Literature DB >> 27130097

The potential of spectral and hyperspectral-imaging techniques for bacterial detection in food: A case study on lactic acid bacteria.

Giorgia Foca1, Carlotta Ferrari1, Alessandro Ulrici1, Giorgia Sciutto2, Silvia Prati2, Stefano Morandi3, Milena Brasca3, Paola Lavermicocca4, Silvia Lanteri5, Paolo Oliveri6.   

Abstract

Official methods for the detection of bacteria are based on culture techniques. These methods have limitations such as time consumption, cost, detection limits and the impossibility to analyse a large number of samples. For these reasons, the development of rapid, low-cost and non-destructive analytical methods is a task of growing interest. In the present study, the capability of spectral and hyperspectral techniques to detect bacterial surface contamination was investigated preliminarily on gel cultures, and subsequently on sliced cooked ham. In more detail, two species of lactic acid bacteria (LAB) were considered, namely Lactobacillus curvatus and Lactobacillus sakei, both of which are responsible for common alterations in sliced cooked ham. Three techniques were investigated, with different equipment, respectively: a macroscopic hyperspectral scanner operating in the NIR (10,470-5880cm(-1)) region, a FT-NIR spectrophotometer equipped with a transmission arm as the sampling tool, working in the 12,500-5800cm(-1) region, and a FT-MIR microscopy operating in the 4000-675cm(-1) region. Multivariate exploratory data analysis, in particular principal component analysis (PCA), was applied in order to extract useful information from original data and from hyperspectrograms. The results obtained demonstrate that the spectroscopic and imaging techniques investigated can represent an effective and sensitive tool to detect surface bacterial contamination in samples and, in particular, to recognise species to which bacteria belong.
Copyright © 2016 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Cooked ham; FT-IR microscopy; FT-NIR spectroscopy; Hyperspectral imaging; Lactic acid bacteria (LAB); Principal component analysis (PCA)

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Year:  2016        PMID: 27130097     DOI: 10.1016/j.talanta.2016.02.059

Source DB:  PubMed          Journal:  Talanta        ISSN: 0039-9140            Impact factor:   6.057


  3 in total

1.  Assessing the capability of Fourier transform infrared spectroscopy in tandem with chemometric analysis for predicting poultry meat spoilage.

Authors:  Ubaid Ur Rahman; Amna Sahar; Imran Pasha; Sajjad Ur Rahman; Anum Ishaq
Journal:  PeerJ       Date:  2018-08-06       Impact factor: 2.984

2.  Principal component analysis of hyperspectral data for early detection of mould in cheeselets.

Authors:  Jessica Farrugia; Sholeem Griffin; Vasilis P Valdramidis; Kenneth Camilleri; Owen Falzon
Journal:  Curr Res Food Sci       Date:  2021-01-11

3.  Detecting Bacterial Biofilms Using Fluorescence Hyperspectral Imaging and Various Discriminant Analyses.

Authors:  Ahyeong Lee; Saetbyeol Park; Jinyoung Yoo; Jungsook Kang; Jongguk Lim; Youngwook Seo; Balgeum Kim; Giyoung Kim
Journal:  Sensors (Basel)       Date:  2021-03-22       Impact factor: 3.576

  3 in total

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