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Classification and quantification of palm oil adulteration via portable NIR spectroscopy

Short wave near infrared spectroscopy (NIR) method was used to detect the presence of lard adulteration in palm oil. MicroNIR was set up in two different scan modes to study the effect of path length to the performance of spectral measurement. Pure and adulterated palm oil sample were classified usi...

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Main Authors: Basri, Katrul Nadia, Hussain, Mutia Nurulhusna, Bakar, Jamilah, Sharif, Zaiton, Abdul Khir, Mohd Fared, Zoolfakar, Ahmad Sabirin
Format: Article
Language:English
Published: Elsevier 2017
Online Access:http://psasir.upm.edu.my/id/eprint/61116/1/Classification%20and%20quantification%20of%20palm%20oil%20adulteration%20via%20portable%20NIR%20spectroscopy.pdf
http://psasir.upm.edu.my/id/eprint/61116/
https://www.sciencedirect.com/science/article/pii/S1386142516305455?via%3Dihub
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spelling my.upm.eprints.611162019-05-14T01:43:33Z http://psasir.upm.edu.my/id/eprint/61116/ Classification and quantification of palm oil adulteration via portable NIR spectroscopy Basri, Katrul Nadia Hussain, Mutia Nurulhusna Bakar, Jamilah Sharif, Zaiton Abdul Khir, Mohd Fared Zoolfakar, Ahmad Sabirin Short wave near infrared spectroscopy (NIR) method was used to detect the presence of lard adulteration in palm oil. MicroNIR was set up in two different scan modes to study the effect of path length to the performance of spectral measurement. Pure and adulterated palm oil sample were classified using soft independent modeling class analogy (SIMCA) algorithm with model accuracy more than 0.95 reported for both transflectance and transmission modes. Additionally, by employing partial least square (PLS) regression, the coefficient of determination (R2) of transflectance and transmission were 0.9987 and 0.9994 with root mean square error of calibration (RMSEC) of 0.5931 and 0.6703 respectively. In order to remove the uninformative variables, variable selection using cumulative adaptive reweighted sampling (CARS) has been performed. The result of R2 and RMSEC after variable selection for transflectance and transmission were improved significantly. Based on the result of classification and quantification analysis, the transmission mode has yield better prediction model compared to the transflectance mode to distinguish the pure and adulterated palm oil. Elsevier 2017 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/61116/1/Classification%20and%20quantification%20of%20palm%20oil%20adulteration%20via%20portable%20NIR%20spectroscopy.pdf Basri, Katrul Nadia and Hussain, Mutia Nurulhusna and Bakar, Jamilah and Sharif, Zaiton and Abdul Khir, Mohd Fared and Zoolfakar, Ahmad Sabirin (2017) Classification and quantification of palm oil adulteration via portable NIR spectroscopy. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 173. pp. 335-342. ISSN 1386-1425; ESSN: 1873-3557 https://www.sciencedirect.com/science/article/pii/S1386142516305455?via%3Dihub 10.1016/j.saa.2016.09.028
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 Short wave near infrared spectroscopy (NIR) method was used to detect the presence of lard adulteration in palm oil. MicroNIR was set up in two different scan modes to study the effect of path length to the performance of spectral measurement. Pure and adulterated palm oil sample were classified using soft independent modeling class analogy (SIMCA) algorithm with model accuracy more than 0.95 reported for both transflectance and transmission modes. Additionally, by employing partial least square (PLS) regression, the coefficient of determination (R2) of transflectance and transmission were 0.9987 and 0.9994 with root mean square error of calibration (RMSEC) of 0.5931 and 0.6703 respectively. In order to remove the uninformative variables, variable selection using cumulative adaptive reweighted sampling (CARS) has been performed. The result of R2 and RMSEC after variable selection for transflectance and transmission were improved significantly. Based on the result of classification and quantification analysis, the transmission mode has yield better prediction model compared to the transflectance mode to distinguish the pure and adulterated palm oil.
format Article
author Basri, Katrul Nadia
Hussain, Mutia Nurulhusna
Bakar, Jamilah
Sharif, Zaiton
Abdul Khir, Mohd Fared
Zoolfakar, Ahmad Sabirin
spellingShingle Basri, Katrul Nadia
Hussain, Mutia Nurulhusna
Bakar, Jamilah
Sharif, Zaiton
Abdul Khir, Mohd Fared
Zoolfakar, Ahmad Sabirin
Classification and quantification of palm oil adulteration via portable NIR spectroscopy
author_facet Basri, Katrul Nadia
Hussain, Mutia Nurulhusna
Bakar, Jamilah
Sharif, Zaiton
Abdul Khir, Mohd Fared
Zoolfakar, Ahmad Sabirin
author_sort Basri, Katrul Nadia
title Classification and quantification of palm oil adulteration via portable NIR spectroscopy
title_short Classification and quantification of palm oil adulteration via portable NIR spectroscopy
title_full Classification and quantification of palm oil adulteration via portable NIR spectroscopy
title_fullStr Classification and quantification of palm oil adulteration via portable NIR spectroscopy
title_full_unstemmed Classification and quantification of palm oil adulteration via portable NIR spectroscopy
title_sort classification and quantification of palm oil adulteration via portable nir spectroscopy
publisher Elsevier
publishDate 2017
url http://psasir.upm.edu.my/id/eprint/61116/1/Classification%20and%20quantification%20of%20palm%20oil%20adulteration%20via%20portable%20NIR%20spectroscopy.pdf
http://psasir.upm.edu.my/id/eprint/61116/
https://www.sciencedirect.com/science/article/pii/S1386142516305455?via%3Dihub
_version_ 1643837509217550336
score 13.211869

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