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* Food Chemistry, Department of Dairy and Food Science, The Royal Veterinary and Agricultural University, Rolighedsvej 30, DK-1958 Frederiksberg C, Denmark
Food Technology, Department of Dairy and Food Science, The Royal Veterinary and Agricultural University, Rolighedsvej 30, DK-1958 Frederiksberg C, Denmark
Corresponding author:
J. Christensen; e-mail:
jach{at}kvl.dk.
The present study demonstrates the use of front-face fluorescence spectroscopy and chemometrics for monitoring light-induced changes in plain yogurt during storage. Fluorescence analysis is suggested as a new rapid method for measuring riboflavin content in yogurt. Fluorescence landscapes with excitation wavelengths from 270 to 550 nm and emission wavelengths in the range 310 to 590 nm were obtained from front-face fluorescence measurements directly on yogurt samples during two storage experiments over a period of 5 wk at 4°C. Yogurts were stored in two different packaging materials (polylactate and polystyrene) and under fluorescent light (3500 lux) or in darkness. Principal Component Analysis of unfolded fluorescence emission spectra revealed systematic changes in fluorescence signal throughout the storage period, strongly related to the storage conditions, i.e. storage time and differences in packaging materials. Correlation between fluorescence spectra and riboflavin content determined by the standard AOAC fluorometric method was evaluated using a Partial Least Square Regression model. The regression model showed a good ability to predict riboflavin in plain yogurt with a high correlation (R = 0.99) and a prediction error of 0.092 µg riboflavin/g. Thus, it is concluded that nondestructive fluorescence spectroscopy can be used to monitor riboflavin content in yogurt, and that the suggested rapid method has the potential to substitute the standard method for analysis of riboflavin in yogurt.
Key Words: fluorescence spectroscopy chemometrics riboflavin yogurt light-induced oxidation
Abbreviation key: PCA = principal component analysis, PC = principal component, PLSR = partial least squares regression, RMSECV = root mean square error of cross validation, PLA = polylactate, PS = polystyrene
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