Fourier Transform Infrared and Raman and Hyperspectral Imaging Techniques for Quality Determinations of Powdery Foods: A Review

Comprehensive Reviews in Food Science and Food Safety - Tập 17 Số 1 - Trang 104-122 - 2018
Wen‐Hao Su1, Da‐Wen Sun1
1Food Refrigeration and Computerized Food Technology (FRCFT), School of Biosystems and Food Engineering, Agriculture & Food Science Centre, Univ. College Dublin (UCD), National Univ. of Ireland, Belfield, Dublin 4, Ireland

Tóm tắt

AbstractFourier transform infrared (FT‐IR) and Raman and hyperspectral imaging (HSI) techniques have emerged as reliable analytical methods for effectively characterizing and quantifying quality attributes of different categories of powdery food products (such as milk powder, tea powder, cocoa powder, coffee powder, soybean flour, wheat flour, and chili powder). In addition to the ability for gaining rapid information about food chemical components (such as moisture, protein, and starch), and classifying food quality into different grades, such techniques have also been implemented to determine trace impurities in pure foods and other properties of particulate foods and ingredients with avoidance of extensive sample preparation. Developments of corresponding quality evaluation systems based on FT‐IR, Raman, and HSI data that measure food quality parameters and ensure product authentication, would bring about technical and economic benefits to the food industry by enhancing consumer confidence in the quality of its products. Accordingly, a comprehensive review of the mushrooming spectroscopy‐based FT‐IR, Raman, and HSI literature is carried out in this article. The spectral data collected, the chemometric methods used, and the main findings of recent research studies on quality assessments of powdered materials are discussed and summarized. Providing a review in such a flourishing research field is relevant as a signpost for future study. The conclusion details the promise of how such noninvasive and powerful analytical techniques can be used for rapid and accurate determinations of powder quality attributes in both academical and industrial settings.

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Tài liệu tham khảo

10.1366/000370206779321454

10.1007/s11947-009-0298-4

10.1002/jrs.2893

10.1016/j.trac.2008.05.010

10.1016/j.foodcont.2012.05.040

10.1021/jf010759

10.1016/j.talanta.2011.04.026

10.1007/s11947-016-1802-2

10.1533/9780857098672

10.1177/0748233712457449

10.1016/j.chemolab.2004.05.007

10.1002/cem.2609

10.1021/jf950305a

10.1007/978-1-4615-2155-6_7

10.1111/j.0013-8703.2004.00197.x

10.1016/j.foodchem.2012.12.036

10.1016/j.foodchem.2017.01.132

10.1016/j.foodres.2013.03.016

10.1205/cherd.05088

10.1016/j.chroma.2004.06.002

10.1016/j.jcs.2014.07.009

10.1016/j.foodchem.2008.08.042

10.1016/j.meatsci.2016.09.017

10.1016/j.lwt.2015.01.021

10.1007/s12393-016-9147-1

10.1016/j.foodchem.2015.11.019

10.1016/j.foodchem.2015.03.111

10.1016/j.jfoodeng.2016.02.004

10.1080/10408398.2015.1004569

10.1016/j.foodcont.2016.10.008

10.1016/j.carbpol.2013.03.001

10.1016/j.jfoodeng.2007.06.027

10.1081/DRT-120023174

10.1081/DRT-120030001

10.1016/j.jfoodeng.2004.01.008

10.1081/DRT-200059136

10.1016/j.foodchem.2016.05.108

10.1016/j.meatsci.2013.04.037

Almeida MR, 2012, Application of FT‐Raman spectroscopy and chemometric analysis for determination of adulteration in milk powder, Anal Lett, 45, 2589, 10.1080/00032719.2012.698672

10.1016/S0260-8774(01)00222-9

Dhakal S, 2016, Evaluation of turmeric powder adulterated with metanil yellow using FT‐Raman and FT‐IR spectroscopy, Foods, 5, 1, 10.3390/foods5020036

10.1016/j.jfoodeng.2004.03.011

10.1016/j.jfoodeng.2013.02.016

10.1016/j.biosystemseng.2015.11.009

10.1016/S0003-2670(00)01107-7

10.1016/j.aca.2007.05.030

10.1016/j.talanta.2013.01.057

10.1016/j.foodchem.2012.11.040

10.1016/j.foodres.2012.09.015

10.1016/j.jfoodeng.2013.09.023

10.1016/j.talanta.2015.05.003

10.1016/j.foodchem.2017.05.011

10.1016/j.talanta.2007.04.054

10.1016/j.tifs.2004.02.011

10.1016/j.jcs.2016.09.006

10.1016/j.talanta.2015.01.012

10.1002/047010631X

10.1056/NEJMoa0809550

10.1007/s11947-015-1477-0

10.1016/j.molstruc.2015.06.081

Hamed M, 1985, Red flour beetle: development and losses in various stored food stuffs, Sarhad J Agric, 1, 97

