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Rice bran FFA determination by diffuse reflectance IR spectroscopy
Author(s) -
ÖzgülYücel Sevil,
Proctor Andrew
Publication year - 2004
Publication title -
journal of the american oil chemists' society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.512
H-Index - 117
eISSN - 1558-9331
pISSN - 0003-021X
DOI - 10.1007/s11746-004-0885-8
Subject(s) - bran , rice bran oil , chemistry , partial least squares regression , coefficient of determination , food science , analytical chemistry (journal) , mathematics , chromatography , organic chemistry , raw material , statistics
Rice bran with FFA levels above 0.1% cannot be used as a food ingredient due to oxidative off‐flavor formation. However, extracting high FFA oil from bran by in situ methanolic esterification of rice bran oil to produce methyl ester biodiesel produces greater yields relative to low‐FFA rice bran oil. Therefore, high‐FFA bran could be exploited for biodiesel production. This study describes an FTIR spectroscopic method to measure rice bran FFA rapidly. Commercial rice bran was incubated at 37°C and 70% humidity for a 13‐d incubation period. Diffuse reflectance IR Fourier transform spectra of the bran were obtained and the percentage of FFA was determined by extraction and acid/base titration throughout this period. Partial least squares (PLS) regression and a calibration/validation analysis were done using the IR spectral regions 4000‐400 cm −1 and 1731‐1631 cm −1 . The diffuse reflectance IR Fourier transform spectra indicated an increasing FFA carbonyl response at the expense of the ester peak during incubation, and the regression coefficients obtained by PLS analysis also demonstrated that these functional groups and the carboxyl ion were important in predicting FFA levels. FFA rice bran changes also could be observed qualitatively by visual examination of the spectra. Calibration models obtained using the spectral regions 4000‐400 cm −1 and 1731‐1631 cm −1 produced correlation coefficients R and root mean square error (RMSE) of cross‐validation of R =0.99, RMSE=1.78, and R =0.92, RMSE=4.67, respectively. Validation model statistics using the 4000‐400 cm −1 and 1731‐1631 cm −1 ranges were R =0.96, RMSE=3.64, and R =0.88, RMSE=5.80, respectively.

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