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Quick and reagent-free monitoring of edible oil saponification values using a handheld Raman device

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dc.contributor.author Ajikumar, N
dc.contributor.author Emmanuel, N
dc.contributor.author Abraham, B
dc.contributor.author John, A
dc.contributor.author Pulparamban, A
dc.contributor.author Unni, K N N
dc.contributor.author Yoosaf, K
dc.date.accessioned 2025-05-05T11:34:46Z
dc.date.available 2025-05-05T11:34:46Z
dc.date.issued 2025-02-01
dc.identifier.citation Food Chemistry; 464:141580 en_US
dc.identifier.uri https://www.sciencedirect.com/science/article/pii/S0308814624032308?via%3Dihub
dc.identifier.uri http://localhost:8080/xmlui/handle/123456789/4902
dc.description.abstract Saponification value, the average molecular weight of fatty acids, is a crucial parameter for detecting adulteration of edible oils. Conventionally, it is determined in a laboratory setup through a time-consuming, laborious titration process using chemical reagents. Herein, the application of Raman spectroscopy for quick SV estimation of oils is demonstrated. It was hypothesized that the SV can be predicted from Raman spectra since the spectral patterns reflect the composition of fatty acid triglycerides. Two model oil systems were studied: coconut-gingelly oil and coconut-sunflower oil. Univariate models built from Raman spectra were successful only for the specific oil system; hence, PLS-Regression was executed across the two systems. The PLSR model on the validation set returned the average error, percentage error, and root mean square error of prediction as 2.1, 0.99 %, and 2.4, respectively. This method offers several advantages of portability, little reagent use, minimal sample preparation, and reduced analysis time. en_US
dc.language.iso en en_US
dc.publisher Elsevier en_US
dc.subject oil adulteration en_US
dc.subject Raman spectroscopy en_US
dc.subject multivariate analysis en_US
dc.title Quick and reagent-free monitoring of edible oil saponification values using a handheld Raman device en_US
dc.type Article en_US


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  • 2025
    Research articles authored by NIIST researchers published in 2025

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