Detection of butter adulteration with lard by employing 1H-NMR spectroscopy and multivariate data analysis
The use of proton Nuclear Magnetic Resonance (1H-NMR) spectroscopy allows the analysis of butter adulteration 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 b...
| Main Authors: | , , , , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
Halal Products Research Institute, Universiti Putra Malaysia
2014
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| Online Access: | http://psasir.upm.edu.my/id/eprint/63955/ http://psasir.upm.edu.my/id/eprint/63955/1/M36.pdf |
| _version_ | 1848854869120647168 |
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| author | Ahmad Fadzlillah, Nurrulhidayah Che Man, Yaakob Abdul Rohman Ismail, Amin Mustafa, Shuhaimi Rosman, Arieff Salleh Khatib, Alfi |
| author_facet | Ahmad Fadzlillah, Nurrulhidayah Che Man, Yaakob Abdul Rohman Ismail, Amin Mustafa, Shuhaimi Rosman, Arieff Salleh Khatib, Alfi |
| author_sort | Ahmad Fadzlillah, Nurrulhidayah |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | The use of proton Nuclear Magnetic Resonance (1H-NMR) spectroscopy allows the analysis of butter adulteration 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 using multivariate data analysis. The spectroscopic data of butter adulterated with lard samples were chemometrically evaluated and calibrated using the partial least square (PLS) algorithm. The multivariate calibration of PLS model for the prediction of adulterant was developed for quantitative measurement. The model yielded a highest regression coefficient (R2) = 0.998 and the lowest root mean square error calibration (RMSEC) = 0.0091 and root mean square error prediction (RMSEP) = 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. |
| first_indexed | 2025-11-15T11:16:43Z |
| format | Conference or Workshop Item |
| id | upm-63955 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T11:16:43Z |
| publishDate | 2014 |
| publisher | Halal Products Research Institute, Universiti Putra Malaysia |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-639552018-06-08T00:27:41Z http://psasir.upm.edu.my/id/eprint/63955/ Detection of butter adulteration with lard by employing 1H-NMR spectroscopy and multivariate data analysis Ahmad Fadzlillah, Nurrulhidayah Che Man, Yaakob Abdul Rohman Ismail, Amin Mustafa, Shuhaimi Rosman, Arieff Salleh Khatib, Alfi The use of proton Nuclear Magnetic Resonance (1H-NMR) spectroscopy allows the analysis of butter adulteration 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 using multivariate data analysis. The spectroscopic data of butter adulterated with lard samples were chemometrically evaluated and calibrated using the partial least square (PLS) algorithm. The multivariate calibration of PLS model for the prediction of adulterant was developed for quantitative measurement. The model yielded a highest regression coefficient (R2) = 0.998 and the lowest root mean square error calibration (RMSEC) = 0.0091 and root mean square error prediction (RMSEP) = 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. Halal Products Research Institute, Universiti Putra Malaysia 2014 Conference or Workshop Item PeerReviewed text en http://psasir.upm.edu.my/id/eprint/63955/1/M36.pdf Ahmad Fadzlillah, Nurrulhidayah and Che Man, Yaakob and Abdul Rohman and Ismail, Amin and Mustafa, Shuhaimi and Rosman, Arieff Salleh and Khatib, Alfi (2014) Detection of butter adulteration with lard by employing 1H-NMR spectroscopy and multivariate data analysis. In: Malaysia International Halal Research & Education Conference 2014 (MIHREC 2014), 2-4 Dec. 2014, Marriott Putrajaya Hotel, Malaysia. (p. 277). |
| spellingShingle | Ahmad Fadzlillah, Nurrulhidayah Che Man, Yaakob Abdul Rohman Ismail, Amin Mustafa, Shuhaimi Rosman, Arieff Salleh Khatib, Alfi Detection of butter adulteration with lard by employing 1H-NMR spectroscopy and multivariate data analysis |
| title | 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_short | 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 |
| url | http://psasir.upm.edu.my/id/eprint/63955/ http://psasir.upm.edu.my/id/eprint/63955/1/M36.pdf |