Differentiation of Listeria monocytogenes serotypes using near infrared hyperspectral imaging

被引:1
|
作者
Matenda, Rumbidzai T. [1 ]
Rip, Diane [1 ]
Pierna, Juan A. Fernandez [2 ]
Baeten, Vincent [2 ]
Williams, Paul J. [1 ]
机构
[1] Stellenbosch Univ, Dept Food Sci, Private Bag X1, ZA-7602 Stellenbosch, South Africa
[2] Walloon Agr Res Ctr CRA W, Knowledge & valorizat Agr Prod Dept, Qual & authenticat Prod Unit, Chaussee Namur 24, B-5030 Gembloux, Belgium
关键词
Food pathogens; Listeria monocytogenes serotypes; NIR-HSI; Multivariate data analysis; Partial least discriminant analysis; Principal component analysis; VARIABLE SELECTION; TEICHOIC-ACIDS; SPECTROSCOPY; CLASSIFICATION; COLONIES; STRAINS; STATE;
D O I
10.1016/j.saa.2024.124579
中图分类号
O433 [光谱学];
学科分类号
0703 ; 070302 ;
摘要
Among the severe foodborne illnesses, listeriosis resulting from the pathogen Listeria monocytogenes exhibits one of the highest fatality rates. This study investigated the application of near infrared hyperspectral imaging (NIR-HSI) for the classification of three L. monocytogenes serotypes namely serotype 4b, 1/2a and 1/2c. The bacteria were cultured on Brain Heart Infusion agar, and NIR hyperspectral images were captured in the spectral range 900-2500 nm. Different pre-processing methods were applied to the raw spectra and principal component analysis was used for data exploration. Classification was achieved with partial least squares discriminant analysis (PLS-DA). The PLSDA results revealed classification accuracies exceeding 80 % for all the bacterial serotypes for both training and test set data. Based on validation data, sensitivity values for L. monocytogenes serotype 4b, 1/2a and 1/2c were 0.69, 0.80 and 0.98, respectively when using full wavelength data. The reduced wavelength model had sensitivity values of 0.65, 0.85 and 0.98 for serotype 4b, 1/2a and 1/2c, respectively. The most relevant bands for serotype discrimination were identified to be around 1490 nm and 1580-1690 nm based on both principal component loadings and variable importance in projection scores. The outcomes of this study demonstrate the feasibility of utilizing NIR-HSI for detecting and classifying L. monocytogenes serotypes on growth media.
引用
收藏
页数:12
相关论文
共 50 条
  • [1] Classification of Listeria species using near infrared hyperspectral imaging
    Matenda, Rumbidzai T.
    Rip, Diane
    Williams, Paul J.
    JOURNAL OF NEAR INFRARED SPECTROSCOPY, 2023, 31 (06) : 298 - 308
  • [2] Near infrared hyperspectral imaging for forensic analysis of document forgery
    Silva, Carolina S.
    Pimentel, Maria Fernanda
    Honorato, Ricardo S.
    Pasquini, Celio
    Prats-Montalban, Jose M.
    Ferrer, Alberto
    ANALYST, 2014, 139 (20) : 5176 - 5184
  • [3] Variety Identification of Raisins Using Near-Infrared Hyperspectral Imaging
    Feng, Lei
    Zhu, Susu
    Zhang, Chu
    Bao, Yidan
    Gao, Pan
    He, Yong
    MOLECULES, 2018, 23 (11):
  • [4] Single kernel wheat hardness estimation using near infrared hyperspectral imaging
    Erkinbaev, Chyngyz
    Derksen, Kieran
    Paliwal, Jitendra
    INFRARED PHYSICS & TECHNOLOGY, 2019, 98 : 250 - 255
  • [5] Limitations of single kernel near-infrared hyperspectral. imaging of soft wheat for milling quality
    Delwiche, Stephen R.
    Souza, Edward J.
    Kim, Moon S.
    BIOSYSTEMS ENGINEERING, 2013, 115 (03) : 260 - 273
  • [6] Detection of ochratoxin A contamination in stored wheat using near-infrared hyperspectral imaging
    Senthilkumar, T.
    Jayas, D. S.
    White, N. D. G.
    Fields, P. G.
    Grafenhan, T.
    INFRARED PHYSICS & TECHNOLOGY, 2017, 81 : 228 - 235
  • [7] Chemical Imaging of Heterogeneous Muscle Foods Using Near-Infrared Hyperspectral Imaging in Transmission Mode
    Wold, Jens Petter
    Kermit, Martin
    Segtnan, Vegard Herman
    APPLIED SPECTROSCOPY, 2016, 70 (06) : 953 - 961
  • [8] Nondestructive quality assessment of chili peppers using near-infrared hyperspectral imaging combined with multivariate analysis
    Jiang, Jinlin
    Cen, Haiyan
    Zhang, Chu
    Lyu, Xiaohan
    Weng, Haiyong
    Xu, Haixia
    He, Yong
    POSTHARVEST BIOLOGY AND TECHNOLOGY, 2018, 146 : 147 - 154
  • [9] Differentiation of Maize Ear Rot Pathogens, on Growth Media, with Near Infrared Hyperspectral Imaging
    Williams, Paul J.
    Bezuidenhout, Cenette
    Rose, Lindy J.
    FOOD ANALYTICAL METHODS, 2019, 12 (07) : 1556 - 1570
  • [10] Differentiation of Maize Ear Rot Pathogens, on Growth Media, with Near Infrared Hyperspectral Imaging
    Paul J. Williams
    Cenette Bezuidenhout
    Lindy J. Rose
    Food Analytical Methods, 2019, 12 : 1556 - 1570