Abstract
The sugar profile of a syrup determines its suitability for use in different food applications. The traditional wet chemical method for sugar profile analysis is time-consuming, destructive, and requires several chemical reagents. Therefore, this study aimed to develop a rapid method for determining the concentration of the main sugars (glucose, maltose, maltotriose, and fructose) in tapioca syrups using NIR spectroscopy in the 12000–4000 cm−1 wavenumber region or 800–2500 nm wavelength range. As large spectral variation due to water and liquid glucose was observed, orthogonal projection (OP) was evaluated to reduce those effects. Results showed that for all sugars studied, orthogonal projection prior to partial least squares regression (PLSR) improved the prediction performance in terms of the root mean square error of prediction (RMSEP) by 5–47% and the coefficient of determination for prediction (Rp2) by 3–7%. The developed models had high Rp2 and low RMSEP values, which provides opportunities for industrial monitoring of the sugar profiles of tapioca syrup products.
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