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Title: Non-targeted NIR spectroscopy and SIMCA classification for commercial milk powder authentication: A study using eleven potential adulterants

Abstract

A non-targeted detection method using near-infrared (NIR) spectroscopy combined with chemometric modeling was developed for the rapid screening of commercial milk powder (MP) products as authentic or potentially mixed with known and unknown adulterants. Two benchtop FT-NIR spectrometers and a handheld NIR device were evaluated for model development. The performance of SIMCA classification models was then validated using an independent test set of genuine MP samples and a set of gravimetrically prepared mixtures consisting of MPs spiked with each of eleven potential adulterants. Classification models yielded 100% sensitivities for the benchtop spectrometers. Better specificity, which was influenced by the nature of the adulterant, was obtained for the benchtop FT-NIR instruments than for the handheld NIR device, which suffered from lower spectral resolution and a narrower spectral range. FT-NIR spectroscopy and SIMCA classification models show promise for the rapid screening of commercial MPs for the detection of potential adulteration.

Authors:
; ORCiD logo; ORCiD logo; ;
Publication Date:
Research Org.:
Oak Ridge Inst. for Science and Education (ORISE), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE Advanced Research Projects Agency - Energy (ARPA-E)
OSTI Identifier:
1471791
Alternate Identifier(s):
OSTI ID: 1630009
Grant/Contract Number:  
SC0014664
Resource Type:
Published Article
Journal Name:
Heliyon
Additional Journal Information:
Journal Name: Heliyon Journal Volume: 4 Journal Issue: 9; Journal ID: ISSN 2405-8440
Publisher:
Elsevier
Country of Publication:
United Kingdom
Language:
English

Citation Formats

Karunathilaka, Sanjeewa R., Yakes, Betsy Jean, He, Keqin, Chung, Jin Kyu, and Mossoba, Magdi. Non-targeted NIR spectroscopy and SIMCA classification for commercial milk powder authentication: A study using eleven potential adulterants. United Kingdom: N. p., 2018. Web. doi:10.1016/j.heliyon.2018.e00806.
Karunathilaka, Sanjeewa R., Yakes, Betsy Jean, He, Keqin, Chung, Jin Kyu, & Mossoba, Magdi. Non-targeted NIR spectroscopy and SIMCA classification for commercial milk powder authentication: A study using eleven potential adulterants. United Kingdom. https://doi.org/10.1016/j.heliyon.2018.e00806
Karunathilaka, Sanjeewa R., Yakes, Betsy Jean, He, Keqin, Chung, Jin Kyu, and Mossoba, Magdi. Sat . "Non-targeted NIR spectroscopy and SIMCA classification for commercial milk powder authentication: A study using eleven potential adulterants". United Kingdom. https://doi.org/10.1016/j.heliyon.2018.e00806.
@article{osti_1471791,
title = {Non-targeted NIR spectroscopy and SIMCA classification for commercial milk powder authentication: A study using eleven potential adulterants},
author = {Karunathilaka, Sanjeewa R. and Yakes, Betsy Jean and He, Keqin and Chung, Jin Kyu and Mossoba, Magdi},
abstractNote = {A non-targeted detection method using near-infrared (NIR) spectroscopy combined with chemometric modeling was developed for the rapid screening of commercial milk powder (MP) products as authentic or potentially mixed with known and unknown adulterants. Two benchtop FT-NIR spectrometers and a handheld NIR device were evaluated for model development. The performance of SIMCA classification models was then validated using an independent test set of genuine MP samples and a set of gravimetrically prepared mixtures consisting of MPs spiked with each of eleven potential adulterants. Classification models yielded 100% sensitivities for the benchtop spectrometers. Better specificity, which was influenced by the nature of the adulterant, was obtained for the benchtop FT-NIR instruments than for the handheld NIR device, which suffered from lower spectral resolution and a narrower spectral range. FT-NIR spectroscopy and SIMCA classification models show promise for the rapid screening of commercial MPs for the detection of potential adulteration.},
doi = {10.1016/j.heliyon.2018.e00806},
journal = {Heliyon},
number = 9,
volume = 4,
place = {United Kingdom},
year = {2018},
month = {9}
}