Deep (offset) non-invasive Raman spectroscopy for the evaluation of food and beverages-A review

被引:22
作者
Arroyo-Cerezo, Alejandra [1 ]
Jimenez-Carvelo, Ana M. [1 ]
Gonzalez-Casado, Antonio [1 ]
Koidis, Anastasios [2 ]
Cuadros-Rodriguez, Luis [1 ]
机构
[1] Univ Granada, Dept Analyt Chem, C Fuentenueva S-N, E-18071 Granada, Spain
[2] Queens Univ, Inst Global Food Secur, 18-30 Malone Rd, Belfast BT9 5BN, Antrim, North Ireland
关键词
Spatially offset Raman spectroscopy (SORS); Analysis through packaging; Food characterization; Quality control; Multivariate analysis; AUTHENTICATION; TOMATOES; QUALITY; SAFETY;
D O I
10.1016/j.lwt.2021.111822
中图分类号
TS2 [食品工业];
学科分类号
0832 ;
摘要
Spatially offset Raman spectroscopy (SORS) technique was developed to overcome the problem with qualitative or quantitative analysis of materials through packaging. To achieve that, the instrument is configured so that the Raman scattered signal is collected at a spatially offset at some distance from the excitation laser spot on the sample. In this way, the Raman spectra are recovered from the sample's sub-surface, providing a characteristic fingerprint of the product that requires a suitable multivariate data analysis to obtain the desired information. Despite the great potential for the technique, SORS applications in the food and agriculture sector are scarce in the literature. This paper is a review of all the studies reported to date where SORS is applied to analyse different foods and beverages. All of them have presented results that demonstrate the ability of SORS to carry out rapid and non-invasive through-the-container measurements and to ensure quality control and authentication of raw materials and end products. The reviewed studies include food analysis of animal and plant origin, through the surface of the food itself, as well as through the original packaging. Using the Raman spectra data, chemometric analyses were used to group, e.g., different varieties or species of the same type of potatoes, cuts of meat or alcoholic beverages, as well as to group them according to differences such as the state of ripeness of tomatoes, or the composition of fish, meat and potatoes, among others. There is a promising future for SORS in foodstuff analysis, so the technique must continue to be studied and evolve in order to obtain the appropriate methodology and instrumentation. In addition, the development of SORS portable instruments greatly facilitates the measurement operation and opens new opportunities for applications in the field or in industrial food processing premises.
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页数:8
相关论文
共 49 条
  • [1] A Novel Approach for Subsurface Through-Skin Analysis of Salmon Using Spatially Offset Raman Spectroscopy (SORS)
    Afseth, Nils Kristian
    Bloomfield, Matthew
    Wold, Jens Petter
    Matousek, Pavel
    [J]. APPLIED SPECTROSCOPY, 2014, 68 (02) : 255 - 262
  • [2] Quantitation of active pharmaceutical ingredient through the packaging using Raman handheld spectrophotometers: A comparison study
    Alaoui Mansouri, M.
    Sacre, P. -Y.
    Coic, L.
    De Bleye, C.
    Dumont, E.
    Bouklouze, A.
    Hubert, Ph
    Marini, R. D.
    Ziemons, E.
    [J]. TALANTA, 2020, 207 (207)
  • [3] Raman optical activity comes of age
    Barron, LD
    Hecht, L
    McColl, IH
    Blanch, EW
    [J]. MOLECULAR PHYSICS, 2004, 102 (08) : 731 - 744
  • [4] Non-invasive identification of incoming raw pharmaceutical materials using Spatially Offset Raman Spectroscopy
    Bloomfield, Matthew
    Andrews, Darren
    Loeffen, Paul
    Tombling, Craig
    York, Tim
    Matousek, Pavel
    [J]. JOURNAL OF PHARMACEUTICAL AND BIOMEDICAL ANALYSIS, 2013, 76 : 65 - 69
  • [5] Buckley K., 2012, INFRARED RAMAN SPECT, P351, DOI [DOI 10.1002/9781119962328.CH6B.CH.6.2, 10.1002/9781119962328.ch6b.ch.6.2]
  • [6] Non-invasive analysis of turbid samples using deep Raman spectroscopy
    Buckley, Kevin
    Matousek, Pavel
    [J]. ANALYST, 2011, 136 (15) : 3039 - 3050
  • [7] Bumbrah G.S., 2015, Egypt. J. Foren. Sci, DOI DOI 10.1016/J.EJFS.2015.06.001
  • [8] A 1064 nm Dispersive Raman Spectral Imaging System for Food Safety and Quality Evaluation
    Chao, Kuanglin
    Dhakal, Sagar
    Qin, Jianwei
    Kim, Moon
    Peng, Yankun
    [J]. APPLIED SCIENCES-BASEL, 2018, 8 (03):
  • [9] Multivariate Curve Resolution (MCR). Solving the mixture analysis problem
    de Juan, Anna
    Jaumot, Joaquim
    Tauler, Rom A.
    [J]. ANALYTICAL METHODS, 2014, 6 (14) : 4964 - 4976
  • [10] Random forest as one-class classifier and infrared spectroscopy for food adulteration detection
    de Santana, Felipe Bachion
    Neto, Waldomiro Borges
    Poppi, Ronei J.
    [J]. FOOD CHEMISTRY, 2019, 293 : 323 - 332