Literature DB >> 28397254

Modern analytical methods for the detection of food fraud and adulteration by food category.

Eunyoung Hong1, Sang Yoo Lee1, Jae Yun Jeong2,3, Jung Min Park2,3, Byung Hee Kim4, Kisung Kwon5, Hyang Sook Chun1.   

Abstract

This review provides current information on the analytical methods used to identify food adulteration in the six most adulterated food categories: animal origin and seafood, oils and fats, beverages, spices and sweet foods (e.g. honey), grain-based food, and others (organic food and dietary supplements). The analytical techniques (both conventional and emerging) used to identify adulteration in these six food categories involve sensory, physicochemical, DNA-based, chromatographic and spectroscopic methods, and have been combined with chemometrics, making these techniques more convenient and effective for the analysis of a broad variety of food products. Despite recent advances, the need remains for suitably sensitive and widely applicable methodologies that encompass all the various aspects of food adulteration.
© 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

Keywords:  adulteration; analytical methods; food authentication; food categories; fraud; geographical origin

Mesh:

Year:  2017        PMID: 28397254     DOI: 10.1002/jsfa.8364

Source DB:  PubMed          Journal:  J Sci Food Agric        ISSN: 0022-5142            Impact factor:   3.638


  20 in total

1.  Identification of adulteration in botanical samples with untargeted metabolomics.

Authors:  E Diane Wallace; Daniel A Todd; James M Harnly; Nadja B Cech; Joshua J Kellogg
Journal:  Anal Bioanal Chem       Date:  2020-04-29       Impact factor: 4.142

2.  Development of a screening method to rapidly discriminate extravirgin olive oil from other edible vegetable oil by means of direct sample analysis with high resolution mass spectrometry.

Authors:  Giovanna Esposito; Simona Sciuto; Cinzia Cocco; Giuseppe Ru; Pier Luigi Acutis
Journal:  J Food Sci Technol       Date:  2021-03-18       Impact factor: 2.701

3.  An Integrative Glycomic Approach for Quantitative Meat Species Profiling.

Authors:  Sean Chia; Gavin Teo; Shi Jie Tay; Larry Sai Weng Loo; Corrine Wan; Lyn Chiin Sim; Hanry Yu; Ian Walsh; Kuin Tian Pang
Journal:  Foods       Date:  2022-06-30

4.  Distinguishing Korean and Chinese red pepper powder using inductively coupled plasma and X-ray fluorescence-based analysis.

Authors:  Jung Eun Lee; Eunji Choi; Cheol Seong Jang; Hyang Sook Chun; Sangdoo Ahn; Byung Hee Kim
Journal:  Food Sci Biotechnol       Date:  2021-09-18       Impact factor: 3.231

5.  The Untargeted Capability of NMR Helps Recognizing Nefarious Adulteration in Natural Products.

Authors:  Seon Beom Kim; Jonathan Bisson; J Brent Friesen; Luca Bucchini; Stefan Gafner; David C Lankin; Shao-Nong Chen; Guido F Pauli; James B McAlpine
Journal:  J Nat Prod       Date:  2021-03-12       Impact factor: 4.050

6.  Development and application of DNA markers to detect adulteration with Scopolia japonica in the medicinal herb Atractylodes lancea.

Authors:  Su Hong Oh; Yea Dam Kim; Cheol Seong Jang
Journal:  Food Sci Biotechnol       Date:  2021-11-26       Impact factor: 2.391

7.  The potential of aerosol eDNA sampling for the characterisation of commercial seed lots.

Authors:  Lorretha C Emenyeonu; Adam E Croxford; Mike J Wilkinson
Journal:  PLoS One       Date:  2018-08-01       Impact factor: 3.240

8.  Development of a fast and simple method to identify pure Arabica coffee and blended coffee by Infrared Spectroscopy.

Authors:  Alexandre Cestari
Journal:  J Food Sci Technol       Date:  2021-06-16       Impact factor: 3.117

9.  Establishment of a PCR Assay for the Detection and Discrimination of Authentic Cordyceps and Adulterant Species in Food and Herbal Medicines.

Authors:  Byeong Cheol Moon; Wook Jin Kim; Inkyu Park; Gi-Ho Sung; Pureum Noh
Journal:  Molecules       Date:  2018-08-02       Impact factor: 4.411

10.  Cuvette-Type LSPR Sensor for Highly Sensitive Detection of Melamine in Infant Formulas.

Authors:  Seo Yeong Oh; Min Ji Lee; Nam Su Heo; Suji Kim; Jeong Su Oh; Yuseon Lee; Eun Jeong Jeon; Hyungsil Moon; Hyung Soo Kim; Tae Jung Park; Guiim Moon; Hyang Sook Chun; Yun Suk Huh
Journal:  Sensors (Basel)       Date:  2019-09-05       Impact factor: 3.576

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