Gum Arabic authentication and mixture quantification by near infrared spectroscopy

Yongjiang Dong; Klavs Martin Sørensen; Sailing He; Søren Balling Engelsen

doi:10.1016/j.foodcont.2017.02.002

Gum Arabic authentication and mixture quantification by near infrared spectroscopy

Yongjiang Dong, Klavs Martin Sørensen^*, Sailing He, Søren Balling Engelsen

^*Corresponding author af dette arbejde

Food Analytics and Biotechnology

15 Citationer (Scopus)

Abstract

A rapid and reliable method is developed for Gum Arabic authentication based on Near Infrared (NIR) spectroscopy and chemometric methods. On a large industrial collection of authentic gum Arabics, the two major Acacia gum species, Acacia senegal and Acacia seyal could be assigned perfectly by the NIR spectroscopic method. In addition, a partial least squares (PLS) regression model is calibrated to predict the blending percentage of the two pure gum types, producing an accuracy, root mean square error of cross validation (RMSECV) of 2.8%. Sampling of the Gum Arabic ‘tears’ is discussed, and it was determined that subsamples from three ‘tears’ is required for a representative result. It is concluded that NIR spectroscopy is a very powerful and reliable method for authenticity testing of Gum Arabic species

Originalsprog	Engelsk
Tidsskrift	Food Control
Vol/bind	78
Sider (fra-til)	144-149
Antal sider	6
ISSN	0956-7135
DOI	https://doi.org/10.1016/j.foodcont.2017.02.002
Status	Udgivet - 2017

Adgang til dokumentet

10.1016/j.foodcont.2017.02.002

Citationsformater

@article{01421bc981a644fe8b6e90f72dfc2f3c,

title = "Gum Arabic authentication and mixture quantification by near infrared spectroscopy",

abstract = "A rapid and reliable method is developed for Gum Arabic authentication based on Near Infrared (NIR) spectroscopy and chemometric methods. On a large industrial collection of authentic gum Arabics, the two major Acacia gum species, Acacia senegal and Acacia seyal could be assigned perfectly by the NIR spectroscopic method. In addition, a partial least squares (PLS) regression model is calibrated to predict the blending percentage of the two pure gum types, producing an accuracy, root mean square error of cross validation (RMSECV) of 2.8%. Sampling of the Gum Arabic {\textquoteleft}tears{\textquoteright} is discussed, and it was determined that subsamples from three {\textquoteleft}tears{\textquoteright} is required for a representative result. It is concluded that NIR spectroscopy is a very powerful and reliable method for authenticity testing of Gum Arabic species.",

keywords = "Acacia senegal, Acacia seyal, Gum Arabic, Near infrared (NIR) spectroscopy, Partial least squares (PLS) regression, Principal component analysis (PCA), Sampling of {\textquoteleft}tears{\textquoteright}",

author = "Yongjiang Dong and S{\o}rensen, {Klavs Martin} and Sailing He and Engelsen, {S{\o}ren Balling}",

year = "2017",

doi = "10.1016/j.foodcont.2017.02.002",

language = "English",

volume = "78",

pages = "144--149",

journal = "Food Control",

issn = "0956-7135",

publisher = "Pergamon Press",

}

TY - JOUR

T1 - Gum Arabic authentication and mixture quantification by near infrared spectroscopy

AU - Dong, Yongjiang

AU - Sørensen, Klavs Martin

AU - He, Sailing

AU - Engelsen, Søren Balling

PY - 2017

Y1 - 2017

N2 - A rapid and reliable method is developed for Gum Arabic authentication based on Near Infrared (NIR) spectroscopy and chemometric methods. On a large industrial collection of authentic gum Arabics, the two major Acacia gum species, Acacia senegal and Acacia seyal could be assigned perfectly by the NIR spectroscopic method. In addition, a partial least squares (PLS) regression model is calibrated to predict the blending percentage of the two pure gum types, producing an accuracy, root mean square error of cross validation (RMSECV) of 2.8%. Sampling of the Gum Arabic ‘tears’ is discussed, and it was determined that subsamples from three ‘tears’ is required for a representative result. It is concluded that NIR spectroscopy is a very powerful and reliable method for authenticity testing of Gum Arabic species.

AB - A rapid and reliable method is developed for Gum Arabic authentication based on Near Infrared (NIR) spectroscopy and chemometric methods. On a large industrial collection of authentic gum Arabics, the two major Acacia gum species, Acacia senegal and Acacia seyal could be assigned perfectly by the NIR spectroscopic method. In addition, a partial least squares (PLS) regression model is calibrated to predict the blending percentage of the two pure gum types, producing an accuracy, root mean square error of cross validation (RMSECV) of 2.8%. Sampling of the Gum Arabic ‘tears’ is discussed, and it was determined that subsamples from three ‘tears’ is required for a representative result. It is concluded that NIR spectroscopy is a very powerful and reliable method for authenticity testing of Gum Arabic species.

KW - Acacia senegal

KW - Acacia seyal

KW - Gum Arabic

KW - Near infrared (NIR) spectroscopy

KW - Partial least squares (PLS) regression

KW - Principal component analysis (PCA)

KW - Sampling of ‘tears’

U2 - 10.1016/j.foodcont.2017.02.002

DO - 10.1016/j.foodcont.2017.02.002

M3 - Journal article

AN - SCOPUS:85013982109

SN - 0956-7135

VL - 78

SP - 144

EP - 149

JO - Food Control

JF - Food Control

ER -

Gum Arabic authentication and mixture quantification by near infrared spectroscopy

Abstract

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