10.1016/j.foodcont.2014.03.047

10.1016/j.foodres.2014.03.064

10.1080/10408390701537385

10.3390/s16040441

10.1016/j.jfoodeng.2016.02.017

10.1016/j.foodchem.2015.01.029

10.1016/j.fm.2004.01.009

10.1016/j.meatsci.2009.03.010

10.1016/j.tifs.2011.01.008

10.1016/j.foodchem.2015.09.055

10.1016/j.foodchem.2013.02.094

Kamruzzaman M, 2016, Food safety, 127, 10.1007/978-3-319-39253-0_7

10.1556/AAlim.44.2015.1.1

10.1016/j.foodres.2011.06.051

10.1111/j.1365-2621.2004.tb17853.x

Larkin P., 2011, Infrared and Raman spectroscopy: principles and spectral interpretation

10.1016/j.atherosclerosis.2011.12.043

10.1016/j.snb.2013.04.103

10.1007/s11947-015-1654-1

10.1016/j.compag.2016.07.016

10.1016/j.foodchem.2016.09.051

10.1111/1541-4337.12217

10.1016/j.foodchem.2016.09.051

10.1080/00032719.2015.1118482

Li X, 2015, Determination of tea polyphenols content by infrared spectroscopy coupled with iPLS and random frog techniques, Comput Electr Agric, 112, 28, 10.1016/j.compag.2015.01.005

Li X, 2016, Rapid detection of talcum powder in tea using FT‐IR spectroscopy coupled with chemometrics, Scient Rep, 6, 30313, 10.1038/srep30313

Li X‐L, 2015, Nondestructive detection of lead chrome green in tea by Raman spectroscopy, Scient Rep, 5, 15729, 10.1038/srep15729

10.1016/j.jfoodeng.2007.02.057

10.1016/j.talanta.2016.01.035

Liu C, 2016, Non‐destructive detection of dicyandiamide in infant formula powder using multi‐spectral imaging coupled with chemometrics, J Sci Food Agric, 97, 2094, 10.1002/jsfa.8014

10.1016/j.foodchem.2013.05.155

10.1111/j.1750-3841.2011.02503.x

10.1255/jnirs.871

10.1016/j.snb.2015.04.060

10.1021/jf500574m

10.1007/s11947-011-0516-8

10.1016/j.ijrefrig.2014.10.024

Ma J, 2016, Spectral absorption index in hyperspectral image analysis for predicting moisture contents in pork longissimus dorsi muscles, Food Chem, 197, 848, 10.1016/j.foodchem.2015.11.023

10.1016/j.lwt.2017.04.040

10.1007/s11947-014-1381-z

10.1255/jnirs.323

10.1021/jf203945d

10.1006/fstl.1999.0603

10.1016/S0260-8774(00)00110-2

10.1016/j.foodchem.2006.06.038

Mishra P, 2015, Detection and quantification of peanut traces in wheat flour by near infrared hyperspectral imaging spectroscopy using principal‐component analysis, J Near Infrar Spectrosc, 23, 15, 10.1255/jnirs.1141

10.1007/s11947-011-0638-z

10.1016/j.idairyj.2004.12.009

10.1016/j.jfoodeng.2016.06.010

Ning J, 2016, Classification of five Chinese tea categories with different fermentation degrees using visible and near infrared hyperspectral imaging, Intl J Food Propert.

10.1016/j.aca.2007.01.045

Pei L, 2015, Au‐Ag core‐shell nanospheres for surface‐enhanced Raman scattering detection of Sudan I and Sudan II in chili powder, J Nanomater, 16, 1, 10.1155/2015/430925

Petrakis EA, 2016, Assessing saffron (Crocus sativus L.) adulteration with plant‐derived adulterants by diffuse reflectance infrared Fourier transform spectroscopy coupled with chemometrics, Talanta, 162, 558, 10.1016/j.talanta.2016.10.072

10.1039/C5FD00199D

10.1007/s00216-006-0851-1

10.1016/j.tifs.2015.05.006

10.1016/j.foodchem.2015.04.120

10.1016/j.ifset.2015.11.003

10.1016/j.biosystemseng.2017.01.006

10.1016/j.meatsci.2014.09.001

10.1016/j.foodchem.2012.10.115

10.1007/s11947-015-1605-x

10.1007/s11694-014-9172-9

Qin J, 2017, Detection and quantification of adulterants in milk powder using a high‐throughput Raman chemical imaging technique, Food Addit Contamin: Part A, 34, 152, 10.1080/19440049.2016.1263880

Qin J, 2017, Detecting benzoyl peroxide in wheat flour by line‐scan macro‐scale Raman chemical imaging, Sens Agric Food Qual Saf IX, 10217, 07

