Literature DB >> 35185196

Electronic nose for detection of food adulteration: a review.

Mrinmoy Roy1, B K Yadav1.   

Abstract

The food products may attract unscrupulous vendors to dilute it with inexpensive alternative food sources to achieve more profit. The risk of high value food adulteration with cheaper substitutes has reached an alarming stage in recent years. Commonly available detection methods for food adulteration are costly, time consuming and requires high degree of technical expertise. However, a rapid and suitable detection method for possible adulterant is being evolved to tackle the aforesaid issues. In recent years, electronic nose (e-nose) system is being evolved for falsification detection of food products with reliable and rapid way. E-nose has the ability to artificially perceive aroma and distinguish them. The use of chemometric analysis together with gas sensor arrays have shown to be a significant procedure for quality monitoring in food. E-nose techniques with numerous provisions are reliable and favourable for food industry in food fraud detection. In the present review, the contributions of gas sensor based e-nose system are discussed extensively with a view to ascertain the adulteration of food products. © Association of Food Scientists & Technologists (India) 2021.

Entities:  

Keywords:  Adulteration; Aroma; Chemometric analysis; E-nose; Sensor

Year:  2021        PMID: 35185196      PMCID: PMC8814237          DOI: 10.1007/s13197-021-05057-w

Source DB:  PubMed          Journal:  J Food Sci Technol        ISSN: 0022-1155            Impact factor:   2.701


  9 in total

1.  Direct olive oil authentication: detection of adulteration of olive oil with hazelnut oil by direct coupling of headspace and mass spectrometry, and multivariate regression techniques.

Authors:  Fernando Peña; Soledad Cárdenas; Mercedes Gallego; Miguel Valcárcel
Journal:  J Chromatogr A       Date:  2005-05-13       Impact factor: 4.759

Review 2.  Contributions of topography and parallel processing to odor coding in the vertebrate olfactory pathway.

Authors:  J S Kauer
Journal:  Trends Neurosci       Date:  1991-02       Impact factor: 13.837

Review 3.  Soybean oil: genetic approaches for modification of functionality and total content.

Authors:  Tom E Clemente; Edgar B Cahoon
Journal:  Plant Physiol       Date:  2009-09-25       Impact factor: 8.340

4.  Discrimination of producing area of Chinese Tongshan kaoliang spirit using electronic nose sensing characteristics combined with the chemometrics methods.

Authors:  Qi Peng; Rungang Tian; Feiran Chen; Bobin Li; Hegang Gao
Journal:  Food Chem       Date:  2015-01-09       Impact factor: 7.514

5.  Analysis of discrimination mechanisms in the mammalian olfactory system using a model nose.

Authors:  K Persaud; G Dodd
Journal:  Nature       Date:  1982-09-23       Impact factor: 49.962

6.  Voltammetric fingerprinting of oils and its combination with chemometrics for the detection of extra virgin olive oil adulteration.

Authors:  Fotios Tsopelas; Dimitris Konstantopoulos; Anna Tsantili Kakoulidou
Journal:  Anal Chim Acta       Date:  2018-02-20       Impact factor: 6.558

7.  Rapid detection of adulterated peony seed oil by electronic nose.

Authors:  Xiaobao Wei; Xingfeng Shao; Yingying Wei; Lingzhi Cheong; Leiqing Pan; Kang Tu
Journal:  J Food Sci Technol       Date:  2018-04-27       Impact factor: 2.701

8.  A biomimetic sensor for the classification of honeys of different floral origin and the detection of adulteration.

Authors:  Ammar Zakaria; Ali Yeon Md Shakaff; Maz Jamilah Masnan; Mohd Noor Ahmad; Abdul Hamid Adom; Mahmad Nor Jaafar; Supri A Ghani; Abu Hassan Abdullah; Abdul Hallis Abdul Aziz; Latifah Munirah Kamarudin; Norazian Subari; Nazifah Ahmad Fikri
Journal:  Sensors (Basel)       Date:  2011-08-09       Impact factor: 3.576

9.  A hybrid sensing approach for pure and adulterated honey classification.

Authors:  Norazian Subari; Junita Mohamad Saleh; Ali Yeon Md Shakaff; Ammar Zakaria
Journal:  Sensors (Basel)       Date:  2012-10-17       Impact factor: 3.576

  9 in total

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