Simple Search:

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


Citation

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

Abstract / Synopsis

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.


Download File

[img]
Preview
PDF (Abstract)
Detection of butter adulteration with lard by employing 1H-NMR spectroscopy and multivariate data analysis.pdf

Download (50kB) | Preview

Additional Metadata

Item Type: Article
Divisions: Faculty of Medicine and Health Science
Halal Products Research Institute
Institute of Bioscience
DOI Number: https://doi.org/10.5650/jos.ess14255
Publisher: Japan Oil Chemists' Society
Keywords: Butter; Lard; 1H-NMR; Multivariate data analysis; Adulteration; Chemometric
Depositing User: Nabilah Mustapa
Date Deposited: 08 Jun 2018 08:27
Last Modified: 08 Jun 2018 08:27
Altmetrics: http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.5650/jos.ess14255
URI: http://psasir.upm.edu.my/id/eprint/63956
Statistic Details: View Download Statistic

Actions (login required)

View Item View Item