Detection of butter adulteration with lard by employing 1H-NMR spectroscopy and multivariate data analysis

The authentication of food products from the presence of non-allowed components for certain religion like lard is very important. In this study, we used proton Nuclear Magnetic Resonance (1H-NMR) spectroscopy for the analysis of butter adulterated with lard by simultaneously quantification of all pr...

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Main Authors: Ahmad Fadzlillah, Nurrulhidayah, Che Man, Yaakob, Abdul Rohman, Rosman, Arieff Salleh, Ismail, Amin, Mustafa, Shuhaimi, Khatib, Alfi
Format: Article
Language:English
Published: Japan Oil Chemists' Society 2015
Online Access:http://psasir.upm.edu.my/id/eprint/63956/1/Detection%20of%20butter%20adulteration%20with%20lard%20by%20employing%201H-NMR%20spectroscopy%20and%20multivariate%20data%20analysis.pdf
http://psasir.upm.edu.my/id/eprint/63956/
https://www.jstage.jst.go.jp/article/jos/64/7/64_ess14255/_article
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spelling my.upm.eprints.639562018-06-08T00:27:38Z http://psasir.upm.edu.my/id/eprint/63956/ Detection of butter adulteration with lard by employing 1H-NMR spectroscopy and multivariate data analysis Ahmad Fadzlillah, Nurrulhidayah Che Man, Yaakob Abdul Rohman Rosman, Arieff Salleh Ismail, Amin Mustafa, Shuhaimi Khatib, Alfi The authentication of food products from the presence of non-allowed components for certain religion like lard is very important. In this study, we used proton Nuclear Magnetic Resonance (1H-NMR) spectroscopy for the analysis of butter adulterated with lard by simultaneously quantification of all proton bearing compounds, and consequently all relevant sample classes. Since the spectra obtained were too complex to be analyzed visually by the naked eyes, the classification of spectra was carried out. The multivariate calibration of partial least square (PLS) regression was used for modelling the relationship between actual value of lard and predicted value. The model yielded a highest regression coefficient (R2) of 0.998 and the lowest root mean square error calibration (RMSEC) of 0.0091% and root mean square error prediction (RMSEP) of 0.0090, respectively. Cross validation testing evaluates the predictive power of the model. PLS model was shown as good models as the intercept of R2Y and Q2Y were 0.0853 and –0.309, respectively. Japan Oil Chemists' Society 2015 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/63956/1/Detection%20of%20butter%20adulteration%20with%20lard%20by%20employing%201H-NMR%20spectroscopy%20and%20multivariate%20data%20analysis.pdf Ahmad Fadzlillah, Nurrulhidayah and Che Man, Yaakob and Abdul Rohman and Rosman, Arieff Salleh and Ismail, Amin and Mustafa, Shuhaimi and Khatib, Alfi (2015) Detection of butter adulteration with lard by employing 1H-NMR spectroscopy and multivariate data analysis. Journal of Oleo Science, 64 (7). pp. 697-703. ISSN 1345-8957; ESSN: 1347-3352 https://www.jstage.jst.go.jp/article/jos/64/7/64_ess14255/_article 10.5650/jos.ess14255
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description The authentication of food products from the presence of non-allowed components for certain religion like lard is very important. In this study, we used proton Nuclear Magnetic Resonance (1H-NMR) spectroscopy for the analysis of butter adulterated with lard by simultaneously quantification of all proton bearing compounds, and consequently all relevant sample classes. Since the spectra obtained were too complex to be analyzed visually by the naked eyes, the classification of spectra was carried out. The multivariate calibration of partial least square (PLS) regression was used for modelling the relationship between actual value of lard and predicted value. The model yielded a highest regression coefficient (R2) of 0.998 and the lowest root mean square error calibration (RMSEC) of 0.0091% and root mean square error prediction (RMSEP) of 0.0090, respectively. Cross validation testing evaluates the predictive power of the model. PLS model was shown as good models as the intercept of R2Y and Q2Y were 0.0853 and –0.309, respectively.
format Article
author Ahmad Fadzlillah, Nurrulhidayah
Che Man, Yaakob
Abdul Rohman
Rosman, Arieff Salleh
Ismail, Amin
Mustafa, Shuhaimi
Khatib, Alfi
spellingShingle Ahmad Fadzlillah, Nurrulhidayah
Che Man, Yaakob
Abdul Rohman
Rosman, Arieff Salleh
Ismail, Amin
Mustafa, Shuhaimi
Khatib, Alfi
Detection of butter adulteration with lard by employing 1H-NMR spectroscopy and multivariate data analysis
author_facet Ahmad Fadzlillah, Nurrulhidayah
Che Man, Yaakob
Abdul Rohman
Rosman, Arieff Salleh
Ismail, Amin
Mustafa, Shuhaimi
Khatib, Alfi
author_sort Ahmad Fadzlillah, Nurrulhidayah
title Detection of butter adulteration with lard by employing 1H-NMR spectroscopy and multivariate data analysis
title_short Detection of butter adulteration with lard by employing 1H-NMR spectroscopy and multivariate data analysis
title_full Detection of butter adulteration with lard by employing 1H-NMR spectroscopy and multivariate data analysis
title_fullStr Detection of butter adulteration with lard by employing 1H-NMR spectroscopy and multivariate data analysis
title_full_unstemmed Detection of butter adulteration with lard by employing 1H-NMR spectroscopy and multivariate data analysis
title_sort detection of butter adulteration with lard by employing 1h-nmr spectroscopy and multivariate data analysis
publisher Japan Oil Chemists' Society
publishDate 2015
url http://psasir.upm.edu.my/id/eprint/63956/1/Detection%20of%20butter%20adulteration%20with%20lard%20by%20employing%201H-NMR%20spectroscopy%20and%20multivariate%20data%20analysis.pdf
http://psasir.upm.edu.my/id/eprint/63956/
https://www.jstage.jst.go.jp/article/jos/64/7/64_ess14255/_article
_version_ 1643837884301574144
score 13.19449