Identification of foodborne pathogens within food matrices by IR spectroscopy

Brandily, Marie-Laure; Monbet, Valérie; Bureau, Bruno; Boussard‐Plédel, Catherine; Loréal, Olivier; Adam, Jean-Luc; Sire, Olivier

doi:10.1016/j.snb.2011.07.034

Cited by 35 publications

(14 citation statements)

References 14 publications

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“…Brandily et al. () reported the use of fiber evanescent wave spectroscopy (FEWS) to classify diverse pathogenic organisms in samples of minced meat and sausage meat and in cheese. The technique requires the sample to be brought into contact with a special optical glass fiber, which is linked to an FTIR spectrometer.…”

Section: Chemometrics In Food‐related Disciplinesmentioning

confidence: 99%

Trends in Chemometrics: Food Authentication, Microbiology, and Effects of Processing

Granato

Putnik

Kovačević

et al. 2018

Comp Rev Food Sci Food Safe

350

202

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In the last decade, the use of multivariate statistical techniques developed for analytical chemistry has been adopted widely in food science and technology. Usually, chemometrics is applied when there is a large and complex dataset, in terms of sample numbers, types, and responses. The results are used for authentication of geographical origin, farming systems, or even to trace adulteration of high value-added commodities. In this article, we provide an extensive practical and pragmatic overview on the use of the main chemometrics tools in food science studies, focusing on the effects of process variables on chemical composition and on the authentication of foods based on chemical markers. Pattern recognition methods, such as principal component analysis and cluster analysis, have been used to associate the level of bioactive components with in vitro functional properties, although supervised multivariate statistical methods have been used for authentication purposes. Overall, chemometrics is a useful aid when extensive, multiple, and complex real-life problems need to be addressed in a multifactorial and holistic context. Undoubtedly, chemometrics should be used by governmental bodies and industries that need to monitor the quality of foods, raw materials, and processes when high-dimensional data are available. We have focused on practical examples and listed the pros and cons of the most used chemometric tools to help the user choose the most appropriate statistical approach for analysis of complex and multivariate data.

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Section: Chemometrics In Food‐related Disciplinesmentioning

confidence: 99%

Trends in Chemometrics: Food Authentication, Microbiology, and Effects of Processing

Granato

Putnik

Kovačević

et al. 2018

Comp Rev Food Sci Food Safe

350

202

View full text Add to dashboard Cite

show abstract

“…Chalcogenide fibers have been successfully implemented in fiber evanescent-wave spectroscopy experiments, for the detection of biochemical molecules in various fields of applications including water pollution [50,51], microbiology, and medicine [52,53]. It has been shown also that the infrared signature of gases embedded in the holes of a chalcogenide MOF can be detected.…”

Section: Fibers Designs For Spectroscopymentioning

confidence: 99%

Original designs of chalcogenide microstuctured optical fibers

Trolès

Brilland²,

Caillaud

et al. 2017

Advanced Device Materials

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The combination of the unique optical properties of chalcogenide glasses, in terms of infrared transmission and optical non-linearity, with the original guiding properties of microstructured optical fibers leads to a new category of fibers with promising applications in mid-infrared optics. The recent developments on chalcogenide microstructured optical fibers are exposed and discussed with regards to mid-IR guiding, infrared light transport and delivery, generation of new infrared sources, and infrared spectroscopy.

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“…In presence of meat matrix, strong absorbance peaks had been also been observed in 1200-800 cm −1 and 3,000-2,500 cm corresponds to "Fingerprint region" in bacterial identification. Brandily et al (2011) had also identified regions 3,000-2,800 cm −1 and 1,800-1,000 cm −1 as providing the greatest contribution to the total variance in the FT-IR spectral data acquired for detection of Listeria monocytogenes, Staphylococcus aureus and Salmonella enteritidis in minced meat, sausage meat and raw cheese matrix. Thus the spectral regions 3,000-2,500 cm −1 (I), 1,800-1,200 cm −1 (II), 1,200-800 cm −1 (III), 4,000-575 cm −1 (IV) and combination of 3,000-2,500 cm −1 , 1,800-1,200 cm −1 and 1,200-800 cm −1 (V) were selected for classification and discriminant analysis in dataset 3.…”

Section: Ftir Spectramentioning

confidence: 99%

Detection of poultry meat specific bacteria using FTIR spectroscopy and chemometrics

2014

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FTIR spectra of poultry meat specific bacteria viz. Salmonella enteritidis, Pseudomonas ludensis, Listeria monocytogenes and Escherichia coli were collected and investigated for identification of spectral windows capable of bacterial classification and quantification. Two separate datasets obtained at different times were used in the study to check reproducibility of results. Multivariate data analysis techniques viz. principal component analysis (PCA), partial least-squares discriminant analysis (PLSDA) and soft independent modelling of class analogy (SIMCA) were used in the analysis. Using full cross-validation and separate calibration and prediction datasets, the highest correct classification results for SIMCA and PLSDA were achieved in spectral window (1800-1200 cm-1) for both datasets. The window was also tested then for quantification of different bacteria and it had been observed that PLS models had better R values for classification (R=0.984) than predicting various concentration levels (R=0.939) of all four poultry specific bacteria inoculated in distilled water. The identified spectral window 1800-1200 cm-1 also demonstrated potential for 100% correct classification of chicken salami samples contaminated with S. enteritidis and P. ludensis from control using SIMCA. However, this wavenumber range yielded few misclassifications using PLS-DA approach. Thus FTIR spectroscopy in combination with chemometrics is a powerful technique that can be developed further to differentiate bacteria directly on poultry meat surface.

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Identification of foodborne pathogens within food matrices by IR spectroscopy

Cited by 35 publications

References 14 publications

Trends in Chemometrics: Food Authentication, Microbiology, and Effects of Processing

Trends in Chemometrics: Food Authentication, Microbiology, and Effects of Processing

Original designs of chalcogenide microstuctured optical fibers

Detection of poultry meat specific bacteria using FTIR spectroscopy and chemometrics

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