Rapid Differentiation and Identification of Foodborne Pathogenic Bacteria and Fungi by FT-IR Spectroscopy

GONG Fang; LIU Xiaojing; KANG Qiuyan; WANG Ying; LI Zhaojie

doi:10.13386/j.issn1002-0306.2021100062

Volume 43 Issue 13

Jun. 2022

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Science and Technology of Food Industry > 2022 > 43(13): 235-241. > DOI: 10.13386/j.issn1002-0306.2021100062

GONG Fang, LIU Xiaojing, KANG Qiuyan, et al. Rapid Differentiation and Identification of Foodborne Pathogenic Bacteria and Fungi by FT-IR Spectroscopy[J]. Science and Technology of Food Industry, 2022, 43(13): 235−241. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2021100062.

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Rapid Differentiation and Identification of Foodborne Pathogenic Bacteria and Fungi by FT-IR Spectroscopy

1.
The CPC Qingdao West Coast New Area Working Committee Military and Civilian Integration Office, Qingdao 266000, China
2.
Weihai Professional School, Weihai 264210, China
3.
Collage of Food Science and Engineering of Qingdao Agricultural University, Qingdao 266000, China

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Received Date: October 11, 2021
Available Online: April 30, 2022

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Abstract

Abstract

Objective: In order to satisfy the detection requirements of common foodborne pathogenic microorganisms in food safety detection, Fourier tranform infrared spectroscopy (FT-IR) was used to establish a method for rapid differentiation and identification method for common foodborne pathogenic bacteria and fungi. Methods: FT-IR fingerprints absorption spectra of 977.9~1805.3 cm⁻¹ for 13 species of foodborne pathogenic bacteria, 900~1800 cm⁻¹ and 2800~3700 cm⁻¹ for 12 species of fungi were collected. Two chemometric methods (PCA and HCA) were used for the data analysis. The veracity of the method to classify the suspected species was proved by labeling verification experiment. Results: The standard spectral derivatives library of all species were created. Two discriminant models were created, and the results showed that the HCA cluster analysis model was proved to be suitable to accurately cluster 13 pathogenic bacteria and 12 fungi at the interspecific level. The suspected strains in the labeling verification experiment were accurately clustered to the corresponding species. Conclusion: The FT-IR technique combined with HCA clustering analysis method were proved to be a feasible method to provide rapid identification of common foodborne pathogenic bacteria and fungi species.

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References

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