Gum Arabic authentication and mixture quantification by near infrared spectroscopy

Research output: Contribution to journal › Journal article › Research › peer-review

Standard

Gum Arabic authentication and mixture quantification by near infrared spectroscopy. / Dong, Yongjiang; Sørensen, Klavs Martin; He, Sailing; Engelsen, Søren Balling.

In: Food Control, Vol. 78, 2017, p. 144-149.

Research output: Contribution to journal › Journal article › Research › peer-review

Harvard

Dong, Y, Sørensen, KM, He, S & Engelsen, SB 2017, 'Gum Arabic authentication and mixture quantification by near infrared spectroscopy', Food Control, vol. 78, pp. 144-149. https://doi.org/10.1016/j.foodcont.2017.02.002

APA

Dong, Y., Sørensen, K. M., He, S., & Engelsen, S. B. (2017). Gum Arabic authentication and mixture quantification by near infrared spectroscopy. Food Control, 78, 144-149. https://doi.org/10.1016/j.foodcont.2017.02.002

Vancouver

Dong Y, Sørensen KM, He S, Engelsen SB. Gum Arabic authentication and mixture quantification by near infrared spectroscopy. Food Control. 2017;78:144-149. https://doi.org/10.1016/j.foodcont.2017.02.002

Author

Dong, Yongjiang ; Sørensen, Klavs Martin ; He, Sailing ; Engelsen, Søren Balling. / Gum Arabic authentication and mixture quantification by near infrared spectroscopy. In: Food Control. 2017 ; Vol. 78. pp. 144-149.

Bibtex

@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",

}

RIS

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

VL - 78

SP - 144

EP - 149

JO - Food Control

JF - Food Control

SN - 0956-7135

ER -

ID: 176653574