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FT-NIR, MicroNIR and LED-MicroNIR for detection of adulteration in palm oil via PLS and LDA

Chemometrics analysis was performed to compare the performance of FT-NIR, MicroNIR and LED-NIR for detection of adulteration in palm oil. FT-NIR has a high spectral resolution and signal-to-noise ratio, but MicroNIR is more light weight and suitable for on-site application. The feasibility of LED to...

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Main Authors: Basri, Katrul Nadia, Laili, Abdur Rehman, Tuhaime, Nur Azera, Hussain, Mutia Nurulhusna, Bakar, Jamilah, Sharif, Zaiton, Abdul Khir, Mohd Fared, Zoolfakar, Ahmad Sabirin
Format: Article
Language:English
Published: Royal Society of Chemistry 2018
Online Access:http://psasir.upm.edu.my/id/eprint/72800/1/FT-NIR.pdf
http://psasir.upm.edu.my/id/eprint/72800/
https://pubs.rsc.org/en/content/articlelanding/2018/ay/c8ay01239c#!divAbstract
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spelling my.upm.eprints.728002021-02-08T01:47:26Z http://psasir.upm.edu.my/id/eprint/72800/ FT-NIR, MicroNIR and LED-MicroNIR for detection of adulteration in palm oil via PLS and LDA Basri, Katrul Nadia Laili, Abdur Rehman Tuhaime, Nur Azera Hussain, Mutia Nurulhusna Bakar, Jamilah Sharif, Zaiton Abdul Khir, Mohd Fared Zoolfakar, Ahmad Sabirin Chemometrics analysis was performed to compare the performance of FT-NIR, MicroNIR and LED-NIR for detection of adulteration in palm oil. FT-NIR has a high spectral resolution and signal-to-noise ratio, but MicroNIR is more light weight and suitable for on-site application. The feasibility of LED to replace the conventional halogen tungsten light source in MicroNIR has been discussed in this paper. The wavelength of LEDs was based on the variable selection method, CARS, and the results were in good agreement with the C–H and O–H bond interaction displayed in the observed NIR spectrum. The advantages of using LED instead of a halogen tungsten light source are cost effectiveness, low power consumption and reduced number of variables. Different pretreatment approaches has been applied to the spectral data acquired to investigate the performance of preprocess to the result of chemometrics. Quantitative analysis was performed using partial least square (PLS) algorithms with the linear regression method. The best correlation coefficient, (R2), reported using FT-NIR was 0.99 with RMSEC and RMSEP values less than 1, indicating that the spread of calibration and prediction data was small. The LDA result showed that LED-NIR outperforms FT-NIR and MicroNIR with a sensitivity of 1.00 and a specificity of 0.9333. Royal Society of Chemistry 2018 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/72800/1/FT-NIR.pdf Basri, Katrul Nadia and Laili, Abdur Rehman and Tuhaime, Nur Azera and Hussain, Mutia Nurulhusna and Bakar, Jamilah and Sharif, Zaiton and Abdul Khir, Mohd Fared and Zoolfakar, Ahmad Sabirin (2018) FT-NIR, MicroNIR and LED-MicroNIR for detection of adulteration in palm oil via PLS and LDA. Analytical Methods, 10 (34). 4143 - 4151. ISSN 1759-9660; ESSN: 1759-9679 https://pubs.rsc.org/en/content/articlelanding/2018/ay/c8ay01239c#!divAbstract 10.1039/C8AY01239C
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 Chemometrics analysis was performed to compare the performance of FT-NIR, MicroNIR and LED-NIR for detection of adulteration in palm oil. FT-NIR has a high spectral resolution and signal-to-noise ratio, but MicroNIR is more light weight and suitable for on-site application. The feasibility of LED to replace the conventional halogen tungsten light source in MicroNIR has been discussed in this paper. The wavelength of LEDs was based on the variable selection method, CARS, and the results were in good agreement with the C–H and O–H bond interaction displayed in the observed NIR spectrum. The advantages of using LED instead of a halogen tungsten light source are cost effectiveness, low power consumption and reduced number of variables. Different pretreatment approaches has been applied to the spectral data acquired to investigate the performance of preprocess to the result of chemometrics. Quantitative analysis was performed using partial least square (PLS) algorithms with the linear regression method. The best correlation coefficient, (R2), reported using FT-NIR was 0.99 with RMSEC and RMSEP values less than 1, indicating that the spread of calibration and prediction data was small. The LDA result showed that LED-NIR outperforms FT-NIR and MicroNIR with a sensitivity of 1.00 and a specificity of 0.9333.
format Article
author Basri, Katrul Nadia
Laili, Abdur Rehman
Tuhaime, Nur Azera
Hussain, Mutia Nurulhusna
Bakar, Jamilah
Sharif, Zaiton
Abdul Khir, Mohd Fared
Zoolfakar, Ahmad Sabirin
spellingShingle Basri, Katrul Nadia
Laili, Abdur Rehman
Tuhaime, Nur Azera
Hussain, Mutia Nurulhusna
Bakar, Jamilah
Sharif, Zaiton
Abdul Khir, Mohd Fared
Zoolfakar, Ahmad Sabirin
FT-NIR, MicroNIR and LED-MicroNIR for detection of adulteration in palm oil via PLS and LDA
author_facet Basri, Katrul Nadia
Laili, Abdur Rehman
Tuhaime, Nur Azera
Hussain, Mutia Nurulhusna
Bakar, Jamilah
Sharif, Zaiton
Abdul Khir, Mohd Fared
Zoolfakar, Ahmad Sabirin
author_sort Basri, Katrul Nadia
title FT-NIR, MicroNIR and LED-MicroNIR for detection of adulteration in palm oil via PLS and LDA
title_short FT-NIR, MicroNIR and LED-MicroNIR for detection of adulteration in palm oil via PLS and LDA
title_full FT-NIR, MicroNIR and LED-MicroNIR for detection of adulteration in palm oil via PLS and LDA
title_fullStr FT-NIR, MicroNIR and LED-MicroNIR for detection of adulteration in palm oil via PLS and LDA
title_full_unstemmed FT-NIR, MicroNIR and LED-MicroNIR for detection of adulteration in palm oil via PLS and LDA
title_sort ft-nir, micronir and led-micronir for detection of adulteration in palm oil via pls and lda
publisher Royal Society of Chemistry
publishDate 2018
url http://psasir.upm.edu.my/id/eprint/72800/1/FT-NIR.pdf
http://psasir.upm.edu.my/id/eprint/72800/
https://pubs.rsc.org/en/content/articlelanding/2018/ay/c8ay01239c#!divAbstract
_version_ 1691734445563838464
score 13.211869

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