Publications by authors named "Donghai Hao"

Background: Human milk fat analog emulsion (HMFAE) is an emulsion that mimics the composition and structure of human milk (HM) fat globules. The application of HMFAE in infant formula requires a series of milk powder processing steps, such as pasteurization and spray drying. However, the effect of milk powder processing on fat digestion of HMFAE is still unclear.

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Differences in the composition and structure of lipid droplets in infant formula (IF) and human milk (HM) can affect the fat digestion of infants, leading to high risk of metabolic diseases during later stages of growth. Recently, interest in simulating HM fat (HMF) has gradually increased due to its beneficial functions for infants. Much research focuses on the simulation of fatty acids and triacylglycerols.

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In order to achieve rapid detection of galactooligosaccharides (GOS), fructooligosaccharides (FOS), calcium (Ca), and vitamin C (Vc), four micronutrient components in infant formula milk powder, this study employed four methods, namely Standard Normal Variate (SNV), Multiplicative Scatter Correction (MSC), Normalization (Nor), and Savitzky-Golay Smoothing (SG), to preprocess the acquired original spectra of the milk powder. Then, the Competitive Adaptive Reweighted Sampling (CARS) algorithm and Random Frog (RF) algorithm were used to extract representative characteristic wavelengths. Furthermore, Partial Least Squares Regression (PLSR) and Support Vector Regression (SVR) models were established to predict the contents of GOS, FOS, Ca, and Vc in infant formula milk powder.

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