Standardization of model for the production of spray dried whey protein-zinc complex and its acceptability in milk

Construction and characterization of Zn-WPH-COS complex nanoparticles with improved zinc bioavailability

Precipitation was an important obstacle to improving zinc's bioavailability. Therefore, zinc-whey protein hydrolysate-chitosan oligosaccharide (Zn-WPH-COS) complexes (167 nm) were prepared by linking Zn-WPH (zinc: 18.4%) with COS (1:1, 2 h) to enhance zinc's bioaccessibility. Fourier-transform infrared showed Zn-WPH formed with zinc replaced hydrogen (from 3274 to 3279 cm-1) and reacted with COO- (C-N: from 1394 to 1402 cm-1), a new peak at 1025 cm-1 proved COS can be successful cross-linked (Zn-WPH-COS). Fluorescence spectra showed zinc and COS reduced WPH hydrophobicity (28.0 and 39.0%, respectively). Circular dichroism showed zinc decreased WPH α-helix (from 13.7 to 11.5%), in contrast with COS to Zn-WPH. Zinc solubility and dialyzability were increased (64.5/ 54.2% vs 50.2/ 41.2% vs 29.5/ 21.7%) in Zn-WPH-COS, compared with Zn-WPH and ZnSO4·7H2O, respectively, due to the smallest size (167 nm) and COS protection on Zn-WPH (gastric digestion). These results indicate Zn-WPH-COS could significantly improve the digestion and absorption of zinc.

Optimization of spray drying process parameters for the food bioactive ingredients

Spray drying (SD) is one of the most important thermal processes used to produce different powders and encapsulated materials. During this process, quality degradation might happen. The main objective of applying optimization methods in SD processes is maximizing the final nutritional quality of the product besides sensory attributes. Optimization regarding economic issues might be also performed. Applying optimization approaches in line with mathematical models to predict product changes during thermal processes such as SD can be a promising method to enhance the quality of final products. In this review, the application of the response surface methodology (RSM), as the most widely used approach, is introduced along with other optimization techniques such as factorial, Taguchi, and some artificial intelligence-based methods like artificial neural networks (ANN), genetic algorithms (GA), Fuzzy logic, and adaptive neuro-fuzzy inference system (ANFIS). Also, probabilistic methods such as Monte Carlo are briefly introduced. Some recent case studies regarding the implementation of these methods in SD processes are also exemplified and discussed.