Abstract
Retrogradation behavior is an important physicochemical property of starch during storage. A fast and sensitive method was developed for determining the retrogradation degree (RD) in corn starch by mid-infrared (MIR), Raman spectroscopy, and combination of MIR and Raman. MIR and Raman spectra were collected from different retrogradation starch and then processed by partial least squares (PLS), interval PLS (iPLS), synergy interval PLS (siPLS), and backward interval PLS (biPLS). Two different levels of fusion data extracted from MIR and Raman spectra were analyzed by PLS. The developed models demonstrated that both MIR and Raman techniques combined with chemometrics can be used to determine the RD in starch. The PLS model built by medium-level fusion approach achieved the most satisfied performance with a correlation coefficient of 0.9658. Integrating MIR and Raman technique combined with chemometrics improved the prediction performance of RD in comparison with a single technique.
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