Raman spectroscopy coupled with the PLSR model: A rapid method for analyzing gamma-oryzanol content in rice bran oil
Issued Date
2024-12-30
Resource Type
eISSN
25901575
Scopus ID
2-s2.0-85207168392
Journal Title
Food Chemistry: X
Volume
24
Rights Holder(s)
SCOPUS
Bibliographic Citation
Food Chemistry: X Vol.24 (2024)
Suggested Citation
Lomarat P., Phechkrajang C., Sunghad P., Anantachoke N. Raman spectroscopy coupled with the PLSR model: A rapid method for analyzing gamma-oryzanol content in rice bran oil. Food Chemistry: X Vol.24 (2024). doi:10.1016/j.fochx.2024.101923 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/101843
Title
Raman spectroscopy coupled with the PLSR model: A rapid method for analyzing gamma-oryzanol content in rice bran oil
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Abstract
Rice bran oil (RBO) is widely used in food, nutraceutical, and cosmetic industries, due to its γ-oryzanol content, a key quality indicator. This study developed a rapid, non-destructive method for quantifying γ-oryzanol in RBO using Raman spectroscopy combined with partial least squares regression (PLSR). The optimal PLSR model, based on orthogonal signal correction (OSC)-pretreated data of Raman spectra from 800 to 1800 cm−1, demonstrated high accuracy with a strong R2-Pearson correlation coefficient of 0.9827 and low root mean square error of prediction (RMSEP) of 0.5314. Principal component analysis (PCA) of OSC-pretreated data showed improved sample grouping by concentration of γ-oryzanol compared to untreated data. Additionally, Bland-Altman plots comparing results from Raman and HPLC methods showed random scatter within ±2 SD of the mean difference, confirming the method's reliability. This study indicates that Raman spectroscopy can serve as a reliable method for determining γ-oryzanol content in RBO products within the related industries.