Application of ATR-FTIR incorporated with multivariate data analysis for discrimination and quantification of urea as an adulterant in UHT milk

Urea is naturally present in milk, yet urea is added intentionally to increase milk’s nitrogen content and shelf life. In this study, a total of 50 Ultra heat treatment (UHT) milk samples were spiked with known urea concentrations (0–5 w/v%). Attenuated total reflectance–Fourier transform infrared (...

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Main Authors: Tan, Emeline, Julmohammad, Norliza, Wee, Yin Koh, Abdullah Sani, Muhamad Shirwan, Rasti, Babak
Format: Article
Language:English
English
Published: MDPI 2023
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Online Access:http://irep.iium.edu.my/105819/13/105819_Application%20of%20ATR-FTIR%20incorporated%20with%20multivariate%20data%20analysis%20for%20discrimination.pdf
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spelling my.iium.irep.1058192023-11-02T03:48:09Z http://irep.iium.edu.my/105819/ Application of ATR-FTIR incorporated with multivariate data analysis for discrimination and quantification of urea as an adulterant in UHT milk Tan, Emeline Julmohammad, Norliza Wee, Yin Koh Abdullah Sani, Muhamad Shirwan Rasti, Babak QD Chemistry Urea is naturally present in milk, yet urea is added intentionally to increase milk’s nitrogen content and shelf life. In this study, a total of 50 Ultra heat treatment (UHT) milk samples were spiked with known urea concentrations (0–5 w/v%). Attenuated total reflectance–Fourier transform infrared (ATR-FTIR) spectroscopy with principal component analysis (PCA), discriminant analysis (DA), and multiple linear regression (MLR) were used for the discrimination and quantification of urea. The PCA was built using 387 variables with higher FL > 0.75 from the first PCA with cumulative variability (90.036%). Subsequently, the DA model was built using the same variables from PCA and demonstrated the good distinction between unadulterated and adulterated milk, with a correct classification rate of 98% for cross-validation. The MLR model used 48 variables with p-value < 0.05 from the DA model and gave R2 values greater than 0.90, with RMSE and MSE below 1 for cross-validation and prediction. The DA and MLR models were then validated externally using a test dataset, which shows 100% correct classification, and the test result (p > 0.05) indicated that the MLR could determine the percentage of urea in UHT milk within the permission limit (70 mg/mL). In short, the wavenumbers 1626.63, 1601.98, and 1585.5534 cm−1 are suitable as fingerprint regions for detecting urea in UHT milk MDPI 2023-07-27 Article PeerReviewed application/pdf en http://irep.iium.edu.my/105819/13/105819_Application%20of%20ATR-FTIR%20incorporated%20with%20multivariate%20data%20analysis%20for%20discrimination.pdf application/pdf en http://irep.iium.edu.my/105819/14/105819_Application%20of%20ATR-FTIR%20incorporated%20with%20multivariate%20data%20analysis%20for%20discrimination_Scopus.pdf Tan, Emeline and Julmohammad, Norliza and Wee, Yin Koh and Abdullah Sani, Muhamad Shirwan and Rasti, Babak (2023) Application of ATR-FTIR incorporated with multivariate data analysis for discrimination and quantification of urea as an adulterant in UHT milk. Foods, 12 (15). pp. 1-18. E-ISSN 2304-8158 https://www.mdpi.com/2304-8158/12/15/2855 10.3390/foods12152855
institution Universiti Islam Antarabangsa Malaysia
building IIUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider International Islamic University Malaysia
content_source IIUM Repository (IREP)
url_provider http://irep.iium.edu.my/
language English
English
topic QD Chemistry
spellingShingle QD Chemistry
Tan, Emeline
Julmohammad, Norliza
Wee, Yin Koh
Abdullah Sani, Muhamad Shirwan
Rasti, Babak
Application of ATR-FTIR incorporated with multivariate data analysis for discrimination and quantification of urea as an adulterant in UHT milk
description Urea is naturally present in milk, yet urea is added intentionally to increase milk’s nitrogen content and shelf life. In this study, a total of 50 Ultra heat treatment (UHT) milk samples were spiked with known urea concentrations (0–5 w/v%). Attenuated total reflectance–Fourier transform infrared (ATR-FTIR) spectroscopy with principal component analysis (PCA), discriminant analysis (DA), and multiple linear regression (MLR) were used for the discrimination and quantification of urea. The PCA was built using 387 variables with higher FL > 0.75 from the first PCA with cumulative variability (90.036%). Subsequently, the DA model was built using the same variables from PCA and demonstrated the good distinction between unadulterated and adulterated milk, with a correct classification rate of 98% for cross-validation. The MLR model used 48 variables with p-value < 0.05 from the DA model and gave R2 values greater than 0.90, with RMSE and MSE below 1 for cross-validation and prediction. The DA and MLR models were then validated externally using a test dataset, which shows 100% correct classification, and the test result (p > 0.05) indicated that the MLR could determine the percentage of urea in UHT milk within the permission limit (70 mg/mL). In short, the wavenumbers 1626.63, 1601.98, and 1585.5534 cm−1 are suitable as fingerprint regions for detecting urea in UHT milk
format Article
author Tan, Emeline
Julmohammad, Norliza
Wee, Yin Koh
Abdullah Sani, Muhamad Shirwan
Rasti, Babak
author_facet Tan, Emeline
Julmohammad, Norliza
Wee, Yin Koh
Abdullah Sani, Muhamad Shirwan
Rasti, Babak
author_sort Tan, Emeline
title Application of ATR-FTIR incorporated with multivariate data analysis for discrimination and quantification of urea as an adulterant in UHT milk
title_short Application of ATR-FTIR incorporated with multivariate data analysis for discrimination and quantification of urea as an adulterant in UHT milk
title_full Application of ATR-FTIR incorporated with multivariate data analysis for discrimination and quantification of urea as an adulterant in UHT milk
title_fullStr Application of ATR-FTIR incorporated with multivariate data analysis for discrimination and quantification of urea as an adulterant in UHT milk
title_full_unstemmed Application of ATR-FTIR incorporated with multivariate data analysis for discrimination and quantification of urea as an adulterant in UHT milk
title_sort application of atr-ftir incorporated with multivariate data analysis for discrimination and quantification of urea as an adulterant in uht milk
publisher MDPI
publishDate 2023
url http://irep.iium.edu.my/105819/13/105819_Application%20of%20ATR-FTIR%20incorporated%20with%20multivariate%20data%20analysis%20for%20discrimination.pdf
http://irep.iium.edu.my/105819/14/105819_Application%20of%20ATR-FTIR%20incorporated%20with%20multivariate%20data%20analysis%20for%20discrimination_Scopus.pdf
http://irep.iium.edu.my/105819/
https://www.mdpi.com/2304-8158/12/15/2855
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