10.1016/j.lwt.2016.09.024

Ramalingam C, 2013, Detection and biochemical characterization of microorganisms in milk and cocoa powder samples by FTIR and subsequent production of bacteriocin from lactobacillus, Intl J Drug Dev Res, 5, 310

10.1007/s11947-016-1817-8

10.1016/j.talanta.2013.06.004

10.1021/jf0101410

10.1021/jf0478657

10.1002/9780470586242

Shen G, 2016, A feasibility study of non‐targeted adulterant screening based on NIRM spectral library of soybean meal to guarantee quality: the example of non‐protein nitrogen, Food Chem, 210, 35, 10.1016/j.foodchem.2016.04.101

10.1016/j.lwt.2008.12.013

10.1007/s11947-008-0163-x

10.1016/j.vibspec.2013.04.005

10.1211/jpp.59.2.0005

10.1007/s11947-013-1120-x

Su W‐H, 2017, Fourier transform mid‐infrared‐attenuated total reflectance (FTMIR‐ATR) microspectroscopy for determining textural property of microwave baked tuber, J Food Eng, 218, 1, 10.1016/j.jfoodeng.2017.08.016

10.1080/10408398.2015.1082966

10.1016/j.talanta.2016.04.041

10.1016/j.compag.2016.04.034

10.1016/j.compag.2016.07.007

10.1016/j.compag.2016.09.015

10.1016/j.jfoodeng.2016.12.014

10.1016/j.compag.2017.06.013

10.1016/j.compag.2017.04.017

10.1016/S0196-8904(96)00063-5

10.1016/S0022-474X(99)00009-0

Sun D‐W., 2016, Computer vision technology for food quality evaluation

10.1016/S0140-7007(99)00011-0

10.1016/S0260-8774(02)00276-5

10.1007/s11947-014-1397-4

10.1016/j.jfoodeng.2005.06.023

10.1155/2016/9256102

10.1007/s11947-013-1079-7

10.1016/S0260-8774(99)00087-4

10.1007/s11746-009-1503-3

10.1016/j.foodcont.2008.11.003

Verdú S, 2016, Spectral study of heat treatment process of wheat flour by VIS/SW‐NIR image system, J Cereal Sci, 71, 99, 10.1016/j.jcs.2016.08.008

10.1016/j.foodcont.2015.11.002

10.1016/j.jfoodeng.2016.07.017

Vermeulen P, 2017, Online detection and quantification of particles of ergot bodies in cereal flour using near infrared hyperspectral imaging, Food Addit Contamin: Part A, 34, 1312, 10.1080/19440049.2017.1336798

10.1016/j.aca.2007.08.039

10.1007/s002170000230

10.1016/S0167-4501(98)80014-9

10.1016/S0260-8774(03)00095-5

10.1080/10408398.2015.1115954

10.1016/j.eswa.2014.08.018

10.1111/j.1750-3841.2009.01173.x

Wang N, 2014, Quantitative analysis of adulterations in oat flour by FT‐NIR spectroscopy, incomplete unbalanced randomized block design, and partial least squares, J Anal Methods Chem, 2014, 393596, 10.1155/2014/393596

10.1007/s11947-007-0033-y

10.1007/s11947-010-0492-4

10.1016/j.ifset.2013.04.016

10.1016/j.talanta.2013.05.030

10.1016/j.talanta.2015.02.027

10.1007/s11947-016-1766-2

10.1016/j.foodchem.2015.01.116

10.1016/j.jfoodeng.2014.02.004

10.1080/10408398.2013.834875

10.1016/j.jfoodeng.2016.06.007

10.1016/j.jfoodeng.2016.10.021

10.1016/j.ijrefrig.2016.10.014

Yang Z, 2016, Detection of melamine in soybean meal using near‐infrared microscopy imaging with pure component spectra as the evaluation criteria, J Spectrosc, 2016, 5868170, 10.1155/2016/5868170

10.1039/C4AY00965G

10.1016/j.jfoodeng.2016.07.015

10.1080/05704928.2011.593216

10.1016/j.tifs.2017.01.012

10.1039/C7RA02520C

Zhao J, 2015, Rapid detection of benzoyl peroxide in wheat flour by using Raman scattering spectroscopy, Sens Agric Food Qual Saf VII, 9488, 05

10.1016/j.talanta.2013.03.075

10.1016/j.jfca.2016.06.005

10.1016/j.compag.2015.03.015

10.1111/1541-4337.12062

10.1016/j.tifs.2004.09.002

Zhou R, 2017, Grading of green tea and quantitative determination of beta‐carotene and lutein based on hyperspectral imaging, Am Soc Agric Biol Eng, 13031, 06

10.1177/0967033517704081

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Comprehensive Reviews in Food Science and Food Safety

Tập 17 Số 1

104-122

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