福建农业学报), 2018, 33(4): 43.
[2] Zhao X H, Li M, Xu Z B. Front Microbiol, 2018, 9: 1236.
[3] Hameed S, Xie L J, Ying Y B. Trends Food Science & Technology, 2018, 81: 62.
[4] ZHANG Yu, LI Jie-qing, LI Tao, et al(张 钰,李杰庆,李 涛,等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2019, 39(2): 449.
[5] YANG Li-jun, WANG Jing, LI Zhao-jie, et al(杨丽君,王 静,李兆杰,等). Food Science(食品科学), 2013, 34(8): 190.
[6] WANG Jing, YANG Li-jun, LI Zhao-jie, et al(王 静,杨丽君,李兆杰,等). Microbiology China(微生物学通报), 2012, 39(2): 1846.
[7] Carlos C, Maretto D A, Poppi R J, et al. Microchemical Journal, 2011, 99(1): 16.
[8] SUN Su-qin(孙素琴). ACT 009 Infrared Spectroscopy Analysis Technology(ATC 009 红外光谱分析技术). Beijing: China Quality Inspection Press(北京: 中国质检出版社), 2013. 93.
[9] Johler S, Stephan R, Althaus D, et al. Syst. Appl. Microbiol., 2016, 39(3): 190.
[10] Salman A, Shufan E, Sharaha U, et al. Vib. Spectrosc., 2019, 100: 7.
[11] Hu X Z, Liu S Q, Li X H, et al. Sci. Rep., 2019, 9(1): 8255.
[12] Novais A, Freitas A R, Rodrigues C, et al. Eur. J. Clin. Microbiol. Infect. Dis., 2019, 38(3): 432.
[13] Lu X N, Hamzah M, Al-Qadiri, et al. Food and Bioprocess Technology, 2011, 4(6): 922. |
[1] |
LI Shu-jie1, LIU Jie1, DENG Zi-ang1, OU Quan-hong1, SHI You-ming2, LIU Gang1*. Study of Germinated Rice Seeds by FTIR Spectroscopy Combined With Curve Fitting[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(06): 1832-1840. |
[2] |
ZHANG Yan-ru1, 2, SHAO Peng-shuai1*. Study on the Effects of Planting Years of Vegetable Greenhouse on the
Cucumber Qualties Using Mid-IR Spectroscopoy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(06): 1816-1821. |
[3] |
WANG Xue-pei1, 2, ZHANG Lu-wei1, 2, BAI Xue-bing3, MO Xian-bin1, ZHANG Xiao-shuan1, 2*. Infrared Spectral Characterization of Ultraviolet Ozone Treatment on Substrate Surface for Flexible Electronics[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(06): 1867-1873. |
[4] |
SHI Wen-qiang1, XU Xiu-ying1*, ZHANG Wei1, ZHANG Ping2, SUN Hai-tian1, 3, HU Jun1. Prediction Model of Soil Moisture Content in Northern Cold Region Based on Near-Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(06): 1704-1710. |
[5] |
WANG Yue1, 3, 4, CHEN Nan1, 2, 3, 4, WANG Bo-yu1, 5, LIU Tao1, 3, 4*, XIA Yang1, 2, 3, 4*. Fourier Transform Near-Infrared Spectral System Based on Laser-Driven Plasma Light Source[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(06): 1666-1673. |
[6] |
FENG Rui-jie1, CHEN Zheng-guang1, 2*, YI Shu-juan3. Identification of Corn Varieties Based on Bayesian Optimization SVM[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(06): 1698-1703. |
[7] |
YU Zhi-rong, HONG Ming-jian*. Near-Infrared Spectral Quantitative Analysis Network Based on Grouped Fully Connection[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(06): 1735-1740. |
[8] |
XIE Yu-yu1, 2, 3, HOU Xue-ling1, CHEN Zhi-hui2, AISA Haji Akber1, 3*. Density Functional Theory Studies on Structure and Spectra of Salidroside Molecule[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(06): 1786-1791. |
[9] |
MENG Fan-jia1, LUO Shi1, WU Yue-feng1, SUN Hong1, LIU Fei2, LI Min-zan1*, HUANG Wei3, LI Mu3. Characteristic Extraction Method and Discriminant Model of Ear Rot of Maize Seed Base on NIR Spectra[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(06): 1716-1720. |
[10] |
PENG Yan-fang1, WANG Jun1, WU Zhi-sheng2*, LIU Xiao-na3, QIAO Yan-jiang2*. NIR Band Assignment of Tanshinone ⅡA and Cryptotanshinone by
2D-COS Technology and Model Application Tanshinone Extract[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(06): 1781-1785. |
[11] |
TIAN Xue1, CHE Qian1, YAN Wei-min1, OU Quan-hong1, SHI You-ming2, LIU Gang1*. Discrimination of Millet Varieties and Producing Areas Based on Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(06): 1841-1847. |
[12] |
HU Bin1, 2, FU Hao1, WANG Wen-bin1, ZHANG Bing1, 2, TANG Fan3*, MA Shan-wei1, 2, LU Qiang1, 2*. Research on Deep Sorting Approach Based on Infrared Spectroscopy for High-Value Utilization of Municipal Solid Waste[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(05): 1353-1360. |
[13] |
YAN Ling-tong, LI Li, SUN He-yang, XU Qing, FENG Song-lin*. Spectrometric Investigation of Structure Hydroxyl in Traditional Ceramics[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(05): 1361-1365. |
[14] |
WANG Li-qi1, YAO Jing1, WANG Rui-ying1, CHEN Ying-shu1, LUO Shu-nian2, WANG Wei-ning2, ZHANG Yan-rong1*. Research on Detection of Soybean Meal Quality by NIR Based on
PLS-GRNN[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(05): 1433-1438. |
[15] |
WANG Yan-ru, TANG Hai-jun*, ZHANG Yao. Study on Infrared Spectral Detection of Fuel Contamination in Mobil Jet Oil II Lubricating Oil[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(05): 1541-1546. |
|
|
|
|