Rapid and quantitative detection of Botryosphaeria dothidea by surface-enhanced Raman spectroscopy with size-controlled spherical metal nanoparticles combined with machine learning.

Journal: International journal of food microbiology
Published Date: May 30, 2025

Abstract

Botryosphaeria dothidea infection has become a major factor affecting the quality of postharvest fruits, so detection of B. dothidea infection is very important to control the spread of infection and ensure food safety. In this study, we built a monitoring platform for rapid and quantitative detection of B. dothidea by Surface-enhanced Raman spectroscopy (SERS) with size-controlled spherical metal nanoparticles combined with machine learning, and the platform could also detect a variety of pathogens. With spherical metal nanoparticles as the active substrate, the SERS enhanced effect was significantly size-dependent. 45-60 nm Ag@ICNPs was determined to achieve the maximum SERS signal detection of B. dothidea, and used as the active substrate to construct a SERS platform for rapid and quantitative detection of B. dothidea. This platform had potential practicability in actual sample detection. The platform was used for the detection of Pseudomonas syringae pv. Actinidiae, Pseudomonas aeruginosa, Ralstonia solanacearum and Pseudomonas extremorientalis, and the SERS fingerprint information of these pathogens was successfully captured, and the quantitative analysis ability of these pathogens was also strong. Machine learning analysis was performed on the SERS spectra of pathogens obtained. Based on the differences between the spectral data sets of different pathogens, PCA could effectively distinguish these five pathogens into different groups. The accuracy rates of SVM, Tree, Linear discrimination analysis, Efficient logistic regression, Naive Bayes, K-Nearest Neighbors, Ensemble and Neural network test were 100 %, 96 %, 100 %, 100 %, 100 %, 100 %, 98 % and 100 % respectively, all of which had relatively high accuracy rates. Overall, this study provides a simple, efficient and accurate method for rapid quantitative detection and identification of multiple pathogens, and can be extended to practical agricultural products.

Authors

  • Longhui Luo
    Key Laboratory of Macrocyclic and Supramolecular Chemistry of Guizhou Province, Institute of Applied Chemistry, Guizhou University, Guiyang 550025, China.
  • Wei Tian
    Department of Geriatrics, Beijing Jishuitan Hospital, Capital Medical University, Beijing, China.
  • Qian Liu
    State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China.
  • Xiaoying Yang
    From the Department of Radiology (B.A.-V.), Bloomberg School of Public Health (E.G.), and Department of Medicine, Cardiology and Radiology (J.A.C.L.), Johns Hopkins University, Baltimore, MD; George Washington University, DC (X.Y.); Office of Biostatistics, NHLBI, NIH, Bethesda, MD (C.O.W.); Department of Preventive Medicine, Northwestern University Medical School, Chicago, IL (K.L.); Department of Cardiology, Wake Forest University Health Sciences, Winston-Salem, NC (W.G.H.); Department of Biostatistics, University of Washington, Seattle (R.M.); Department of Radiology, UCLA School of Medicine, Los Angeles, CA (A.S.G.); Division of Epidemiology and Community Health, University of Minnesota, Minneapolis (A.R.F.); Departments of Medicine and Epidemiology, Columbia University, New York, NY (S.S.); and Radiology and Imaging Sciences, NIH Clinical Center, Bethesda, MD (D.A.B.).
  • Tingting Chen
    Department of Hygiene Detection Center, School of Public Health, Southern Medical University (Guangdong Provincial Key Laboratory of Tropical Disease Research), Guangzhou, Guangdong, China.
  • Zhibo Zhao
    Engineering and Technology Research Center of Kiwifruit, Guizhou University, Guiyang 550025, China.
  • Xiufang Yan
    College of Tobacco Science, Guizhou University, Guiyang 550025, China.
  • Chao Kang
    Key Laboratory of Macrocyclic and Supramolecular Chemistry of Guizhou Province, Institute of Applied Chemistry, Guizhou University, Guiyang 550025, China.
  • Dongmei Chen
    School of Automation, Hangzhou Dianzi University, Hangzhou 310018, China.
  • Youhua Long
    Engineering and Technology Research Center of Kiwifruit, Guizhou University, Guiyang 550025, China.

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