Studying Release Kinetic of Cinnamaldehyde Microencapsulated with High Amylose Corn Starch in Simulated Mouth Conditions and During Storage and Optimizing Microcapsules Properties using Parametric Sweep

Samanian, Nargess; Mohebbi, Mohebbat; Razavi, Seyed Mohammad Ali; Varidi, Mahdi; Abolfazl Esfahani, Javad

doi:10.22101/JRIFST.2022.327161.1323

Studying Release Kinetic of Cinnamaldehyde Microencapsulated with High Amylose Corn Starch in Simulated Mouth Conditions and During Storage and Optimizing Microcapsules Properties using Parametric Sweep

Document Type : Original Paper

Authors

¹ Department of Food Science and Technology, Ferdowsi University of Mashhad, Mashhad, Iran

² Center of Excellence in Native Natural Hydrocolloids of Iran, Ferdowsi University of Mashhad, Mashhad, Iran

³ Department of Mechanical Engineering, Ferdowsi University of Mashhad, Mashhad, Iran

10.22101/JRIFST.2022.327161.1323

Abstract

In this research, the possibility of cinnamaldehyde encapsulating with high amylose starch using ultrasound treatment was studied. The resulting microcapsules had an average size of 636.36±59.041 nm. The included cinnamaldehyde was 53.44±1.29, which only increased by 3 percent during 28 days of storage. Also, cinnamaldehyde release was investigated under simulated mouth conditions including temperature, saliva composition, and shear stress, using SPME-GC-MS, which was followed by analytical modeling. Among analytical kinetic models, zero-degree, Korsmeyer-Peppas, and Makoid-Banakar models during in-mouth release, and Korsmeyer-Peppas model during storage had the greatest agreements with release profiles. Using the results a 3 phase, 2D, constant source , reservoir model was simulated and solved using Comsol Multiphysics 5.6. Mesh independence analysis and low RMSE (1.78×10^-6) alongside high R²(0.997) indicated the model’s success in predicting the release of cinnamaldehyde in simulated mouth conditions. Investigating the role of physiological factors and microcapsules properties revealed that interpersonal differences play a more important role in determining the release behavior of cinnamaldehyde from high amylose starch capsules. Model parameters were also optimized using the SNOPT algorithm.

Keywords

Main Subjects

Food Nanotechnology

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